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Universidade do Minho
Escola de Engenharia
José Pedro Oliveira Fernandes
Developing an Ultrasound-based
Water Treatment System
Outubro de 2023
UMinho | 2023 José Pedro Oliveira Fernandes Developing an Ultrasound-based
Water Treatment System
José Pedro Oliveira Fernandes
Developing an Ultrasound-based
Water Treatment System
Dissertação de Mestrado
Mestrado em Engenharia Mecânica
AE Sistemas Mecatrónicos
Trabalho efetuado sob a orientação do
Professor Doutor Hélder Jesus Fernandes Puga
Professor Doutor Paulo Jorge Ramisio Pernagorda
Universidade do Minho
Escola de Engenharia
Outubro de 2023
DIREITOS DE AUTOR E CONDIÇÕES DE UTILIZAÇÃO DO TRABALHO POR TERCEIROS
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Atribuição
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Developing an Ultrasound-based Water Treatment System
i
Developing an Ultrasound-based Water Treatment System
Acknowledgments
I extend my deepest gratitude to all those who played a direct or indirect role in my academic journey.
To my family, whose unwavering support and unshakable belief in me have been my cornerstone. To
my father, whose guidance, impassioned conversations about mechanical intricacies, and status as my
initial muse upon hearing the word ”mechanic” shaped my path.
To my brother, a perpetual source of youthful exuberance and, paradoxically, my primary motivation
to strive for a brighter, better world. I hope I’m setting an example worth following. Live and enjoy.
To my grandparents, for nourishing me both physically and emotionally, and for being a steadfast
presence even on the gloomiest or most stressful days.
To Bia, an inspiring figure to emulate, the Picasso of the graphic design, the most critical person and,
the future’s most annoying teacher.
To all my friends, thank you for sharing in every high and low, for the countless gatherings, melodies,
and conversations that defined this journey.
To Bruno, Dário, and Tiago, my trusted mechanical comrades for the past five years, thank you for
being my confidants and companions.
A heartfelt acknowledgment to my Society Loving the Planet Minho, for providing not only camaraderie
but also purpose, and a platform for environmental consciousness at the University of Minho.
To all the players I had the privilege of coaching, who provided a welcome escape from the rigors of
university life, I extend my heartfelt gratitude. Thank you for allowing me to be a part of your journey.
To Diogo, Grilo, and Inês, for their invaluable assistance and camaraderie in the laboratory these past
six months. Grilo thank you for being always there to help.
A special mention to the laboratory technicians and researchers, particularly Catarina, Filipe, Marcos,
Miguel, Sérgio, and Sónia, for their support and expertise.
To the University of Minho, the researchers, professors, and sponsors involved in the Res4Valor project,
my heartfelt thanks.
To the Department of Textile Engineering, for the provision of ultra-filtrated water.
To Professor Vítor Monteiro for his invaluable electronic support.
To all the teachers from whom I had the privilege of learning
To my supervisors, Hélder Puga and Paulo Ramísio, you have not only been fountains of wisdom but
also exceptional guides.
And finally, to the most vibrant butterfly and the brightest star in the night sky, it is done. I made it.
ii
STATEMENT OF INTEGRITY
I hereby declare having conducted this academic work with integrity. I confirm that I have not
used plagiarism or any form of undue use of information or falsification of results along the
process leading to its elaboration.
I further declare that I have fully acknowledged the Code of Ethical Conduct of the University
of Minho.
Developing an Ultrasound-based Water Treatment System
iii
Developing an Ultrasound-based Water Treatment System
Abstract
This dissertation examined the effects of ultrasound in different stages of a Wastewater Treatment
Plant (WWTP), focusing on adsorption and oxidation processes. Additionally, it provided guidance for the
proper design of an ultrasound-assisted equipment aimed at water treatment.
Initially, the physical effects of ultrasound treatment on water were explored. The initial
understanding of these phenomena guided the research in two distinct directions. On one hand, the
feasibility of combining ultrasound treatment with existing adsorption mechanisms was investigated. On
the other hand, the potential of this technology in isolation for wastewater treatment was examined.
In the context of wastewater treatment, sensors were developed to monitor acoustic cavitation within
the ultrasound equipment. After validating the sizing of this equipment, a study was conducted at a WWTP
to evaluate the effectiveness of ultrasound treatment in water contaminated with various pollutants and
organisms.
The application of ultrasound proved impactful in the initial moments. When applied to ultra-filtered
water, ultrasound treatment (Is=20.7 ±1.6 W·cm−2) in the first 18 seconds resulted in a 2.7-fold increase
in ORP and a 2.29-fold reduction in pH.
The combination of ultrasound treatment with the organic compound ”Nutrimais da Lipor” in
adsorption resulted in a Cu removal rate of 82%, surpassing conventional mechanical action by 4.3
times. The removal of CIP was accelerated, reaching the maximum adsorption capacity (70%) in 1
minute, being 1.75 times more effective than the mechanical approach. With the Kaolin adsorbent, both
methods showed comparable results after 1 minute.
Regarding the treatment of contaminated water at the WWTP, the developed sensors for monitoring
acoustic cavitation identified cavitation thresholds and transition zones, confirming the geometric
dimensions of the ultrasound chamber.
Applying ultrasound treatment with different powers (200 W, 400 W, and 800 W) showed a significant
variation in physicochemical parameters in the first 5 minutes, followed by stabilization and return to initial
values. COD decreased in the first 2 to 5 minutes, then returned to initial values. These results highlight the
potential of ultrasound treatment, especially in the initial stages of application, for accelerating processes
and the possibility of integration with other methods.
Keywords Adsorption, Cavitation, Piezoelectric, Ultrasound, Wastewater
iv
Developing an Ultrasound-based Water Treatment System
Resumo
A presente dissertação analisou os efeitos do ultrassom em diferentes fases de uma Estação de
Tratamento de Águas Residuais (ETAR), com foco nos processos de adsorção e oxidação. Além disso,
apresentou orientações para a conceção adequada de um equipamento auxiliado por ultrassom.
Inicialmente, exploraram-se os efeitos físicos do tratamento por ultrassons na água. A compreensão
inicial desses fenômenos orientou a pesquisa em duas direções distintas. Por um lado, investigou-se a
viabilidade da combinação do tratamento por ultrassons com mecanismos já existentes de adsorção. Por
outro lado, examinou-se o potencial desta tecnologia, de forma isolada, no tratamento de águas residuais.
No âmbito do tratamento de águas residuais, foram desenvolvidos sensores para monitorizar a
cavitação acústica dentro do equipamento de ultrassom. Após validar o dimensionamento deste
equipamento, conduziu-se um estudo numa ETAR para avaliar a eficácia do tratamento por ultrassons
em água contaminada por diversos poluentes e organismos.
A aplicação do ultrassom mostrou-se impactante nos momentos iniciais. Quando aplicado em água
ultrafiltrada, o tratamento por ultrassons (Is=20.7 ±1.6 W·cm−2) nos primeiros 18 segundos provoca
um aumento de 2.7 vezes do ORP e numa redução de 2.29 vezes do pH.
A combinação de tratamento por ultrassons com o composto orgânico ”Nutrimais da Lipor” na
adsorção, resultou numa taxa de remoção de Cu de 82%, superando 4.3 vezes a ação mecânica
convencional. A remoção de CIP foi acelerada, atingindo a capacidade máxima de adsorção (70%) num
1 minuto, sendo 1.75 vezes mais eficaz que a abordagem mecânica. Com o adsorvente Caulim, ambos
os métodos apresentaram resultados comparáveis após 1 minuto.
Relativamente ao tratamento de água contaminada da ETAR, os sensores desenvolvidos para
monitorizar a cavitação acústica permitiram identificar os limiares de cavitação e as zonas de transição,
bem como confirmar as dimensões geométricas da câmara de ultrassom.
Aplicando o tratamento por ultrassons com diferentes potências (200 W, 400 W e 800 W), observou-se
uma variação acentuada nos parâmetros físico-químicos nos primeiros 5 minutos, seguida de estabilização
e retorno aos valores iniciais. A COD diminuiu nos primeiros 2 a 5 minutos, para então retornar aos valores
iniciais. Estes resultados destacam o potencial do tratamento por ultrassom, nomeadamente nas fases
iniciais de aplicação, no acelerar de processos e na possibilidade de integração com outros.
Palavras-Chave Adsorção, Águas Residuais, Cavitação, Piezoelétrico, Ultrassom
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Developing an Ultrasound-based Water Treatment System
Table of Contents
Acknowledgments ii
Abstract iv
Resumo v
1 Introduction 1
1.1 Contextualization ................................... 1
1.2 Motivation ...................................... 2
1.3 Objectives ...................................... 3
1.4 Structure of the Dissertation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2 State of Art 5
2.1 Wastewater Treatment by Conventional Processes . . . . . . . . . . . . . . . . . . . 5
2.1.1 Characterization of Domestic and Industrial Wastewater . . . . . . . . . . . . 5
2.1.2 EmergentPollutants ............................. 9
2.1.3 Wastewater Treatment Plant . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.2 Wastewater Treatment by Ultrasound Assisted Systems . . . . . . . . . . . . . . . . . 17
2.2.1 Coagulation and Flocculation Enhanced by Ultrasound Treatment . . . . . . . 18
2.2.2 Adsorption Enhanced by Ultrasound Treatment . . . . . . . . . . . . . . . . 19
2.2.3 General Wastewater Treatment Enhanced by Ultrasound . . . . . . . . . . . . 22
2.3 Effects of Cavitation on Wastewater treatment . . . . . . . . . . . . . . . . . . . . . 23
2.3.1 Variables Affecting Sonochemical Reactions . . . . . . . . . . . . . . . . . . 29
2.3.2 Ultrasound Components and Functioning . . . . . . . . . . . . . . . . . . . 33
2.3.3 Acoustic Cavitation Characterization . . . . . . . . . . . . . . . . . . . . . 39
3 Development of a Sensor for Characterization of Acoustic Activity 41
3.1 Equipment Design and Integration . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
3.2 Piezoelectric Sensor Setup and Data Analysis . . . . . . . . . . . . . . . . . . . . . 48
3.3 Experimental Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
4 Experimental Evaluation 59
4.1 Physical Analysis of Ultrasound Action on Water . . . . . . . . . . . . . . . . . . . . 59
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Developing an Ultrasound-based Water Treatment System
4.1.1 Piezoelectric Calibration and Protective Layer Impact . . . . . . . . . . . . . 59
4.1.2 Cavitation Monitorization with Piezoelectric Sensors . . . . . . . . . . . . . . 63
4.1.3 Resonance Frequency Analysis of Piezoelectric Sensors . . . . . . . . . . . . 76
4.1.4 Ultrasound Effects on Water and Water-Oil Mixture . . . . . . . . . . . . . . . 80
4.2 Ultrasound Effects on Water Characteristics and Adsorption . . . . . . . . . . . . . . 83
4.2.1 Impact of Ultrasound on ORP and pH . . . . . . . . . . . . . . . . . . . . . 83
4.2.2 Ultrasound Impact on Adsorption Processes . . . . . . . . . . . . . . . . . . 85
4.3 Insights from the Experimental Analysis . . . . . . . . . . . . . . . . . . . . . . . . 90
5 Performance Assessment on a Wastewater Treatment Plant 93
5.1 Experimental Conditions and Setup . . . . . . . . . . . . . . . . . . . . . . . . . . 93
5.2 Analysis of Ultrasound Treatment Effects on Wastewater Parameters . . . . . . . . . . 95
6 Conclusions 105
6.1 Piezoelectric Sensor for Cavitation Characterization . . . . . . . . . . . . . . . . . . 105
6.2 Assessment of Impacts of Ultrasound on Wastewaterw . . . . . . . . . . . . . . . . . 106
6.3 FutureWorks .....................................107
References 107
Appendix A - Piezoelectric Datasheet 123
Appendix B - Calibration Extended Data of« Sensors 2 and 3 125
vii
Developing an Ultrasound-based Water Treatment System
List of Figures
Figure 2.1– Three main groups of possibles wastewater treatment, physical, chemical or biological.
During the conventional process, these can be combined between them.. . . . . . . . . . . . . . . . . . . . 11
Figure 2.2– Diagram of a WWTP and the primary procedures carried out during each phase of
liquid treatment. Image adapted from Shah et
al.
[45]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Figure 2.3– Sequence of coagulation and flocculation as part of wastewater treatment. Image
adapted from Teh et
al
. [52] .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
Figure 2.4– Mechanism of adsorption between a liquid and the absorbent. The process is
characterize by three main layers: absorbent, adsorbate and absorptive. Image adapted from
Ameri et
al
. [58]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Figure 2.5– Water phase diagram. The passage from liquid to vapour can occur by decreasing
the pressure like seen in cavitation (1-2) or increasing the temperature (1-3). Image adapted from
Franc et
al
. [99]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
Figure 2.6– Process of bubble formation and growth in cavitation. Bubble nuclei form, grow, and
reach a critical size, causing implosion and fragmentation. This cycle recurs. Image adapted from
Ashokkumar et
al
. [103]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Figure 2.7– Impact of the Pressure Variation on the Formation and Growing of Bubbles. The
constant compression and rarefaction lead to nucleation, growth by rectified diffusion, ending with
the implosion of the bubble. Image adapted from Mason et
al
. [105]. . . . . . . . . . . . . . . . . . . . . . 26
Figure 2.8– Hotspot, gas-liquid interface and bulk solution regions and their characteristics during
bubble implosion. Image adapted from Carpenter et
al
. [111]. . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
Figure 2.9– Sequence of Cellular Degradation by Cavitation. It begins with gas cavity formation due
to increased water vapour. The ensuing collapse releases destructive radicals, leading to cellular
destruction, augmented by mechanical stress from implosion. Image adapted from Fetyan et
al
.
[97]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
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Developing an Ultrasound-based Water Treatment System
Figure 2.10– Sound range along the spectrum and the position of the different types of ultrasound,
low frequency ultrasound, high frequency ultrasound and ultrasonic spectrum used in medical
diagnosis. Image adapted from Fetyan et
al
. [97]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
Figure 2.11– Typical configuration of an ultrasound device for water treatment application. (a) The
ultrasound tip consist of a horn emitting waves perpendicular to the ultrasound axis. Alternatively,
it may involve a waveguide and an acoustic radiator. Image adapted from Marin-Hernandez et
al
.
[136]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
Figure 2.12– Piezoeletric disk response with two different exciting possibilities. Mechanical force
yields voltage (direct effect for sensors); applied voltage induces dimensional change (indirect effect
for transducers). Image adapted from Sikalidis et
al
. [139]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
Figure 3.1– Equipment main components with focus on the exterior section and structural parts. . . 42
Figure 3.2– Part of the equipment responsible for the generation and propagation of the sound
waves and respective parts: Piezoeletric transducer, Waveguide, Flange, Booster and Acoustic
Radiator. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
Figure 3.3– System operation with water inlet and outlet for chamber cooling. The treated water
outlet can be positioned at the (a) bottom valve if contaminants tend to rise to the surface, or at
the (b) top if contaminants tend to settle. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
Figure 3.4– Design Concept A employs two tubes for wire passage: (a) with a dual entry at the top
for chamber access, and (b) a perpendicular tube for wire passage to the piezoelectric sensors. (c)
A detailed view emphasizes the connection between the tubes, highlighting the wire passage hole
and the superior plate securing the second tube.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Figure 3.5– Design Concept B employs a single curved tube for wire passage: (a) entering from the
bottom of the cylinder in a straightforward operation, (b) utilizing a double inlet accessory connected
with a threaded connection, and (c) establishing the wire connection to the piezoelectric sensors
via the superior passage on top of the tube. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
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Developing an Ultrasound-based Water Treatment System
Figure 3.6– Structural component to guide and attach all the wires from the sensor (a) Specifications
for tube dimensions and a technical drawing for manufacturing (b) Wended tube support for the
wire passage to the piezoelectric sensors after manufacturing. . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
Figure 3.7– Piezoelectric sensor configuration after polarization. Image adapted from Puga et
al
.
[156].. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
Figure 3.8– Piezoelectric sensors for the acoustic reading with a (a) front view of sensors 1, 2 and
3 and (b) the back view of the three once they have all the same construction.. . . . . . . . . . . . . . . . 49
Figure 3.9– Main Menu for the LabVIEW program with the Start, Help and Exit bottoms.. . . . . . . . . 50
Figure 3.10– LabVIEW code for the Main Menu with (a) sequence for the access to the Menu Start
or Help and (b) for close the program. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
Figure 3.11– Help Menu with all the explanations for utilization of the program and all the options
possible.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
Figure 3.12– LabVIEW Code for the Help Menu With Sequences for the Buttons. . . . . . . . . . . . . . . 52
Figure 3.13– Data Acquisition Menu with the FFT graphic, Impact Load and Voltage acquisition. It
is possible to set the recording time, the output file location, number of samples and rate and start
and stop the record. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
Figure 3.14– LabVIEW Code for Data Acquisition in the Recording and Acquisition Menu. . . . . . . . . 54
Figure 3.15– Test Positions 1 and 2. Position 1 is located at a distance of 50 mm from the water
level, while Position 2 is positioned 250 mm above it. The acoustic sensors are fixed to the interior
structure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
Figure 3.16– Experimental Setup for Impact Test. The positions ’zero’ and ’rebounding’ are
characterized by their respective heights and velocities. Data acquisition from the presented
piezoelectric element is facilitated by the NI cDAQ 9172 system connected to the computer. The
rebounding height is captured using a slow-motion camera. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
Figure 3.17– Tension Divider for Tension Reduction: (a) Breadboard utilized for electrical
connections. (b) Electrical circuit for the tension divider. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
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Developing an Ultrasound-based Water Treatment System
Figure 4.1– Voltage Measurement for Sensor 1 and its Respective Noise Threshold during the
calibration process. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Figure 4.2– Calibration Curve for Sensor 2 with Voltage Variation in Response to Impact Load. . . . . 60
Figure 4.3– Calibration Curve for Sensor 3 with Voltage Variation in Response to Impact Load. . . . . 61
Figure 4.4– Voltage as a Function of Impact Load: Sensor 2 exhibits a higher voltage reading for
each impact load. However, both sensors display similar temporal behavior, differing primarily in
sensitivity.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
Figure 4.5– Piezoelectric sensors after 90 seconds of cavitation at varying ultrasound frequencies
- from 100 W to 900 W, with 10-second intervals. (a) The three sensors were at the same level on
the chamber, with 80 mm difference from the water level. (b) Sensor 1 exhibited damages only on
areas with deficient epoxy cover. Sensors 2 and 3 displayed damages on the surface layer. . . . . . . 63
Figure 4.6– Magnitude variation of the sub-harmonic (f/2) for Sensors 1, 2, and 3 at Position 1. The
analysis is divided into three zones, Zone 1 (0 W to 500±10 W), Zone 2 (Beginning of cavitation,
500±10 W to 600±10 W), Zone 3 (Developed cavitation, after 600±10 W).. . . . . . . . . . . . . . . . . 64
Figure 4.7– Analysis of sub-harmonic magnitude variation for Sensors 1 and 3 at Position 1.
Standard deviation aside, line plots show consistent behavior, especially for lower values.
Cavitation threshold lies between 500 W and 600 W, marked by a sharp increase. Value at 350 W
is negligible, stemming from an instantaneous peak. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
Figure 4.8– Fast Fourier transform graphics for the sensor 1 at position 1 for (a) 260±10 W (b)
500±10 W and (c) 700±10 W. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
Figure 4.9– Fast Fourier transform graphics for the sensor 3 at the position 1 for (a) 260±10 W
(b) 500±10 W and (c) 700±10 W. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
Figure 4.10– Magnitude variation of the sub-harmonic for Sensors 1, 2, and 3 at Position 2. The
analysis is segmented into three zones: Zone 1 (0 W to 410 W ), Zone 2 (Beginning of cavitation,
410±10 W to 500±10 W), Zone 3 (Developed cavitation, after 500±10 W). . . . . . . . . . . . . . . . . . 68
xi
Developing an Ultrasound-based Water Treatment System
Figure 4.11– Analysis of sub-harmonic magnitude variation for Sensors 1 and 3 at Position 2. The
cavitation threshold is between 400±10 W and 500±10 W, marked by a sharp increase. Beyond
this threshold, the magnitude stabilizes with a slight decrease. . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
Figure 4.12– Fast Fourier transform graphics for the Sensor 1 at the Position 2 for (a) 260±10 W
(b) 500±10 W and (c) 700±10 W. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
Figure 4.13– Fast Fourier transform graphics for the sensor 3 at the position 2 for (a) 260±10 W
(b) 500±10 W and (c) 700±10 W. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
Figure 4.14– Bubble formation due to cavitation over 4 seconds. Cavitation flow changes in axial
and radial positions may interfere with acoustic readings due to waves propagating in different
directions within the same position. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
Figure 4.15– Cavitation generation by the ultrasound acoustic radiator (a) Ultrasound induces
cavitation with axial and radial movements, creating centrifugal flow. Axial movements at base
generate cavitation-aligned acoustic waves. (b) Acoustic streaming distribution along wave guide,
low and high center amplitude. (c) Conical bubble structure on ultrasound acoustic radiator tip. . . . 74
Figure 4.16– Analysis of the distribution of the noise on the voltage acquisition and it relation with
the sub-harmonic, harmonic and ultra-harmonic.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
Figure 4.17– (a) Voltage Values Recorded by Piezoelectric Sensor 1. (b) Corresponding Impact Load
Calculated Using the Previous Calibration Line and the mean voltage value.. . . . . . . . . . . . . . . . . . 75
Figure 4.18– (a) Voltage Values Recorded by Piezoelectric Sensor 2. (b) Corresponding Impact
Load Calculated Using the Previous Calibration Line and the mean voltage value.. . . . . . . . . . . . . . 76
Figure 4.19– Piezoelectric sensors with two geometries. Piezoelectric A represents the unmodified
piezoelectric, while Piezoelectric B denotes the final geometry and its corresponding Epoxy layer. . . 77
Figure 4.20– Impedance graphic for piezoelectric A with the Resonance t 44,550 Hz and anti-
resonance at 45,480 Hz.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
Figure 4.21– Impedance graph for Piezoelectric B, which includes the epoxy layer, two distinct
resonances and anti-resonance are evident: (a) at 44,550 Hz and 46,500 Hz and at (b) 46,500
Hz and 47,520 Hz. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
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Developing an Ultrasound-based Water Treatment System
Figure 4.22– Ultrasound Resonance Test. (a) Conducted at different levels of submersion in water.
(b) Resonance at minimal water contact measured at 19,700 Hz. Decreasing submersion depth
led to a decrease in resonance frequency. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
Figure 4.23– Flocculation and coagulation test on water-oil mixture: (a) Experiment: 500 mL beaker
with 500 mL water and 10 mL SAE 10W40 oil. (b) Intermittent ultrasound treatment: 15 seconds
on, 15 seconds off, for 2 minutes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
Figure 4.24– Mixture visual behaviour over 3 minutes. (a) Initial state pre-ultrasound. (b) Movement
of water mixture in the first second after ultrasound, forming an inverted mushroom-shaped white
mixture. (c)(d) By the second second, the mixture is entirely white. . . . . . . . . . . . . . . . . . . . . . . . . 81
Figure 4.25– Sequence of Water Flow Movements upon Contact with Ultrasound. (a) Initially, the
wave propagates along the same axis as the ultrasound. (b) Upon reaching the bottom, the flow
tends to dissipate towards the base, causing radial movement. (c) The flow now has two paths:
it can ascend through the sides, escaping ultrasound, or remain at the bottom as refluxes. (d)
Escaped molecules are recirculated to the bottom due to continued ultrasound action. . . . . . . . . . . 82
Figure 4.26– Effects of acoustic cavitation on the ORP and pH of ultra-filtered water. (a) The ORP
increases 2.52 times fast with ultrasound action and then stabilize. (b) The decreases 2.29 times
faster and then stabilize as well.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
Figure 4.27– Effects of acoustic cavitation on the ORP and pH of ultra-filtered water. (a) The
ultrasound action promotes an exponential decrease over the ORP values and (b) the same action
promotes only a difference on pH after 70 seconds.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
Figure 4.28– Equipment used for the adsorption tests. (a) Ultrasound with the beaker with the
solution to treat. The beaker is in a water cooling system with a tank with water. (b) Rotational
machine for the mechanical action. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
Figure 4.29– Experimental procedure for the adsorption tests. Each experiment has 500 mL of
ultra-filtrated water, pollutant solution and adsorbent. In some cases, the adsorbent is not used.
The time points for the samples removal it were 0, 1, 5, 15 and 30 minutes.. . . . . . . . . . . . . . . . . 87
Figure 4.30– Hanna 83300 for the measurement of inorganic pollutants concentration on the
samples. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
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Developing an Ultrasound-based Water Treatment System
Figure 4.31– Ciprofloxacine removal rate and it temperature during the exposition time, combining
the ultrasound with (a) Kaolinite and with (b) Organic Compound. . . . . . . . . . . . . . . . . . . . . . . . . . 89
Figure 4.32– Copper removal rate during the 30 minutes exposition time, combining the ultrasound
with (a) Kaolinite and with (b) Organic Compound.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
Figure 5.1– Experimental Setup for Ultrasound Cleaning in ETAR of Serzedo. The ultrasound unit
is linked to both the power supply and a computer for system control. The transducer is cooled
using compressed air supplied by an air compressor.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
Figure 5.2– Experimental Study Scheme with Real Wastewater: A 500 mL sample is collected at
0, 2, 5, 10, and 20 minutes, followed by analysis using the HANNA HI98494. An 80 mL sample
is extracted from the initial 500 mL for subsequent laboratory testing, while the remaining solution
is returned to the chamber. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
Figure 5.3– Variation of parameters that are indicators of chemical reactions on wastewater
treatment with application of a acoustic power of 200 W. (a) pH and ORP (b) Temperature and
Dissolved Oxygen. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
Figure 5.4– COD removal with application of a acoustic power of 200 W.. . . . . . . . . . . . . . . . . . . . 97
Figure 5.5– Variation of parameters that are indicators of chemical reactions and biological and
organic reaction along wastewater treatment with application of a acoustic power of 200 W. (a)
N−NH−
4and N−NO−
3(b) Ntotal and P O−
4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98
Figure 5.6– Variation of parameters that are indicators of chemical reactions on wastewater
treatment with application of a acoustic power of 400 W. (a) pH and ORP (b) Temperature and
Dissolved Oxygen. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
Figure 5.7– COD removal with application of a acoustic power of 400 W.. . . . . . . . . . . . . . . . . . . . 99
Figure 5.8– Variation of parameters that are indicators of chemical reactions and biological and
organic reaction along wastewater treatment with application of a acoustic power of 400 W. (a)
N−NH−
4and N−NO−
3(b) Ntotal and P O−
4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
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Developing an Ultrasound-based Water Treatment System
Figure 5.9– Variation of parameters that are indicators of chemical reactions on wastewater
treatment with application of a acoustic power of 800 W. (a) pH and ORP (b) Temperature and
Dissolved Oxygen. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
Figure 5.10– COD removal with application of a acoustic power of 800 W. . . . . . . . . . . . . . . . . . . . 101
Figure 5.11– Variation of parameters that are indicators of chemical reactions and biological and
organic reaction along wastewater treatment with application of a acoustic power of 800 W. (a)
N−NH−
4and N−NO−
3(b) Ntotal and P O−
4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
Figure 5.12– COD removal comparison for the three powers of 200 W, 400 W and 800 W. . . . . . . . 104
Figure A.1– Data-sheet of the piezoelectric device provided by the manufacturer. . . . . . . . . . . . . . . 124
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Developing an Ultrasound-based Water Treatment System
List of Tables
Table 2.1– ORP ranges for each chemical reaction in water [31].. . . . . . . . . . . . . . . . . . . . . . . . . . 7
Table 2.2– Water Quality Classification based on BOD5and COD [34]. . . . . . . . . . . . . . . . . . . . . . 8
Table 3.1– Sensor requirements for the design and development of the acoustic sensor reading.. . . 44
Table 3.2– Data Acquisition Parameters for the NI cDAQ 9172.. . . . . . . . . . . . . . . . . . . . . . . . . . . 58
Table 4.1– Resonance and Anti-Resonance comparison between Piezoelectric A and B. . . . . . . . . . 78
Table 4.2– Insights provided by the data analysis from the chamber sensorization.. . . . . . . . . . . . . 91
Table 4.3– Insights provided by the data analysis from the application of Ultrasound on water. . . . . 91
Table 4.4– Insights provided by the data analysis from the aplication of Ultrasound with adsorption
processes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
Table 5.1– Physical and Chemical Parameters of Wastewater Before the Ultrasound Assisted
Treatment with each Different Power. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
Table 5.2– Physical and chemical parameters for the wastewater treated with ultrasound along the
experimental test. Parameters at 0, 2, 5, 10 and 20 minutes.. . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
Table B.1– Experimental data of sensor 2 and corresponding calibration results with the 0.30 g
sphere.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
Table B.2– Experimental data from sensor 2 and corresponding calibration results with the 2.02
grams sphere.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
Table B.3– Experimental data from sensor 2 and corresponding calibration results with the 0.88
grams sphere.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
Table B.4– Experimental data from sensor 3 and corresponding calibration results with the 0.30
grams sphere.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
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Developing an Ultrasound-based Water Treatment System
Table B.5– Experimental data from sensor 3 and corresponding calibration results with the 2.02
grams sphere.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
Table B.6– Experimental data from sensor 3 and corresponding calibration results with the 0.88
grams sphere.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
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Developing an Ultrasound-based Water Treatment System
List of Symbols
Abbreviations, Initials, and Acronyms
A Ultrasound Amplitude µm
BOD Biomechanical Oxygen Demand -
BNR Biological Nutrient Removal -
CIP Ciprofloxacin -
COD Chemical Oxygen Demand mV
CO2Carbon Dioxide -
DBPs Disinfection by-products -
EC Emergent Pollutants -
EPR Electron Paramagnetic Resonance -
H Hydrogen -
HO Hydroxyl Radical -
H2O Water -
H2O2Hydrogen Peroxide -
MA Mechanical Action -
O3Ozone -
OC Organic Compound -
OD Oxygen Demand mg/L
PAHs Poly Aromatic Hydrocarbons -
pH Potential of Hydrogen -
R Resistance Ω
TDS Total Dissolved Solids mg/L
TiO2Titanium Dioxide -
TOC Total Organic Carbon mg/L
TN Total Nitrogen mg/L
US Ultrasound -
UV Ultra-Violet -
WWTP Wastewater Treatment Plant -
ZnO Zinc Oxide -
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Developing an Ultrasound-based Water Treatment System
Roman Symbols
c Speed of Sound 343 m/s
f Frequency Hz
I Current A
L Length m
LIIntensity of Sound dB
M Molar Mass g/mol
m Mass kg
p Pressure MPa
P Power W
IsUltrasound Intensity W/m3
T Temperature ºC
t Time s
V Volume m3
Z Acoustic Impedance Ω
Greek Symbols
γSurface Tension N/m
λWavelength µm
ωAngular Velocity rad/s
σElectrical Conductivity µS/cm
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Developing an Ultrasound-based Water Treatment System
1. Introduction
1.1 Contextualization
Water, a vital global resource, has been facing escalating challenges in recent years. Access to clean
water, recognized as a fundamental human right by the Union Nations, is indispensable for a healthy and
dignified life [1]. However, increasing water scarcity poses substantial risks to communities worldwide,
imperiling standards of food production, goods manufacturing, sanitation, and public health [2].
Over the past four decades, global water usage has been mounting at a rate of 1% annually, with
emerging economies expected to sustain this trend until 2050 [3]. Concurrently, the availability of
freshwater per capita is dwindling, with Africa and Asia experiencing the most pronounced declines at
41% and 30%, respectively, while Europe displays a more modest reduction at 3% [3]. Even in Europe,
30% of countries encountered water scarcity conditions during the Summer of 2015 [4]. Currently, 10%
of the global population resides in regions facing high or critical water stress [3].
In tandem with these challenges, climate change presents a formidable obstacle for the future,
precipitating various human and economic repercussions. Projections estimate a global population of
8.6 billion by 2030, potentially surging to 9.7 billion by 2050, intensifying pressure on water resources.
Each additional person necessitates 1,300 m3of water annually [5].
Wastewater treatment stands at the forefront of critical global challenges. As industrial, domestic,
and agricultural activities continue to generate wastewater laden with organic and inorganic pollutants,
the need for effective treatment methods has become increasingly urgent [6]. Conventional approaches,
including coagulation, biological oxidation, absorption, and ion exchange, are struggling to keep pace
with the escalating release of organic compounds and the emergence of contaminants. These pollutants,
derived from an array of sources such as medical and recreational drugs, personal care products, industrial
chemicals, and more, have infiltrated wastewater treatment plant effluents, surface water, groundwater,
and even drinking water [7–9].
Moreover, the inadequacies of current treatment methods are evident in their limited ability to ensure
total disinfection of wastewater. The high toxicity and carcinogenicity of certain pollutants pose a significant
challenge, necessitating the breakdown of refractory molecules into smaller, more amenable forms for
further oxidation through biological methods [10]. Chlorination, a common method for disinfection due to
its cost-effectiveness and ease of implementation, falls short in eliminating persistent toxic by-products. It
is also ill-suited for addressing wet weather pollution and urban runoff [11].
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Developing an Ultrasound-based Water Treatment System
1.2 Motivation
As wastewater treatment facilities emerge as major (indirect) emitters of organic micro pollutants into the
aquatic environment, there is an evident and pressing need for the implementation of new technologies
to ensure the comprehensive removal of contaminants [12, 13]. In this context, Advanced Oxidation
Processes (AOPs) have gained prominence. These processes, characterized by numerous radical reactions
that target recalcitrant organic compounds, offer a potential solution with their low selectivity and ability to
mineralize contaminants into harmless compounds [7, 14].
In light of the pressing challenges in wastewater treatment outlined above, the exploration of innovative
and effective solutions has become paramount. One such promising avenue lies in the integration of
ultrasound technology. Ultrasound, known for its versatility and non-invasive nature, has demonstrated
remarkable potential in enhancing wastewater treatment processes. It offers a clean and chemical-free
alternative, steering clear of the production of toxic compounds often associated with traditional treatment
methods [7, 15].
The potential of ultrasound in revolutionizing wastewater treatment is underscored by its capacity to
efficiently remove a wide range of contaminants. From bacteria to pharmaceuticals, ultrasound’s efficacy
in eliminating pollutants is a testament to its versatility [16–18]. Its simplicity and lack of reliance on
chemical interactions, which can lead to the formation of harmful by-products, set ultrasound apart as a
sustainable and environmentally conscious solution [13, 15].
This research is further motivated by its integration into the larger ”Res4Valor” project. This project
delves into the adsorption behavior of organic compounds, aiming to evaluate the efficiency of various
filter media in retaining pollutants. The insights gained from this endeavor will not only contribute to the
development of selection criteria and system designs for environmental protection but also form the
foundation for a comprehensive comparison between adsorption and ultrasonic cavitation. The potential
synergy between these wastewater treatment technologies holds promise for a more sustainable and
effective approach to tackling water pollution.
In the face of escalating wastewater challenges, harnessing the power of ultrasound presents an
opportunity to redefine the landscape of wastewater treatment. This research endeavors to unlock the full
potential of ultrasound technology, offering a beacon of hope for a cleaner, more sustainable future.
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Developing an Ultrasound-based Water Treatment System
1.3 Objectives
This work focuses on two main objectives related to wastewater treatment. The first objective is to evaluate
the effects of ultrasound on various components of a wastewater treatment plant, with a specific focus
on the adsorption process and oxidation. The second objective is to suggest the guidelines for a correct
conception of an equipment assisted by ultrasound to auxiliary the wastewater treatment.
The primary objective is to study the impact of ultrasound waves on wastewater treatment
processes. This entails an examination of acoustic cavitation across various phases of wastewater
treatment, including flocculation, coagulation, oxidation and adsorption. Additionally, will be investigated
the effects of ultrasonic cavitation on water and oil-water mixtures. The study will extend to water
samples containing both organic and non-organic matter to assess pollutant removal. Special attention
will be given to the adsorption process, particularly with respect to an organic compound and Kaolinite.
This investigation aims to ascertain if ultrasound can effectively enhance adsorption processes.
In addition to the research on ultrasound effects, this work seeks to set the guidelines for develop an
ultrasound equipment for wastewater treatment. The equipment will undergo validation through various
tests, with a particular focus on developing mechatronic devices to monitor acoustic cavitation inside the
ultrasound chamber. The success of the prototype is directly linked to sensorization. The instruments
used to monitor acoustic cavitation will provide crucial insights into the functioning of ultrasound and the
design of the chamber.
To establish a comprehensive perspective on the potential of ultrasound in wastewater treatment, it
is intended to study diverse physical and chemical water parameters over varying duration and under
different ultrasound power settings. This extensive analysis seeks to integrate the data garnered from the
preceding experiments, allowing for a comprehensive understanding of ultrasound’s impact on wastewater.
Ultimately, this aims to offer valuable insights that will guide the development of future equipment. At the
same time, the study intends to understand and validate the variation of acoustic cavitation over time.
This research aims to investigate the impact of ultrasound on wastewater treatment and analyze the key
factors influencing its performance. The study seeks to evaluate the technology’s potential for improving
wastewater treatment processes and aims to achieve a comprehensive understanding of ultrasound and
its associated mechanisms.
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Developing an Ultrasound-based Water Treatment System
1.4 Structure of the Dissertation
This dissertation is divided into six parts, commencing with the Introduction addressing the wastewater
treatment problem, its consequences, and the potential contribution of advanced oxidation processes to
enhance the removal of emergent pollutants. The main objectives of this dissertation are also outlined.
The second chapter lays the foundation for the exploration of established knowledge. It begins with
an overview of wastewater treatment plants and their characteristics. Parameters ensuring water quality
are presented, alongside discussions on emergent pollutants. Subsequently, a comprehensive review
of literature pertaining to the utilization of ultrasound as an assisting process for wastewater treatment
techniques is provided. Special attention is given to coagulation, flocculation, adsorption, and general
wastewater treatment with ultrasound.
The chapter culminates in a thorough investigation of cavitation phenomena, its introduction in
chemistry, and the underlying principles governing its characterization.
The subsequent chapter introduces the equipment, detailing its features and the requisites necessary
for developing the sensor for acoustic characterization, along with the sensor development process.
Following the equipment development chapter, the dissertation proceeds to the experimental
evaluation of the sensors, as well as the effect of ultrasound on water. This chapter encompasses the
calibration of sensors and their integration into the chamber to comprehend cavitation phenomena.
Concurrently, it presents the results of cavitation on water, both with and without oil mixture.
Additionally, the augmentation of adsorption processes is assessed. The chapter concludes with insights
gleaned from the experimental tests.
Post the experimental evaluation, a real case study is presented involving the performance
assessment of a wastewater treatment plant. Here, the impact of ultrasound cavitation on various water
quality parameters is evaluated.
In the conclusions, the discussion is partitioned to address sensorization, the impact of water on water
with contaminants, and culminates with prospective directions for future research.
The dissertation concludes with an appendix containing piezoelectric characteristics and calibration
data, followed by the list of references for this work.
4
Developing an Ultrasound-based Water Treatment System
2. State of Art
This chapter serves as a comprehensive bibliographic overview of wastewater and its treatment
processes. It encompasses the definition and key quality parameters for wastewater assessment, as well
as the conventional treatment methods. Additionally, it delves into the integration of ultrasound to
enhance these processes. Furthermore, the chapter provides a thorough exploration of ultrasonic
cavitation phenomena and the underlying principles governing its characterization.
2.1 Wastewater Treatment by Conventional Processes
Decree-Law No. 152/97 outlines water quality standards, notably for surface water, distinguishing
between domestic and industrial wastewater [19]. Decree-Law No. 236/98 further refines these
categories, introducing urban wastewater [20].
Domestic wastewater arises from residential and service buildings, primarily from human
metabolism and household activities. Industrial wastewater encompasses non-domestic activities,
including manufacturing and commercial processes. Urban wastewater encompasses a blend of
domestic, industrial, and rainwater sources in urban areas [20].
2.1.1 Characterization of Domestic and Industrial Wastewater
A wastewater treatment plant should possess the capacity to receive wastewater from diverse sources,
highlighting the importance of employing standardized quality parameters to comprehensively assess the
composition of the wastewater at both the inlet and throughout the treatment process.
Substances found in water can have diverse origins. Wastewater constitutes a complex mix of dissolved
or suspended substances, alongside a variety of microorganisms. These substances can be classified into
four types based on their particle size: those above 10−3µm are dissolved or in molecular dispersion,
from 10−3to 1 µm are in dispersion or colloidally suspended, up to 10 µm in fine suspension, and up to
100 µm in coarse suspension [21, 22].
Qualitative characterization of wastewater is divided into three main groups: physical, chemical, and
microbiological. This characterization is essential to ensure that the treatment process is adequate and
systematic [21].
The quality and quantity of pollutants in wastewater vary greatly depending on the characteristics of
different countries and populations. Worldwide, these parameters change due to social, economic, and
cultural differences. A study by Tchobanoglous et
al
. [23] investigated various pollutants in different
5
Developing an Ultrasound-based Water Treatment System
countries, revealing that wastewater treatment plants need to be adjusted and flexible enough to adapt to
the diverse types of wastewater found in each country and region. To assess water quality, it is necessary
to consider various parameters. Among the important physical properties that will be considered in this
study, are solid concentration, turbidity, colour, and temperature [21].
Total solids in wastewater encompass both organic and inorganic substances. The organic portion
is referred to as total volatile solids (TVS), while the other suspended solids are retained by wastewater
filtration. Turbidity measures the inverse of the transparency characteristic, indicating the penetration of
light into water. True colour is defined as the colour observed after the filtration of suspended particles.
The colour can be influenced by both inorganic and organic substances. Temperature is another critical
parameter, as it affects density, viscosity, solubility, and can accelerate biochemical processes [21, 24, 25].
Regarding chemical characteristics, there are countless sources of pollutants, resulting in millions
of different chemical substances in wastewater. Characterizing water quality by identifying the specific
present chemicals is virtually impossible. Instead, the chemical characterization of the pollutant is based
on grouping the compounds according to their similar chemical properties, such as organic matter, total
nitrogen and pesticides [21].
One of the primary parameters to evaluate is the pH value, which assesses the concentration of H+
ions in the water. The pH is a measure of the potential of hydrogen ions (Hydronium) in the aqueous
solution. Jensen et
al
. [26] defined pH as the negative logarithm of the hydrogen ion concentration, or in
other words, the concentration of Hydronium ions, Equation 2.1.
pH =−log[H3O+](2.1)
The pH measurement provides information about the balance between acidic and basic chemicals
present in the analysed sample. It describes the concentrations of hydronium (H3O+) and hydroxide
(OH−) ions in the aqueous solution. The pH scale ranges from 0 to 14 and is logarithmic, meaning
that each unit change represents a tenfold difference in acidity or alkalinity. The neutral point is at pH 7,
below which the solution is considered acidic, and above which it is considered alkaline. Acidic reactions
have more free hydronium ions (positively charged), while alkaline reactions have more negatively charged
hydroxide ions. pH measures the activity of hydrogen ions in the solution [27]. By measuring pH, it is
possible to identify the ongoing chemical reactions in the water [28].
ORP (Oxidation-Reduction Potential) measures how one substance can oxidize or reduce another
substance. Essentially, it indicates the electric potential of a liquid at a specific temperature. ORP is
measured using a chemical-inert platinum electrode immersed in the solution sample. The electrical
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Developing an Ultrasound-based Water Treatment System
potential is then read relative to the reference electrode, and the value is presented in millivolts (mV) or
Volts (V) [29].
The measurement values provided by ORP indicate whether a substance tends to undergo oxidation
or reduction when in contact with another substance. In other words, ORP measures if a substance is
more likely to lose or gain electrons during a chemical reaction. Oxidation refers to the loss of electrons,
while reduction involves the gain of electrons. The ORP meter’s measurement is a result of the relationship
between oxidizing agents and reducing agents in the solution [30].
Biochemical reactions can be diagnosed by comparing the ORP value with the corresponding values in
Table 2.1. ORP indicates the ability of wastewater to allow the occurrence of specific biological reactions.
The lifespan of bacteria in water can be easily detected by ORP, making it a valuable tool in controlling
water treatment processes and identifying prevalent reactions [31].
ORP is a crucial parameter in drinking water supply systems, helping maintain high oxidation levels
through sanitization to prevent contamination. It’s instrumental in evaluating water quality and the efficacy
of sanitizing agents. Monitoring ORP enables the detection of potential issues that could affect water quality
[28].
Table 2.1: ORP ranges for each chemical reaction in water [31].
Biochemical Reaction ORP range (mV)
Nitrification +100 to +350
cBOD degradation +50 to +250
Biological phosphorus removal +25 to +250
Denitrification +50 to -50
Sulfide formation -50 to -250
Biological phosphorus release -100 to -250
Acid formation -100 to -225
Methane production -175 to -400
Organic matter in water can be classified into two main types: biodegradable and
non-biodegradable. Biodegradable compounds are predominantly composed of proteins, carbohydrates,
and lipids. Their degradation is facilitated by redox reactions, contingent on the final electron acceptor.
This process can be further categorized as aerobic (in the presence of oxygen as the acceptor), anoxic
(utilizing nitrate or nitrite as the acceptor), and anaerobic (with organic compounds serving as the
acceptor) [21].
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Developing an Ultrasound-based Water Treatment System
To assess the organic matter present in water, three commonly used parameters are Biochemical
Oxygen Demand (BOD), Chemical Oxygen Demand (COD), and Total Organic Carbon (TOC).
Together, these parameters provide a comprehensive evaluation of the oxidizable organic matter.
BOD (Biochemical Oxygen Demand) is a critical parameter that quantifies the amount of oxygen
utilized during the biochemical oxidation of organic matter in water over a specified time period and at a
particular temperature, typically for 5 days at 20 °C. This parameter indirectly assesses the
biodegradable organic matter in water, including carbohydrates, proteins, and fats. The measurement is
based on the consumption of dissolved oxygen, which is proportional to the amount of organic matter
that undergoes biochemical oxidation [21, 22].
Chemical Oxygen Demand (COD), on the other hand, evaluates the amount of organic matter in water.
It is determined by measuring the amount of oxygen required for the chemical oxidation of organic matter
using potassium dichromate under standardized conditions [32].
Total Organic Carbon (TOC) measures the overall concentration of organic matter in water. It is used
to determine the amount of carbon-containing compounds present in a sample [33]. These parameters,
in combination, provide valuable information about the presence and extent of organic pollutants in
wastewater, helping in wastewater treatment and environmental management.
In Table 2.2, it is possible to observe the information that COD and BOD provide regarding water
quality, along with the acceptable ranges for each parameter [34].
Table 2.2: Water Quality Classification based on BOD5and COD [34].
Indicator Value Range (mg/L) Water Quality Classification
BOD5 < 3 Excellent
3 < BOD5 < 6 Good
6 < BOD5 < 30 Acceptable
30 < BOD5 < 120 Contaminated
BOD5 > 120 Heavily Contaminated
COD < 10 Excellent
10 < COD < 20 Good
20 < COD < 40 Acceptable
40 < COD < 200 Contaminated
COD > 200 Heavily Contaminated
8
Developing an Ultrasound-based Water Treatment System
2.1.2 Emergent Pollutants
Emerging pollutants refer to new compounds or chemicals that lack regulatory status, and whose effects
on the environment and human health remain unknown. Consequently, establishing a definitive
maximum allowable concentration in sanitized water becomes a challenging task. Currently, the impacts
of substances like phthalates, pharmaceutical compounds, PAHs, PCBs, and Bisphenol A remain
uncertain, highlighting a significant gap in our understanding [35]. This category encompasses a broad
spectrum of contaminants, ranging from pharmaceuticals and personal care products to plastic waste,
pesticides, and metals. Detecting and characterizing these pollutants presents difficulties due to their
varied sources, diverse forms, and complex behaviour [36, 37].
These emerging pollutants stem from a range of sources, including hospital wastewater discharge,
illicit drug use, municipal sewage, discharges from wastewater treatment plants (WWTPs), landfill leachate,
among others [38]. Their presence is particularly concerning considering their potential to contaminate
soil, rivers, surface water, and even groundwater. Consequently, they may be transferred from soil to plants
and ultimately reach consumers, leading to the presence of pollutants in crops and potentially impacting
human consumption [39].
Ciprofloxacin (CIP) belong to te group of emergent pollutants, in this case from the pharmaceuticals.
It belongs to the fluoroquinolone group of broad-spectrum antibiotics and finds extensive use globally in
treating various bacterial infections, including those affecting the urinary, respiratory, gastrointestinal, skin,
bone, and joints. With a chemical formula of C17H18FN3O3 and a molecular weight of approximately
331.34 g/mol [40], it is a pivotal drug in modern medicine.
Despite its therapeutic benefits, the environmental impact of CIP is a growing concern due to its
low biodegradability, leading to its accumulation in ecosystems. This accumulation poses risks such
as interference with non-target pathogens, plant photosynthesis, structural alterations in algae, and the
emergence of antibiotic-resistant bacteria. Notably, CIP has been consistently detected in effluents from
wastewater treatment plants, surface waters, and groundwater, with recorded concentrations reaching as
high as 30 mg/L and 50 mg/L in pharmaceutical wastewater [40].
Copper, a prevalent heavy metal in wastewater, continues to be a major concern for wastewater
treatment plants [41]. Its presence in wastewater is pervasive due to its extensive utilization across various
industrial applications, establishing it as one of the most commonly employed metals in these processes.
The prevalence of copper in wastewater arises from its inclusion in a wide array of industrial processes,
ranging from electronics manufacturing to construction, plumbing, and even in agricultural practices as a
key component in pesticides and fertilizers.
9
Developing an Ultrasound-based Water Treatment System
Notably, Copper is classified as a heavy metal due to its remarkably high density, exceeding that
of water by fivefold. This characteristic, while contributing to its utility in industry, also underscores its
potential environmental and health risks. Even at relatively low concentrations, copper poses a substantial
toxic threat to both aquatic ecosystems and human health [42].
According to established guidelines from the World Health Organization and Portugal’s regulatory
framework, the allowable copper ion content in drinking water should not surpass 2 mg/L, underscoring
the significance of controlling copper levels to safeguard human health [43]. This guideline is rooted in
extensive research highlighting the potential harm posed by elevated copper concentrations.
The toxicity of heavy metals, including copper, is further compounded by their enduring presence and
propensity to accumulate within living organisms. This phenomenon is not confined to a particular species
but spans a broad spectrum of organisms, from microorganisms in the soil to aquatic plants and animals.
The accumulation of copper can lead to a cascade of severe health issues, ranging from carcinogenic
effects to disruptions in the nervous system and even renal failure, with potentially fatal consequences
when present in elevated amounts [41].
2.1.3 Wastewater Treatment Plant
A wastewater treatment plant enclose unitary treatment processes and operations designed to eliminate
pollutants and microorganisms, resulting in treated wastewater that meets specific quality standards [44].
There are three primary categories of wastewater treatment based on the process employed: Physical,
Chemical and Biological. These are employed sequentially to eliminate toxic compounds from the aqueous
solution. Figure 2.1 illustrates the key unitary processes utilized in each method. In a wastewater treatment
plant, a selection of these processes is employed, either individually or in combination, to ensure the final
effluent meets required standards [21].
Wastewater pollutants can exist in both dissolved and suspended forms. In an ordinary wastewater
treatment plant, there are five levels of treatment: preliminary, primary, secondary, tertiary, and advanced
treatment. Each level of treatment serves a purpose of removing pollutants and improving the quality of
the effluent [21].
In Portugal, the regulation of wastewater treatment plants is governed by Directive No. 91/271/CEE
and Decree-Law No. 152/97 [19]. These directives provide guidelines for the types of pollutants and
the appropriate treatment levels required for wastewater treatment in the country. By following these
regulations, wastewater treatment plants in Portugal can effectively treat wastewater and ensure that the
discharged effluent meets the necessary environmental standards [19].
10
Developing an Ultrasound-based Water Treatment System
Figure 2.1: Three main groups of possibles wastewater treatment, physical, chemical or biological. During
the conventional process, these can be combined between them.
The treatment comprises three phases: liquid, solid, and gas. The liquid phase encompasses
preliminary, secondary, tertiary, and advanced treatments. The primary objective of preliminary
treatment is the removal of solids, sand, and grease to optimize the effectiveness of subsequent
treatments, preventing blockages and contamination. This phase achieves the elimination of suspended
solids through sedimentation, decantation, or chemical coagulation [45].
After the secondary treatment, the effluent is expected to meet the quality requirements, with low
biodegradable organic matter and colloidal suspension. Biological processes take on significant
importance in this phase but are not the only ones. Following the biological reactor, there is a decanter
assisted by coagulation-flocculation to separate the biological and chemical flakes [21].
When needed, the tertiary and advanced treatments further improve the quality of water provided by the
last two. In the tertiary treatment, the main goal is to remove nutrients such as nitrogen and phosphorus.
On the other hand, the advanced process refines the water quality even further by eliminating pollutants
in residual concentrations [21].
Solid pollutants are removed in the preliminary treatment in grated, sieved, sand, and grease forms.
In the gas phase treatment, the primary focus is to diminish the odour from methane emissions. However,
for this study, only the liquid phase is of interest and will be addressed [46].
In Figure 2.2, it is possible to observe a schematic representation of a typical WWTP, focusing on
the liquid phase treatment. Each unitary treatment leads to the separation of pollutants, resulting in a
progressive cleaning of water and, during the processes, the release of some types of sludge.
11
Developing an Ultrasound-based Water Treatment System
Figure 2.2: Diagram of a WWTP and the primary procedures carried out during each phase of liquid
treatment. Image adapted from Shah et
al.
[45].
Preliminary treatment encompasses several mechanisms. The initial step is harrowing, responsible
for segregating larger solid waste. The subsequent phase, known as screening, refines the process further
with a more delicate retention mesh [22].
Once the major residues have been removed, the subsequent phases focus on extracting smaller
pollutants such as sand, oil, and grease. Desandation, grease and oil removal can be achieved using
the same equipment but serve distinct purposes. Desandation aims to extract sand from the effluent
by combining reduced fluid velocity with gravity-induced sand deposition. Conversely, techniques are
employed for oil and grease removal, primarily to accumulate grease on the surface [22].
Following the initial treatment of the wastewater effluent, the first treatment is implemented. Typically,
this treatment involves three key unitary processes: sedimentation, decantation, and flotation. These
processes lead to a reduction of TSS by approximately 50% to 70% and BOD by around 30% to 40% [47].
In the secondary treatment stage of wastewater treatment, the focus shifts towards the
implementation of biological methods for a more thorough purification process, targeting the removal of
a substantial amount of organic pollutants. This phase employs various processes, including activated
sludge, trickling filters, and rotating biological contactors, all designed to significantly reduce both BOD
and SST. Integral to this phase are microorganisms like bacteria and protozoa, crucial in breaking down
remaining organic matter. The secondary treatment concludes with a secondary decantation. However,
trace quantities of pollutants and biological matter persist in the treated water, necessitating tertiary and
refinement treatments. These employ more sophisticated processes, paving the way for potential water
reuse [22].
Tertiary treatment complements the preceding treatment stages by eliminating pollutants that persist
in the water, including pathogens, nutrients like nitrogen and phosphorus, and particles that are
12
Developing an Ultrasound-based Water Treatment System
challenging to remove. Nitrogen and phosphorus can be removed through biological or chemical means,
while disinfection aims to partially destroy or inactivate pathogens using chemical agents like ozone and
chlorine, and UV radiation. Filtration is typically performed prior to UV disinfection to remove suspended
particles. Additional treatments encompass coagulation, flocculation, sedimentation, activated carbon
adsorption, ion exchange, and reverse osmosis, all designed to remove specific pollutants through
physical and/or chemical processes [22].
Numerous techniques have been employed to extract pollutants from water, but many merely
relocate the pollution to another phase, necessitating further processing of solid waste and regenerating
adsorbents. To address this issue, alternative methods like biodegradation, ozonation, and advanced
oxidation processes have been adopted. Among these, photocatalytic degradation and AOPs have
emerged as promising techniques for completely mineralizing organic contaminants present in
wastewater and effluent streams [48].
To contextualize this thesis proposal and provide a comprehensive analysis, it is essential to expand
the examination of chemical coagulation, adsorption, and AOPs.
A crucial mechanism in water treatment is flotation. Its primary objective mirrors that of decantation,
involving the separation of solid or liquid particles suspended in water. These particles rise to the surface,
forming a buoyant layer. This process is commonly employed for grease treatment and is applied in
preliminary, secondary, and solid-phase treatment stages [21].
Particles with a lower density than water tend to rise towards the liquid’s surface. The viscosity of the
liquid directly impacts the movement of these particles, making it a more challenging process. There are
methods to improve efficiency, such as introducing compressed air, which adheres to suspended particles
during their ascent [49].
Separating colloidal suspended particles in water poses a significant challenge. Chemical coagulation
is the key process that destabilizes these particles, enabling subsequent flocculation. This step is integral to
wastewater treatment, enhancing the removal of solid sediments in both primary and secondary processes
and preparing for subsequent processes like filtration [50].
Flocculation follows coagulation, aggregating the micro-clots formed earlier. The underlying principles
of this process, along with unitary processes, are depicted in Figure 2.3. After flocculation, it becomes
necessary to separate the suspended solids from the water using various methods such as sedimentation,
flotation, filtration, and more [21].
In Figure 2.3, a visual representation of the processes over time is provided. These are crucial for the
effective treatment of water contaminants.
13
Developing an Ultrasound-based Water Treatment System
The initial step in this sequence involves the destabilization of colloidal particles through chemical
coagulation. This process hinges on the electrical charge, typically negative, that surrounds these particles.
The negative charge results in repulsion between particles, keeping them suspended in the water. The
stability of particle suspension in water is primarily dictated by the electrical charge of colloidal particles
and the double layer of ions enveloping them [21, 49].
To destabilize colloidal particles, it is imperative to neutralize the negative charges on their surfaces.
Upon introducing coagulant agents into the water, these disrupt the particles’ electrical charges, causing
them to draw nearer and form micro-flocs. Among the most frequently employed coagulants are ferric
chloride or alum, known for their positive electrical charge, which aids in effectively neutralizing the
negatively charged colloidal particles [51].
Once the colloidal particles are destabilized and broken apart through coagulation, the subsequent
step involves bringing them together to form larger aggregates or flakes. This crucial process is known as
flocculation. It typically entails gentle stirring or agitation to promote collisions between the destabilized
particles. This interaction allows the particles to adhere to one another, forming larger, easily removable
aggregates. These larger particles can be efficiently eliminated through processes such as sedimentation
or filtration [21].
The interplay between coagulation and flocculation is illustrated in Figure 2.3, providing a visual
representation of these essential water treatment stages [52].
Figure 2.3: Sequence of coagulation and flocculation as part of wastewater treatment. Image adapted
from Teh et
al
. [52] .
In the realm of tertiary wastewater treatment, a myriad of processes come into play to ensure the
effective elimination of heavy metals, oil emulsions, as well as inorganic and organic compounds. Among
the commonly employed methods are gravitational separation, centrifugation, coagulation, flotation,
adsorption, biological treatments, filtration techniques, and thermal oxidation [53].
In recent years, there has been a growing focus on the development of novel adsorption processes
14
Developing an Ultrasound-based Water Treatment System
aimed at enhancing the removal of both organic and inorganic pollutants from water. Adsorption
stands out as one of the most efficient, effective, and economically viable methods for water purification.
This technology boasts a wide array of adsorbent categories and finds applicability across various
research domains. Its appeal lies in its ability to provide cost-effective and highly efficient water
treatment, characterized by rapid kinetics, straightforward operation, and the absence of residual
by-products or sub-products. Adsorption plays a pivotal role in tasks such as separation, purification,
detoxification, and the metabolism of medicinal drugs [54, 55].
The essence of adsorption processes can be summarized as mass transfer phenomena, where
atoms, ions, or molecules migrate from a liquid phase onto a solid surface. This movement occurs due
to interactions, whether chemical or physical in nature [56]. This approach offers significant advantages,
including highly effective and rapid adsorption kinetics, compatibility with a wide range of target
contaminants, and the potential for developing a diverse array of commercial products. However, it’s
worth noting that adsorption methods are generally non-selective, and some adsorbents can be relatively
costly, with regeneration presenting certain challenges [57].
The process of adsorption involves the adherence of molecules or particles to the surface of a solid
material, resulting in the formation of a thin layer, as illustrated in Figure 2.4 [58].
Figure 2.4: Mechanism of adsorption between a liquid and the absorbent. The process is characterize by
three main layers: absorbent, adsorbate and absorptive. Image adapted from Ameri et
al
. [58].
At its core, adsorption involves the transfer of material from a fluid phase to a solid phase, making it
a fundamental separation process for concentrating materials from a bulk vapour or liquid phase onto the
surface of a porous solid [59].
There are two primary types of adsorption: physical adsorption and chemisorption, also known as
activated adsorption. Physical adsorption is governed by van der Waals forces and occurs when an
15
Developing an Ultrasound-based Water Treatment System
absorbent with a solid surface interacts with an adsorbate, typically a pollutant. These forces are
relatively weak and arise from temporary fluctuations in electron distribution within molecules. Generally,
this process is reversible but less specific in its interactions. On the other hand, chemical adsorption
involves ionic or covalent bonding between the adsorbate and the pollutant, resulting in more stable
connections but requiring a higher activation energy [60].
Innovations in adsorption technology have led to the development of various efficient adsorbents. Clay-
polymer composites, which combine natural clay minerals with polymeric materials, have demonstrated
enhanced capabilities in removing metal ions from aqueous solutions. Additionally, industrial by-products
like fly ash, iron slags, hydrous titanium oxide, and waste iron can be chemically modified to improve
their heavy metal ion removal efficiency through adsorption. Furthermore, low-cost bio-sorbents, such as
non-active biomass and non-living algae, have proven effective in removing heavy metal ions, including
copper, from industrial wastewater [60].
The continuous advancement and diversification of adsorption technologies offer promising avenues
for the efficient and environmentally responsible removal of pollutants from wastewater, contributing to the
overall improvement of water quality and the protection of natural ecosystems.
In the same way, and to respond to the sludge generation and the inability to treat effluents containing
high levels of recalcitrant compounds, other processes were developed.
Advanced Oxidation Processes (AOPs) are a class of treatments defined by their generation and
utilization of powerful transient species, predominantly hydroxyl radicals [61, 62].
Within wastewater effluents, the compounds present have the potential to undergo oxidation,
resulting in the formation of alternative species. Alternatively, a more favourable pathway involves
complete mineralization, wherein the compounds are converted into carbon dioxide and water. This
mineralization process is advantageous as it produces no secondary by-products or sludge [63].
As previously discussed, wastewater treatment plants (WWTPs) require upgrades to ensure the efficient
removal and destruction of emerging contaminants like toxins, pesticides, dyes, and pharmaceuticals.
Advanced oxidation processes (AOPs) encompass a range of powerful oxidative water treatment techniques
applied in diverse settings, including industrial plants, hospitals, and wastewater treatment facilities. This
category includes several methods, such as UV/O3, UV/H2O2, Fenton and photo-Fenton reactions, non-
thermal plasma treatments, sonolysis, photocatalysis, radiolysis, supercritical water oxidation, and others
[48, 53]. These processes involve the reaction of hydroxyl radicals or other reactive oxygen species with
pollutant species.
Organic pollutants commonly engage with hydroxyl radicals through either addition or hydrogen
16
Developing an Ultrasound-based Water Treatment System
abstraction pathways. This interaction leads to the creation of carbon-centred radicals, which
subsequently react with molecular oxygen to produce peroxyl radicals. Additionally, hydroxyl radicals
have the capacity to form radical cations by extracting an electron from electron-rich substrates. These
cations can undergo hydrolysis in aqueous environments, resulting in the production of oxidized
products. These oxidation by-products are generally less harmful and more readily amenable to
bioremediation [48, 61].
However, AOPs are known for their high cost and are often used as a pretreatment step. The radicals
mentioned earlier are highly effective oxidants but have a short lifespan and lower concentrations. AOPs
can also serve as a quaternary treatment in WWTPs to eliminate micro-pollutants and enhance the
disinfection process [48].
The hydroxyl radicals generated, exhibit characteristics such as being short-lived, easily produced,
powerful oxidants, electrophilic behaviour, ubiquitous in nature, highly reactive, and practically
non-selective. They have the ability to react with various organic compounds, leading to simpler and less
complex organic compounds initially. In the case of complete mineralization, hydroxyl radicals result in
the production of carbon dioxide, water, and inorganic salts, as demonstrated in Equation 2.2 [53, 61].
Organic Species +HO.⇒CO2+H2O+Inorganic ions (2.2)
AOPs offer several advantages over conventional methods, primarily the ability to convert complex
organic compounds into simpler ones or even into CO2and H2O without generating sludge. This
eliminates the need for additional treatment stages. AOPs are also effective in treating wastewater with
very low organic loads, containing dissolved organic compounds that are challenging to remove.
However, their drawback lies in their high cost, particularly with reagents like ozone, and the energy
requirements for ultraviolet technology. Consequently, AOPs are primarily considered for the alternative
treatment of wastewater that cannot undergo biological treatment. They may be used as a preliminary
treatment to convert recalcitrant pollutants into a form amenable to biological treatment or as a final
treatment step before discharge [53].
2.2 Wastewater Treatment by Ultrasound Assisted Systems
Researchers conducted studies on the ultrasound’s impact on various aspects of the wastewater
treatment process. The obtained results demonstrate the potential of ultrasound in enhancing oxidation
and organic degradation. As previously mentioned, the individual processes within a wastewater
17
Developing an Ultrasound-based Water Treatment System
treatment plant (WWTP) do not guarantee complete pollutant removal and have proven ineffective in
eliminating certain contaminants like microorganisms, fine clay and Emergent Pollutants [7].
To assess the efficacy of ultrasound, whether used independently or in combination with other
processes of treatment, the effects of ultrasound on pollutant removal at different points within the
WWTP were investigated. The areas of focus included flocculation, sedimentation, coagulation, the
removal of organic compounds and heavy metals, as well as the overall improvement of wastewater
treatment facilitated by ultrasound.
2.2.1 Coagulation and Flocculation Enhanced by Ultrasound Treatment
In-depth investigations into wastewater treatment methods have highlighted the potential for significant
improvements through the application of ultrasound treatment. In a study focused on sedimentation,
Vikulina et
al
. [64] explored the enhancement of suspended solids settling by combining ultrasound (0.3
- 0.5 W/cm2) with a coagulant. Experimental data demonstrated that the integration of ultrasound
resulted in a decreased requirement for coagulant injection, thereby reducing the overall need for
chemical additions.
This significant enhancement was reaffirmed by Ma et
al
. [65], where ultrasonic-flocculation
sedimentation outperformed sole flocculation sedimentation in terms of removing total phosphorus, total
nitrogen, reducing COD, BOD, and turbidity. Removal rates for TP, TN, BOD, COD Cr, and turbidity saw
respective increases of 16.1%, 12.7%, 9.1%, 20.0%, and 18.3% with ultrasound power of 60 W, during two
minutes and 10 g/L of flocculant.
Ultrasound treatment has demonstrated the capability to significantly enhance coagulation
processes. Özyonar et
al
. [66] highlighted the effectiveness of coupling ultrasound (180 W and 40 kHz)
with electrocoagulation in wastewater treatment applications. The combination with ultrasound treatment
significantly enhanced the removal efficiency to 99.9% reduction in Chemical Oxygen Demand (COD).
Additionally, it demonstrated remarkable colour removal rates for Reactive Red 241 and Disperse Blue
60, surpassing the rates achieved by electrocoagulation alone (87% and 92% respectively). Remarkably,
these outcomes were achieved in less than a minute.
Additionally, Trujillo-Ortega et
al
. [67] investigated a method that effectively removed up to 90% of
indigo dye and arsenic through the combined use of ultrasound treatment (300 W and 40 kHz) and
electrocoagulation [68].
Moreover, ultrasound treatment applied with coagulation, has shown significant improvements. Fast
et
al
. [69] examined turbidity removal efficiencies and found them comparable to conventional rapid mix
18
Developing an Ultrasound-based Water Treatment System
coagulation. Removal percentages ranged from 84.1% to 90.5% for Chitosan in the rapid mix process, and
84% to 97% for Chitosan in the ultrasound process (25 kHz and 100 W during 20 min).
Furthermore, researchers have explored the synergistic effects of ultrasound treatment when
combined with other Advanced Oxidation Processes. In pretreatment, Duckhouse et
al
. [70]
demonstrated enhanced E. Coli inactivation through the combination of sodium hypochlorite and
ultrasound treatment at 20 kHz and 850 kHz. Another study revealed that ultrasound disinfection at 20
kHz and 500 W, when combined with chlorine dioxide, led to a 50% improvement in inactivation [71].
Ultrasound treatment has proven to be a versatile and effective tool with biocidal properties. Phull
et
al
. [72] illustrated that 80% of chlorine removal is achievable with 15 minutes of sonication (20 kHz
and 30 W ·cm2). Additionally, ultrasound treatment on its own exhibited the power to reduce bacterial
colonies in water. The study also emphasized that integrating ultrasound treatment into the disinfection
process could lead to a reduction in the amount of required chlorine. The synergistic effect of combining
sonication with normal chlorination was observed to result in a significant amplification of their individual
effects, indicating that the combination is superior to sonication alone.
Stępniak
et al.
[73] examined the efficacy of ultrasonic coagulation assistance in the context of water
treatment. The findings revealed that, under the conditions of a vibration amplitude of 16 µm and a
frequency of 22 kHz over a period of 5 minutes, the removal of contaminants from water reached 29%.
Furthermore, when combined with aluminum sulfate as a coagulant, the coagulation efficiency experienced
a notable enhancement, exhibiting a 35% increase.
2.2.2 Adsorption Enhanced by Ultrasound Treatment
Researchers have delved into the augmentation of adsorption processes through ultrasound in wastewater
treatment, showcasing a significant enhancement in efficiency. One crucial area of focus has been the
study of emergent pollutants, with a particular emphasis on organic dyes. These dyes pose a significant
concern due to their widespread industrial use and the escalating contamination caused by them in recent
years.
In a similar study by Jun et
al
. [74], the role of ultrasound treatment in improving adsorbent dispersion
in water was examined. Lower ultrasound frequencies, 28 kHz compared with 580 kHz, demonstrated
superior performance in enhancing absorbent dispersion. Furthermore, the combination of ultrasound
treatment with the adsorbent yielded remarkable results. In just 5 minutes, this approach achieved 60%
removal of dye, more than double that achieved with conventional stirring assistance.
Dil et
al.
highlighted the influence of pH on the adsorption enhanced by ultrasound treatment,
19
Developing an Ultrasound-based Water Treatment System
demonstrating that higher values increased removal efficiency of heavy metals (Cadium and Cobalt) and
azo dyes (Methylene Blue (MB)) [75]. Lower pH levels resulted in positive charges on both dyes and the
adsorbent, leading to repulsion and reduced removal percentages. As pH levels increased from 2.0 to
5.0, removal efficiency improved. Above pH 5.0, dyes adhered more effectively, resulting in higher
removal percentages. At pH 6.0 was identified as the optimal condition for maximum removal in the
quaternary system.
The incorporation of copper-doped zinc sulfide nanoparticles loaded on activated carbon, assisted
by ultrasound, enhanced the removal of Auramine-O (AO), Erythrosine (Er), and Methylene Blue (MB).
Remarkably, this achieved total removal of the three dyes in just 2.5 minutes of application with a mere
0.04 g of absorbent and ultrasound parameters of 40 kHz and 130 W [76].
Numerous other studies have confirmed the effectiveness of acoustic cavitation in enhancing the
removal of various dyes [77], including AB92 and DR80, AM and BB FCF, Crystal Violet, MB and EY,
BR46, BB41, and MG, showcasing the broad applicability of this technique [55, 77–80].
Researchers have amassed compelling evidence supporting the use of ultrasound to enhance the
removal and oxidation of ciprofloxacin from contaminated water samples. Advanced oxidation processes
have proven effective in eliminating such pollutants, and when combined with ultrasound, their efficiency
is significantly augmented. Furthermore, ultrasound treatment on its own demonstrates the ability to
mineralize and eliminate ciprofloxacin from water.
In a study conducted by Olusholaet
al
. [81], the introduction of zinc oxide nanoparticles alongside
ultrasonic treatment bolstered the degradation of the pollutant. Results showed that ultrasound treatment
alone (20 kHz and 125 W) achieved a 30% degradation of CIP within just 20 minutes, with this efficiency
increasing to 50% when zinc oxide nanoparticles were introduced, at the same time. After one hour, the
ultrasound treatment alone, at low pH values, 1.75, reach a maximum removal of 76% and combined with
absorbent it reached 96%. It was observed that lower initial concentrations of CIP favored degradation,
same as low pH values.
Moreover, the utilization of a pulsing mode was found to be advantageous for degrading
pharmaceuticals with high diffusivity or hydrophobicity. This mode allowed compounds to diffuse and
accumulate at liquid-bubble interfaces during silent cycles, thereby facilitating the degradation process
[82].
In a study by Sutar et
al
. [83], ultrasound treatment alone achieved only a 5% degradation of CIP.
However, when combined with Laccase catalysis, the removal efficiency improved to 51%. The study also
revealed that the duty cycle of ultrasound significantly influenced the removal rate, with a 50% duty cycle
20
Developing an Ultrasound-based Water Treatment System
proving more efficient than 40% and 60%. The same study mention that with the same power, 75 W, the
ultrasound treatment with 22 kHz shows a better removal rate (50%) than 40 kHz (23%).
In the study by Kyzas et
al
. [84], complete removal of Ciprofloxacin was achieved by combining
ultrasound treatment (20 kHz and 120 W/cm2) with ferrous ions, hydrogen peroxide, and persulfate
activation within 60 minutes. However, it was noted that high pH levels reduced the removal rate due to
the destabilizing effect of ferrous ions on the structure, which in turn lowered the oxidation potential and
hindered the reaction between ferrous ions and hydrogen peroxide, leading to increased sludge production.
Furthermore, Chakma et
al
. [85] examined ultrasound treatment effect on CIP, reaching a maximum
removal rate of 38% (ultrasound treatment parameters: 37 kHz and 130 W) at the end of 30 minutes,
with low pH values found to enhance CIP removal. This study also explore the mechanisms behind
the CIP degradation, concluding that the ultrasound treatment is responsible for physical and chemical
degradation.
In a study by Bel et
al
. [86], ultrasound treatment at a frequency of 520 kHz and a power density of
92 W/L resulted in a maximum removal rate of 25% after 30 minutes, with lower pH values identified as
contributing to enhanced removal of CIP (initial concentration: 15 mg/L).
In another investigation, Igwegbe et
al
. [87] focused on a CIP concentration of 25 mg/L, revealing a
removal rate of 25% after 30 minutes of ultrasound treatment (60 kHz, 10 minutes application, and 500 W).
This study further validated the trend of increased CIP removal when ultrasound treatment was combined
with another advanced oxidation process. The combined processes of US, US/ZnO, and US/ZnO/PS
achieved removal rates of 35.93%, 70.48%, and 99.48%, respectively, at the end of 180 minutes.
In the context of ultrasound-enhanced adsorption for copper removal, in the study conducted by Gupta
et
al
. [88], the removal rates after 1 minute reached 80% with the adsorbent beeing water melon shell
and ultrasound treatment power of 90 W.
The study by Secondes et
al
. [89] focused on a hybrid process that combined ultrasound irradiation
(35 kHz) with activated carbon adsorption to tackle emerging contaminants (ECs) in synthetic
wastewater. This approach demonstrated enhanced adsorption capacity with ultrasound treatment. For
consequence, the improved removal was attributed to the combined effects of enhanced adsorption and
sonolytic degradation.
Like the case with Ciprofloxacin, ultrasonic treatment in conjunction with hydrous iron oxide proved
effective in reducing the final solution concentration of copper species in the pH range of 7.5 to 9.5 [90].
Regarding the use of Kaolin as an adsorbent enhanced by ultrasound, specific studies in the literature
are limited. However, previous research has confirmed the efficiency of kaolin in heavy metal removal
21
Developing an Ultrasound-based Water Treatment System
through adsorption, however there is a lake on the literature for the combination between acoustic cavitation
and Kaolin [91].
2.2.3 General Wastewater Treatment Enhanced by Ultrasound
The research on ultrasound cavitation’s impact on wastewater presents intriguing findings, particularly
when combined with other Advanced Oxidation Processes (AOPs). In a study by Rossi et
al
. [92], the
synergistic effect of ultrasound (24 kHz and 250 W) and ozone was explored in treating primary effluents.
This combined process exhibited remarkable removal efficiencies for various contaminants, including
soluble Chemical Oxygen Demand (sCOD) at approximately 60%, formaldehyde at about 50%, and
Methylene Blue Active Substances (MBAS) at over 90%. Additionally, the process displayed significant
disinfection capabilities, achieving a 4-log reduction for E. coli and a 5-log reduction for Total Coliforms.
In another investigation employing a sono-electrocoagulation system, Arka et
al
. [93] achieved removal
rates of 97.5% for COD and complete color removal. The study highlighted that COD and color removal
rates were enhanced at pH levels of 6, 7, or 8, but decreased in other pH ranges.
Serna-Galvis et
al
. [94] explored the cavitation effect of ultrasound (375 kHz and 88 W/L) on 17
emergent pollutants in water, both in isolation and in combination with other techniques. After 90
minutes, the concentrations of certain compounds increased when submitted to ultrasound treatment
alone. However, when combined with other processes like sono-Fenton, sono-photo-Fenton, and
sono-photo-Fenton/oxalic acid, the degradation of pollutants was enhanced. Similarly, Serna-Galvis et
al
.
[95] with the same ultrasound treatment parameters, observed an increase in the concentration of
certain pollutants (Ciprofloxacin, Norfloxacin and Carbamazepine) after applying ultrasound for 90
minutes. The combination of ultrasound treatment with Fe2+ and UVC light further increased
pharmaceutical removal, leading to an average removal of the pollutants around 85%, with some of them
reaching the total removal.
Chandak et
al
. [96] investigated the removal of pharmaceuticals from wastewater and studied the
variation of COD removal across various processes. The study found that while ultrasound treatment
alone (250 W and 22 kHz) achieved a COD removal of 14%, when combined with processes like hydrogen
peroxide or ozone, the removal rate more than doubled (36%). The maximum COD removal percentage
(92%) was achieved by combining ultrasound with ozone and copper oxide, highlighting the significance
of an oxidizing process for process enhancement.
Finally, Vásquez-López et
al
. [34] focused solely on the effect of ultrasound treatment (26 kHz and
1333.3 W/L) on wastewater without combining it with other processes. After 30 minutes of application,
22
Developing an Ultrasound-based Water Treatment System
the study found significant removal rates: TOC removal at 68.7%, COD at 39.9%, BOD5 at 39.5%, TN at
50%, NH3-N at 67.8%, TP at 37.3%, and PO4-P at 42.5%. Notably, there were negligible variations in pH,
a decrease in conductivity, and only a minor reduction in dissolved oxygen (0.8 mg/L).
The findings derived from the referenced literature indicate that acoustic cavitation enhances pollutant
removal when combined with other Advanced Oxidation Processes (AOPs). A comparative analysis of the
results obtained by Vásquez-López et
al
. [34] with those of Serna-Galvis et
al
. [94] and Serna-Galvis et
al
.
[95] reveals a notable disparity in power intensity. Specifically, the power intensity in the former case is
approximately 15 times higher than in the latter studies. Since that the acoustic cavitation is more intense,
it leads to superior removal rates once that the cavitation is more intense.
While the results underscore the potential of acoustic cavitation as a valuable tool for wastewater
treatment and pollutant removal, it is noteworthy that the ultrasound treatment parameters employed by
Vásquez-López et
al
. [34] may pose scalability challenges. The parameters necessitate a substantial
amount of energy, coupled with large transducers, or alternatively, result in a low quantity of treated water
flow. A comparative examination of this study with the research conducted by Chandak et
al
. [96] reveals
that ultrasound treatment, when combined with other AOPs, achieves high COD removal while utilizing
less power. This combination leverages the advantages of both processes, offering a more sustainable
and efficient approach to wastewater treatment.
2.3 Effects of Cavitation on Wastewater treatment
Cavitation encompasses the intriguing physical phenomenon wherein bubbles or voids are formed within
a liquid due to exposure to significant negative pressure conditions. The size of these bubbles can range
from nanometres to substantial centimetres. Cavitation can be induced through two primary methods, by
generating considerable tension within a liquid or by introducing an amount of energy locally within the
liquid. In this context, this study will lies on the former method, specifically acoustic cavitation and the
effects of cavitation in liquids [97].
Cavitation can be associated with either liquid flow or acoustic conditions. When there is a rapid
pressure fluctuation within a hydraulic system, the liquid’s pressure drops until it reaches its vapour
pressure, leading to the creation of bubbles. Subsequently, upon pressure restoration, the liquid swiftly
moves away from the low-pressure zone, causing the bubbles to collapse. This collapse generates shock
waves and elevates the surrounding liquid’s temperature [98]. It is worth noting that cavitation becomes
evident once the pressure falls below a certain threshold, signifying a loss of liquid cohesion [99].
23
Developing an Ultrasound-based Water Treatment System
The relationship between vapour pressure and cavitation finds elucidation through a phase diagram,
Figure 2.5. This diagram expounds on the behaviour of water under specific temperature and pressure
conditions. It becomes evident that by elevating the temperature of water (while maintaining constant
pressure), the transition to the vapour state becomes attainable. Conversely, reducing the pressure, as
observed in cavitation, pushes water below this delineated line, leading it into the vapour domain [100].
Figure 2.5: Water phase diagram. The passage from liquid to vapour can occur by decreasing the pressure
like seen in cavitation (1-2) or increasing the temperature (1-3). Image adapted from Franc et
al
. [99].
Acoustic cavitation hinges on the emission of high-frequency sound waves through the liquid medium
[101]. These waves are generated by ultrasound devices that acts on the liquid, leading to alternating
compressive and tensile phases, fostering bubble formation and expansion [102]. The cavitation event
itself occurs during the tensile or rarefaction phase, characterized by a negative pressure environment.
Within this phase, the negative pressure surpasses a critical threshold, leading to the separation of liquid
molecules. This occurs as the distance between adjacent molecules exceeds a critical value. This critical
point, termed the ”threshold,” signifies the juncture at which the molecule distance becomes sufficiently
extensive to induce bubble formation [13, 48, 101].
These bubbles emerge when the liquid’s pressure declines to a level that encourages vaporization,
known as the rarefaction phase. This phase leads to the creation of minuscule gas-filled pockets, often
referred to as bubble nuclei [102]. Bubble nuclei can either grow if mechanisms support their expansion or
dissolve if no sustaining process is present. These bubbles undergo oscillations in size due to the cyclical
shifts between rarefaction and compression phases. As illustrated in Figure 2.6, bubble size experiences
24
Developing an Ultrasound-based Water Treatment System
continuous enlargement due to the gas’s compressibility within [103].
Bubble or nuclei growth, is propelled by two primary processes: rectified diffusion and bubble
coalescence. Research conducted by Ashokkumar [103] has explored bubble growth behaviour in
diverse mediums. In solutions featuring active solutes, which will be further discussed in the context of
wastewater, bubble growth is predominantly constrained to rectified diffusion. The presence of
surface-active solutes retards bubble coalescence, amplifying the importance of rectified diffusion.
However, it is important to note that water exhibits both processes simultaneously. Bubble coalescence
pertains to the fusion of two or more bubbles into one. When bubbles amalgamate, their boundaries
collapse, forming a fresh, larger boundary encompassing the merged bubble [103, 104]. This
phenomenon is inherently connected to rectified diffusion, which signifies the migration of molecules in
one direction due to external driving forces or gradients. Refer to Figure 2.6 for a visual representation of
this process. After the initial appearance of nuclei, if multiple mechanisms exist, coalescence unites
certain bubbles, leading to their growth. This coalescence process combines with rectified diffusion,
accelerating bubble expansion. Once a bubble reaches its resonance size, it collapses and fragments
into the liquid, seeding new nuclei that initiate the next cycle.
Figure 2.6: Process of bubble formation and growth in cavitation. Bubble nuclei form, grow, and reach a
critical size, causing implosion and fragmentation. This cycle recurs. Image adapted from Ashokkumar et
al
. [103].
Diffusion takes the main paper in presence of some solute, which makes it the most interesting process
to be studied. The rectified diffusion is connected to the gas inside the bubble. This last one, during the
compression phase, has a pressure higher than at equilibrium and, consequently, gas diffuses out of the
bubble. Amid the expansion phase, the gas diffuses inside the bubble. However, comparing the surface
area of the bubble in compression and expansion, the expansion phase has a large area [105].
25
Developing an Ultrasound-based Water Treatment System
Therefore, the gas inside the bubble will increase because the amount of input or output flux is
proportional to the surface area (exchange area). Another consequence of these size changes will be the
increase of diffusion effect during the compression, as seen in Figure 2.7. In compression, the liquid
shell will be more concentrated, which means that the diffusion is higher. In the expensive phase, the
concentration is lower, thus, the diffusion will be reduced [106]. The rectified diffusion is the cause of the
bubble growth along the cycles. This growth will be continuous until the bubble reaches its resonance
size when the bubble oscillating frequency is in the same range as the driving ultrasound frequency. At
this point the pressure is high, assisted by the compressive stress and the effect of surface tension, and
the bubble will be forced to shrink or collapse. This process is approximately adiabatic, so it reaches a
very high temperature in the compression phase [102, 104, 107].
The liquid will heat over the ultrasonic wave propagation through the liquid that will be scattering and
attenuated. Liquid convection is a consequence of the two previously mentioned, micro-streaming and
acoustic streaming. Micro-streaming is the consequence of the expansion and shrinking of the gas bubbles
during the cavitation. When a bubble is vibrating, there are currants around it, generating the flow known
as micro-streaming. Acoustic cavitation provokes convection once the wave sound propagation along the
liquid causes the liquid to flow in the direction of the sound propagation. The propagated ultrasound
pressure causes radiation forces, standing waves and acoustic streaming [108].
Figure 2.7: Impact of the Pressure Variation on the Formation and Growing of Bubbles. The constant
compression and rarefaction lead to nucleation, growth by rectified diffusion, ending with the implosion of
the bubble. Image adapted from Mason et
al
. [105].
Cavitation initiation occurs only when the surface tension of the liquid is overcome. As previously
mentioned, the critical pressure, or cavitation threshold, is determined by the following equation:
26
Developing an Ultrasound-based Water Treatment System
Pcrit =Pυ−2·γ
R(2.3)
Where R (m) is the bubble size, Pυ(Pa) is the vapour pressure of the liquid and γ(N/m) the surface
tension [11].
Cavitation can be categorized into transient or stable [102]. Both occur at low ultrasound intensities,
but transient cavitation exists for a limited number of cycles and is particularly efficient for inducing
chemical reactions [109]. In contrast, stable cavitation transpires when bubbles oscillate consistently
across many cycles, leading to micro-streaming within the surrounding liquid. These microbubbles,
comprised solely of gas, such as air, exhibit a longer lifespan than one ultrasound cycle. As frequency
increases, the bubbles are propelled toward the pressure antinode, sparking certain chemical reactions
[110].
Bubble remnants are not entirely dissolved into the surrounding fluid, and the remaining gas from
implosion ascends to the liquid interface. This process serves as a method for degassing the liquid. This
phenomenon is observed in cavitation bubbles with modest dimensions, which induce robust flow (micro-
streaming). Furthermore, if the bubbles don’t reach resonance size, they will grow through the diffusion of
gas molecules from the surrounding liquid, ultimately achieving a stable equilibrium size. This indicates
the establishment of stable cavitation, commonly exploited in medical applications like ultrasound imaging
and drug delivery [102].
On the contrary, transient cavitation entails bubbles filled with gas undergoing erratic oscillations and
ultimately imploding. The duration of this phenomenon is shorter compared to stable cavitation. The cavity
is rapidly formed and collapses energetically after just a few cycles, resulting in elevated local temperatures,
pressures, and shear forces that can disintegrate biological cells or other organic materials present [102].
Within the context of cavitation, the collapse of bubbles can be delineated into three distinct phases,
as illustrated in Figure 2.8 [7, 111]. The initial phase, centred at the thermolytic core, experiences extreme
conditions with temperatures ranging from 4000 to 5000 K and pressures reaching approximately 500
atm. Remarkably, despite the elevated temperatures, this overheating stage persists for less than 10 µs
[112]. During this phase, water molecules inside the bubble undergo pyrolysis, yielding HO.and H.
radicals.
The subsequent phase occurs at the interface between the cavitation bubble and the surrounding
liquid. In this region, analogous chemical reactions take place, alongside processes such as the
dimerization of HO.to form H2O2. The primary mechanism involves the attack of free radicals
emanating from the implosion of cavitation bubbles [7].
27
Developing an Ultrasound-based Water Treatment System
The final phase encompasses the bulk region, where the increase in temperature is inferior due to
the adiabatic nature of cavitation reactions. Within this bulk region, the radical attack on pollutants is
anticipated to occur under the influence of H2O2. As depicted in Figure 2.8, these three phases exhibit
distinct temperature and pressure conditions. The outermost bulk region experiences minimal impact, with
the middle phase seeing a temperature rise to around 2000 K and negligible pressure changes. However,
in the central region, known as the hotspot zone, temperatures and pressures reach remarkable values
[109, 113].
As consequence, the chemical effects of cavitation manifest on the previous distinct regions, Figure
2.8. In the hot gas phase within the bubble, solvent or volatile compound sonolysis occurs, resulting
in the formation of radicals. The high pressure and temperature in this phase lead to sonolysis of non-
volatile compounds and subsequent heating of the liquid. At the liquid shell around the bubble, gradients
in pressure, temperature, and the presence of an electrical field result from the sonolysis of non-volatile
compounds. The chemical reactions observed are a consequence of the radicals originating from the
interior of the bubble. In the surrounding liquid medium, the reactions occur as a consequence of the
radical reactions expelled from the interior of the bubble. These processes encompass emulsion formation,
mixing of bubble gas and liquid, mechanical effects on solids and metals, heat transfer and fluid flow [106].
Figure 2.8: Hotspot, gas-liquid interface and bulk solution regions and their characteristics during bubble
implosion. Image adapted from Carpenter et
al
. [111].
In the realm of cavitation, where bubbles collapse in three distinct phases, as depicted in Figure
2.8 [7, 111], it is essential to consider the dramatic contrast between initial and final bubble conditions.
Starting with an initial radius of approximately 1 µm, the internal pressure at 1 atm, a temperature of 20
28
Developing an Ultrasound-based Water Treatment System
°C, and an energy density of around 106eV /µm3, these parameters can exhibit some variability under
specific conditions. As the bubble collapses, its radius can range from 3 µm to 0.4 mm, the internal
pressure can rise to 2500 atm, the internal temperature can peak at 6000 K, and the energy density can
reach 2.8×108eV /µm3[114].
These elevated temperature conditions exert a considerable influence on the overall solution
temperature. In a study by [115], the kinetic isotope effect was investigated, revealing a temperature
range of 1000-4600 K. This range is attributed to specific regions within the cavitation hotspot.
Furthermore, in a separate experiment involving multibubble sonochemistry and sonoluminescence, the
same author proposed an extended temperature range of 750-6000 K [115].
The temperature-dependent radical production, influenced by frequency, is a critical factor in the
chemical effects of cavitation. Radicals are generated during the collapse of the bubble from the solvent
vapour or volatile compounds in the liquid. This initial radical acts as a catalyst, initiating a chain reaction
of radical formation, ultimately leading to reactions with substrates or other radicals [106]. The reaction
rate is slow, ranging from 10−4to 10−5mol/(L ·min), and is not influenced by the ultrasound.
2.3.1 Variables Affecting Sonochemical Reactions
The implosion of bubbles, accompanied by intricate chemical and physical processes, underscores the
significance of sonochemistry. This term succinctly encapsulates its essence: the study of chemistry in
the presence of sound, specifically ultrasound waves. Sonochemistry employs high-frequency and
high-power sound waves to infuse energy into a liquid reaction mixture, leading to both physical and
chemical transformations within the liquid [109]. This field finds applications in diverse areas, including
food processing, oil emulsion stabilization, particle size reduction, filtration systems for suspended
particles, homogenization, atomization, and environmental protection [109].
As refereed before, when bubbles collapse during cavitation, they release a substantial amount of heat,
reaching temperatures as high as 5000 °C, and generate extreme pressure conditions, often exceeding
1000 bar [109]. This phenomenon is known as the ”Hot-spot theory,” emphasizing the localized and
drastic conditions created by bubble collapse.
At a frequency of 20kHz, transient bubbles form, with their maximum radius ranging from 10 to 50 µm,
dependent on the acoustic pressure amplitude. Importantly, cavitation collapse is frequency-dependent,
with bubble size decreasing as frequency increases [106, 109].
As bubbles collapse to their maximum radius, their shell velocity approaches the speed of sound.
When bubble size reaches the sub-micron range, the gas inside the bubble decelerates the wall motion,
29
Developing an Ultrasound-based Water Treatment System
giving rise to the generation of awe-inspiring shock waves [106].
The collapse of bubbles also significantly influences the flow of liquid in aqueous environments. In
cases where bubbles do not collapse uniformly, they generate liquid jets, causing liquid to rush into the
bubble. This phenomenon becomes particularly pronounced at boundary areas where a liquid interfaces
with a solid surface. Finding a perfectly spherical bubble with homogeneous collapse in practice proves
to be a challenging endeavour [106].
To neutralize microorganisms, several mechanisms come into play, all stemming from acoustic
cavitation in the aqueous medium. First, the collapse of bubbles generates shock waves and vortices,
creating shear stress within the liquid bulk, which exceeds the shear rate throughout the liquid [13, 112].
Secondly, the physical and chemical consequences of bubble collapse, such as high temperature and
pressure increases, result in changes to microorganisms. These changes are further influenced by the
presence of hydroxyl radicals, which are formed as a consequence of the hot-spot hypothesis. During
bubble collapse, free radicals are generated [13, 112].
The action of ultrasound leads to the disintegration of water molecules, forming hydroxyl radicals:
H2O→HO +H(2.4)
These hydroxyl radicals, HO., interact directly in the gaseous phase or at the liquid/gas interface.
Their reaction with oxygen results in the formation of hydrogen peroxide [116]:
H2O+H.→HO.+H2(2.5)
O2+H.→HO.
2(2.6)
2HO.→H2O2(2.7)
HO.+H2O2→H2O2+HO.
2(2.8)
These chemical reactions lead to the formation of hydrogen peroxide, which further affects
microorganisms:
H2O2→2HO.(2.9)
HO.+HO.
2→H2O+O2(2.10)
H2O2+H.→H2O+HO.(2.11)
30
Developing an Ultrasound-based Water Treatment System
These intriguing chemical reactions culminate in the formation of hydrogen peroxide, exerting further
influence on microorganisms. The radicals mentioned above infiltrate the chemical structure of bacterial
cell walls, ultimately leading to their degradation. Furthermore, the physical, chemical, and mechanical
effects discussed earlier also contribute to the disruption of bacterial cells and the de-agglomeration of
clusters. The neutralization of microorganisms is driven by cell dilution and the growth of free radicals.
One of the mechanisms responsible for cell neutralization is the physical disruption of the cell over time, a
result of mechanical fatigue. Additionally, micro-stray shear forces, chemical attacks by free radicals, and
the impact of bubble collapse near the cell wall all contribute to this process Moreover, hydroxyl radicals play
a crucial role in the oxidation of pollutants. High rates of successful recombination of hydroxyl radicals
lead to high rates of oxidation, making this process dependent on the cavitation process and chamber
design [112].
These intricate processes within sonochemistry, from the generation of shockwaves and vortices
during bubble collapse to the formation of hydroxyl radicals, culminate in the remarkable disruption and
neutralization of microorganisms. This orchestration of physical, chemical, and mechanical effects,
illustrated in Figure 2.9, demonstrates the profound potential of sonochemistry in applications such as
wastewater treatment and environmental protection, where the targeted dismantling of cells plays a
pivotal role 2.9.
Figure 2.9: Sequence of Cellular Degradation by Cavitation. It begins with gas cavity formation due to
increased water vapour. The ensuing collapse releases destructive radicals, leading to cellular destruction,
augmented by mechanical stress from implosion. Image adapted from Fetyan et
al
. [97].
Numerous factors can influence cavitation and, consequently, the outcomes of sonochemical
reactions. These factors include acoustic power, frequency, hydrostatic pressure, the nature and
temperature of the solvent, the gas used, and the reactor’s geometry [48].
Acoustic intensity, as indicated in Equation 2.12, varies with power input or the transmittance
31
Developing an Ultrasound-based Water Treatment System
area of the ultrasonic transducer. Higher intensities result in increased hydroxyl radical concentration and
enhanced mass transfer, leading to greater degradation of organic substances [117].
However, this phenomena it is limited to a maximum power. Beyond a certain power threshold, bubble
radius tends to stabilize, limiting degradation [48]. This behaviour holds for various types of pollutants,
including hydrophilic [118], hydrophobic [119], and volatile compounds [120].
Ia=Ps
A(2.12)
Where Iais the acoustic intensity (W/m2), Psis the input power (W) and A is the transmittance area
(m2) of the ultrasound.
The behaviour of cavitation collapse hinges on the applied frequency, dictating bubble size and the
maximum collapse temperature. Lower frequencies yield a modest temperature rise, akin to an isothermal
collapse scenario. Conversely, elevating the frequency reduces bubble size, resulting in shorter collapse
durations. Typically, the highest collapse temperature is observed around 300 kHz, signifying a shift
towards nearly adiabatic collapse [106].
Research by Al-Bsoul [121] demonstrated the greater effectiveness of lower-frequency ultrasound (20
kHz) compared to higher frequencies (40 kHz) in wastewater treatment, achieving a COD removal of 30%
versus 14%, respectively. Lower frequencies may be more efficient for wastewater treatment applications.
Higher frequencies, between 200-350 kHz, lead to increased radical formation and greater hydrogen
peroxide accumulation [122]. Highly hydrophobic or volatile substances require higher frequencies for
efficient degradation [48].
In relation to frequency, ultrasound irradiation can be administered through two methods: continuous
or pulsed. The continuous method is the most commonly employed due to its process simplicity. However,
certain studies have reported that the pulsed technique exhibits greater efficacy in eliminating pollutants.
Xiao et
al
. [123] and Xiao et
al
. [124] shows that using pulses, instead of continuous irradiation, allows to
accumulate hydrophobic pollutants in the bubble interface, inducing higher levels of molecule degradation
upon collapse.
Temperature significantly influences sonochemical reactions by altering fluid properties. Increasing
temperature decreases viscosity and surface tension while increasing vapour pressure, reducing violent
collapses due to increased vapour inside bubbles. The solvent’s boiling point is another critical factor;
solvents further from their boiling points generate more cavitation bubbles, but these dampen bubble
collapses and hinder sonochemical effects [106].
Cavitation is more pronounced at lower temperatures, where high temperatures disrupt solute-matrix
32
Developing an Ultrasound-based Water Treatment System
interactions (hydrogen bonding, dipole interactions, and Van der Waal forces), resulting in faster diffusion
rates and less violent collapses [109].
The smaller the thermal conductivity of the gas inside the bubble, the higher the maximum collapse
temperature [106].
Generally, lower temperatures (25°C to 30°C) favour cavitation [10]. For applications emphasizing
thermal effects, lower temperatures are advisable [125].
For an ultrasound intensity of 20 kHz, increasing temperature reduces pollutant degradation [126].
Studies on 2,4-Dichlorophenol, 4-Chlorophenol, Dextran, and Diazinon confirmed that higher
temperatures lead to reduced degradation [126–129]. Lower initial temperatures (20°C) are more
effective for decolorization compared to higher temperatures (30°C and 40°C) [18].
K. Brabec et
al
. [130] research indicated an inverse relationship between cavitation threshold and
temperature; as temperature increases, cavitation threshold decreases. Additionally, the cavitation
threshold tends to increase with higher viscosity.
While it is acknowledged that parameters such as pH and initial solvent concentration can exert
influence on sonochemical behaviour, it is important to note that these factors will not be the focus of
this study.
2.3.2 Ultrasound Components and Functioning
Before defining ultrasound is important to specify what is sound. Sound is a form of energy that is produced
in consequence of disturbs or vibrations in a medium (air, water, solids), and may come from vibrating
bodies, airflow changing, heat sources or supersonic flow. It is a mechanical energy transmitted in gas,
liquid or solid form by pressurized waves [97]. These vibrations cause pressure waves that will propagate
through the medium, generating series of compression and rarefaction. Waves have some interesting
particularities that will impact the way how sound will be propagated. A wave can transport energy and
information through a medium, without transport the medium itself [110, 131].
Ultrasonic waves belonging to the range between 20 kHz and 200 MHz. Above it, the ultrasonic
frequencies are not able to produce acoustic cavitation. In normal conditions, the maximum listened
sound range for humans, is from 16 kHz to 18 kHz. The ultrasound frequencies are considered from
20 kHz and dependent of the application can go to 2MHz. The conventional ultrasound frequencies for
industrial applications are from 20 kHz to 100 kHz and are considered as low ultrasound frequencies.
To sonochemistry, are used frequencies in the 100 kHz-2 MHz range and since 5 MHz to 10 MHz, it
is nominated as low power high frequency ultrasound and it is used for medicals diagnostic purposes
33
Developing an Ultrasound-based Water Treatment System
[48, 106]. The intensities higher than 10GHz are mentioned as hyper sound. In Figure 2.10 can be seen
the sound range along all frequencies.
Figure 2.10: Sound range along the spectrum and the position of the different types of ultrasound, low
frequency ultrasound, high frequency ultrasound and ultrasonic spectrum used in medical diagnosis.
Image adapted from Fetyan et
al
. [97].
A sound wave, under ideal conditions, can be described as a sinusoidal plane wave characterized
by several key parameters, including frequency, period, wavelength, and amplitude [131, 132]. These
parameters help to understand the fundamental properties of sound waves. Frequency (f) in Hz, represents
the number of cycles a wave completes per second and is the inverse of the period (T) in seconds, which
is the time required to complete one cycle.
f=1
T(2.13)
The amplitude characterizes the variation in pressure over time. It can be mathematically represented
as:
A(t) = Amax ·sin(2πt +ω)(2.14)
Here, Amax represents the maximum amplitude (µm), t represents time (s), and ωis the angular
velocity (rad/s).
The propagation of sound waves is influenced by the distance they must travel through a medium, and
two main factors come into play: scattering and absorption. Scattering refers to sound waves reflecting in
various directions from their original path, while absorption involves the conversion of sound energy into
other forms of energy [109]. Attenuation, which measures the reduction in ultrasonic intensity, help to
understand the factors that decrease ultrasonic intensity as sound travels through a medium.
Pure water, without any other substance, possesses an attenuation coefficient of 2·10−7cm−1,
indicating that over a 1 km distance, the attenuation is only 2%. This low coefficient makes water an
34
Developing an Ultrasound-based Water Treatment System
excellent medium for transmitting acoustic signals over long distances. For instance, at 20 kHz, the
typical length is 7.4 cm. Considering the Rayleigh scattering cross-section of wastewater particles, their
presence has negligible effects on ultrasound attenuation in wastewater [11, 133].
Air bubbles in water create interfaces between air and water, making them highly reflective to
ultrasound due to the substantial difference in acoustic impedance between these media. Bubbles
reflect ultrasound waves effectively because this impedance difference spans approximately four orders
of magnitude. However, bubbles can also attenuate sound transmission, especially in situations involving
dense bubble clouds or resonance with the ultrasound frequency [11].
Ultrasound waves are introduced into the liquid medium either via direct contact with the ultrasonic
source (direct sonication) or by immersing a vessel containing the solution to be treated (indirect
sonication). Indirect sonication consists of a piece that includes a transducer coupled with a vibrating
plate for the bath method [134].
The horn system is constituted by an ultrasonic electrical generator, an electro
mechanical/piezoelectric transducer, an wave guide, an ultrasonic horn or acoustic radiator, a mounting
flange, a reactor chamber and a working liquid inlet and outlet, Figure 2.11. In some cases, there are
other components such a cooling system with their respective pipes [135].
Figure 2.11: Typical configuration of an ultrasound device for water treatment application. (a) The
ultrasound tip consist of a horn emitting waves perpendicular to the ultrasound axis. Alternatively, it
may involve a waveguide and an acoustic radiator. Image adapted from Marin-Hernandez et
al
. [136].
35
Developing an Ultrasound-based Water Treatment System
Transducer or converter is the part responsible to convert the electrical energy into mechanical energy,
vibration. The ultrasound basis is a source of high-energy vibrations. In practice, the source is one
transducer that is capable of convert electrical energy into mechanical energy in the form of ultrasonic
vibrations. There are three classic types of transducers, gas driven, liquid driven and, the most efficient,
the electro mechanical. However, to high power vibrations, are considered two types: piezoelectric and
magneto strictive [48, 136].
In this work will be focus on the use of piezoelectric transducers. Piezoelectric materials can respond
in two different ways according to the stimulus applied. If there is a mechanical load, the material responds
producing an electrical potential. However, if there is an electrical potential applied across faces there is
the inverse piezoelectric effect [109, 137].
The transducer construction is normally made by the assembly of layers with blocks or discs of
aluminium and with electrically active piezoelectric elements. This particular configuration can be
thought of as a mechanical transformer and behaves similar to a bell when excited by a driving
piezoelectric element at its resonant frequency. When appropriately stimulated, the system resonates
and produces a characteristic ”ringing” sound due to the transfer of mechanical energy between
different parts of the configuration [137]. A screw or pin compress the two blocks of metal (superior and
inferior layers) again the piezoelectric ceramic plates. This configuration it will be responsible for the
introduction of a force into the piezoelectric ceramics [138].
When an external force is applied, the electric dipoles within the crystal align, creating a positive
and negative face, resulting in an electric field across the crystal. This phenomenon occurs in a poled
piezoelectric material, where subjecting it to tensile or compressive stress generates positive or negative
voltage across its faces, respectively [139].
This crystal then converts electrical energy into mechanical vibration, producing sound through
alternated potential at high frequencies. When the alternating potential reaches a sufficiently high
frequency, it generates high-frequency sound waves, commonly known as ultrasound [109]. Essentially,
a zirconium titanate piezoelectric transducer converts electrical pulses with periodic intervals into
ultrasound pulses [133]. In this process, the application of an external voltage to a poled piezoelectric
material causes the material to either extend or compress, depending on whether the voltage is positive
or negative [139].
To achieve high-amplitude oscillations, certain physical properties of the ceramic material must be
taken into account. Three key properties play a crucial role in ensuring the effective functioning of the
piezoelectric ceramic. Firstly, a high Curie temperature, which is the temperature at which certain
36
Developing an Ultrasound-based Water Treatment System
materials transition from a ferromagnetic or ferroelectric state to a paramagnetic or paraelectric state
[138]. Secondly, a low dissipation factor is essential to prevent overheating and prolong the ceramic’s
lifespan. Lastly, a high ”d” constant, which signifies a high ratio of mechanical strain produced by an
applied electromagnetic field [137]. In essence, a high d ratio implies that a small mechanical
deformation in the material will result in a large electrical signal, and vice versa, enhancing the
conversion of energy between electrical and mechanical domains.
The distinction between the direct and indirect piezoelectric effects lies in the direction of the electrical
impulse as seen in Figure 2.12. When a mechanical impact occurs, the crystals generate a potential
difference that can be read by a device. Conversely, the opposite effect results in the generation of
ultrasound waves [138]. The former principle is employed in applications like acoustic and pressure
sensors [140, 141]. The latter principle underlies the emission of ultrasonic waves [142].
Figure 2.12: Piezoeletric disk response with two different exciting possibilities. Mechanical force
yields voltage (direct effect for sensors); applied voltage induces dimensional change (indirect effect for
transducers). Image adapted from Sikalidis et
al
. [139].
Guided waves are a category of waves that propagate along a defined path within a medium or
structure, as opposed to radiating outward in all directions like free or unguided waves. Their propagation
is confined by the geometry and boundaries of the medium itself, resulting in distinct characteristics.
Ultrasonic guided waves serve as an exemplary instance of guided wave propagation and exhibit typical
attributes [143].
One key feature of guided waves is their constrained path, determined by the medium’s geometry.
This confinement leads to reduced dispersion when compared to free waves over long travel distances.
However, guided waves are not entirely immune to dispersion. Different frequencies within the wave can
travel at varying velocities, which can result in mode separation and frequency-dependent behaviour [143].
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Developing an Ultrasound-based Water Treatment System
In the context of wastewater treatment, the primary objective of utilizing waveguides is to channel
ultrasonic waves along the z-axis towards the target structure, such as the acoustic radiator [144]. However,
as the waveguide it is in contact with the fluid, it will works as a acoustic radiator too in certain point. These
waveguides can take different forms: they can be either solid or perforated with holes.
Solid waveguides are characterized by their rigidity and inability to displace along the z-axis. They
provide a stable and predictable path for the ultrasonic waves. However, they may involve some losses and
dispersion during wave propagation. On the other hand, perforated waveguides feature holes that permit
movement along both the negative and positive axes of the z-axis. The presence of these perforations offers
advantages such as reduced losses and dispersion during wave propagation. Additionally, perforated
waveguides enable the transmission of non-continuous waves, which can be particularly beneficial in
various wastewater treatment applications.
Waveguides play a critical role in ensuring efficient and controlled delivery of ultrasound waves to target
structures within wastewater treatment systems. They serve as conduits for these guided waves, allowing
for precise energy deposition and effective treatment of contaminants. Understanding the properties and
advantages of different waveguide designs is essential for optimizing the performance of ultrasound-based
wastewater treatment processes.
The booster serves to amplify the amplitude generated by the preceding component, while the horn
transmits mechanical energy in the form of ultrasonic waves into the aqueous medium. Both components
are meticulously engineered to operate at specific frequencies, often designed to be half a wavelength in
length, although alternative configurations, such as full-wavelength designs, are feasible and contingent
upon the intended application [145].
In certain applications, the booster has the capability to alter the wavelength. However, in the context
we are investigating in this study, it functions primarily as a waveguide, preserving the original wave
characteristics. In this role, it acts as an integral structural element. Conversely, the booster plays a
pivotal role in the structural integrity of the ultrasound system, as it facilitates the connection between
the internal waveguide and the flange. Its responsibility is to ensure a secure and reliable linkage
between these two crucial components.
The acoustic radiator is affixed to the waveguide with the sole purpose of extracting waves from
the waveguide and transmitting them into the surrounding water. This component serves as the interface
between the ultrasound system and the solution being studied, typically taking the form of a solid cylindrical
object.
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Developing an Ultrasound-based Water Treatment System
2.3.3 Acoustic Cavitation Characterization
The study of acoustic cavitation involves investigating its inherent consequences. Sutkar et
al
. [125],
in their research, categorize the different types of effects that can be observed with acoustic cavitation.
Understanding these effects enables the measurement of cavitation by assessing its resultant impacts.
The quantification of primary effects involves measuring parameters such as pressure, temperature, and
bubble activity.
In addition to the aforementioned classification, the various methods for detecting cavitation can also
be differentiated based on their physical and chemical characteristics. Verhaagen et
al
. [146] categorized
cavitation detection into basic tests, acoustic methods, optimal techniques [147, 148], chemical [149–151]
and physical approaches [152].
The measurement of cavitation using acoustic methods involves monitoring the sub-harmonic
frequency, a technique reliant on observing oscillations at these frequencies, rooted in understanding the
dynamic behaviour of gas bubbles within a liquid subjected to the alternating pressure from an acoustic
field. The motion exhibited by these bubbles closely resembles oscillations at certain frequencies (f),
satisfying the following mathematical relation:
x·f=y·f0(2.15)
where f0is the sound field frequency and n, m integers [153].
In the context of ultrasound application, energy transitions from the acoustical mode at frequency f0
to an acoustical mode at frequency f. When investigating cavitation, the most crucial scenario occurs
when m=1 and n=2. This configuration is particularly significant because it enables the straightforward
detection and differentiation of the sub-harmonic signal from the fundamental frequency of the sound field,
as detailed by Santis et
al.
[153].
Numerous investigations have focused on employing sub-harmonic frequency to study cavitation. The
key findings emphasize that the sub-harmonic frequency can serve as an exceptionally sensitive and rapid
method for detecting the onset of cavitation. Indeed, piezoelectric detectors only register a significant
increase in sub-harmonic oscillation amplitude at the initial stages of acoustic cavitation. This phenomenon
can be attributed to the presence of numerous pulsating bubbles within the liquid medium. Additionally,
the amplitude of the acoustic field diminishes due to heightened absorption by the cavitation liquid and
the subsequent transfer of power to the sub-harmonic mode, as proposed by Edmonds et
al
. [154].
In their research, Puga et
al
. [155] employed an acoustic detection system that marries a
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Developing an Ultrasound-based Water Treatment System
piezoelectric detector with a molybdenum rod submerged within an aluminum-filled chamber. This
approach to cavitation detection closely aligns with their intended methodology.
Apart from focusing on sub-harmonic detection, their article also delves into the study of
ultra-harmonics to gain a clearer understanding of acoustic cavitation. The stabilization of
ultra-harmonics, combined with an elevation in the first sub-harmonic, significantly enhances the
precision of cavitation detection.
Similarly, and using a different approach, Brabec et
al
. [130] developed an acoustic measurement
system that combines a piezoelectric sensor with an echocontrast agent, specifically a 5% solution of
lyophilized egg albumin. This approach enhances the ultrasound field and, consequently, improves
cavitation detection.
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Developing an Ultrasound-based Water Treatment System
3. Development of a Sensor for Characterization of Acoustic
Activity
This chapter aims to develop a system proficient in characterizing acoustic cavitation, with the ultimate
goal of integrating a sensorization system into the existing equipment. Additionally, this chapter provides
a comprehensive exposition of the equipment, elucidates the sensor requirements, explores available
options, and outlines the methodology for their calibration and testing.
3.1 Equipment Design and Integration
The analysis of the equipment will consider as the ultrasound setup is composed of two primary component
groups, each serving distinct functions. One group is dedicated to the generation and propagation of
ultrasound, while the other is responsible for containing the wastewater within the chamber and at the
same time responsible for the structural stability. The chamber itself possesses a total volume of 20 L,
along with an interior diameter measuring 100 mm. Notably, the chamber is equipped with two separate
inlets. The larger diameter inlets, regulated by spherical valves, facilitate the intake and outflow of water,
boasting an inside diameter of 30 mm. A noteworthy feature of this chamber is its water-cooling capability,
a characteristic that sets it apart.
In parallel, the smaller diameter inlets are instrumental in connecting water for cooling purposes,
indirectly contributing to the temperature regulation of the liquid within.
Extending from the chamber, a supporting structure provides essential stability to the entirety of the
ultrasound equipment. This structural framework is reinforced by a beam that establishes secure
connections with the chamber at two key points, ultimately extending to an elevated base.
The base, equipped with four rubber feet, is designed to effectively dampen vibrations. To enhance
its mechanical resilience, the lower section of the structure incorporates three sturdy ribs.
For a visual representation of all the exterior components and structural features, refer to Figure 3.1.
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Developing an Ultrasound-based Water Treatment System
Figure 3.1: Equipment main components with focus on the exterior section and structural parts.
The counterpart of the equipment handles ultrasound generation and propagation, Figure 3.2. The
piezoelectric transducer, responsible for generating ultrasound, is a 20 kHz transducer linked to the power
generator. The first waveguide, positioned externally to the chamber, boasts a 25 mm diameter and
connects the transducer to a 38 mm external diameter booster. A flange situated between the transducer
and booster serves as the top chamber seal. Within the chamber, an internal wave guide, with a length
of 364 mm and a diameter of 50 mm, facilitates the propagation of ultrasound within the water and until
the acoustic radiator. As referenced before, the booster is the structural element that supports the flange
and ultrasonic wave guide.
Additionally, the waveguide is equipped with strategically placed holes to accommodate dimensional
variations along the vertical axis.
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Developing an Ultrasound-based Water Treatment System
Figure 3.2: Part of the equipment responsible for the generation and propagation of the sound waves and
respective parts: Piezoeletric transducer, Waveguide, Flange, Booster and Acoustic Radiator.
The equipment’s functioning is detailed on Figure 3.3. The two spherical valves control the inflow and
outflow of water. Presently, the setup is configured to allow water to enter through the upper valve and
exit from above. However, changing this configuration is a straightforward process; one simply needs to
switch from one valve to the other.
In cases where sediment deposition occurs, it is preferable to have an inlet from the bottom and an
outlet from above. Given that this is an experimental chamber operating in batch mode, this configuration
is essential, as there is no external pressure from above to expel water from the chamber.
There are two other inlets for chamber cooling. These lead to a serpentine arrangement within the
chamber, which promotes convective and conductive heat transfer from the chamber to surrounding liquid.
Figure 3.3: System operation with water inlet and outlet for chamber cooling. The treated water outlet
can be positioned at the (a) bottom valve if contaminants tend to rise to the surface, or at the (b) top if
contaminants tend to settle.
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Developing an Ultrasound-based Water Treatment System
The quest for mechatronic control and sensor integration for reading the acoustic cavitation, required
substantial improvements to the original design. These adaptations were imperative to accommodate
sensorization effectively. Key among these modifications was the creation of an internal construction
enabling the seamless passage of cables and measurement systems from the exterior to the interior.
Acquiring the electrical signal within LabVIEW was a fundamental requirement. Additionally, the
diameter of the system was constrained to be below 15 mm to ensure compatibility with the existing
setup.
Resistance to ultrasound activity was another crucial criterion, mandating the system to acquire at a
minimum frequency of 40 kHz. This stringent requirement was established to enable measurements in
environments where ultrasound activity is prevalent.
The system was also expected to feature non-complex acquisition systems, aligning with the
overarching objective of achieving an economical solution. This called for the integration of streamlined
and cost-effective components.
Additionally, the need for removable and adjustable sensor positioning was crucial for ensuring
adaptability and simplified maintenance. This feature enables the reconfiguration and substitution of
sensors as necessary, thereby facilitating continuous system optimization.
The detailed requirements for sensor development are outlined in Table 3.1.
Table 3.1: Sensor requirements for the design and development of the acoustic sensor reading.
Sensor Requirements
Acquire electrical signal in Lab view Diameter bellow 15 mm
Resistance to ultrasound activity Acquire at minimum of 40 kHz
Non complex acquire systems Economic
Removable Variable sensor position
To meet the specified requirements, two design concepts were developed for integrating sensors into
the ultrasonic chamber.
Option A, originating from the upper inlet, necessitates distinct guides and a complex integration
system. This solution involves two guide tubes for cables, with the second tube also supporting the
sensor. It requires a support with a 90 degree joint to mimic a Morse cone system. However, this approach
introduces challenges such as wire passage through multiple holes, potentially increasing signal noise and
assembly complexity.
In more practical terms, option A involves the use of two separate guide tubes for cables, Figure 3.4.
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Developing an Ultrasound-based Water Treatment System
The second tube serves a dual purpose by also providing support for the sensor. To achieve this, a support
with a 90 degree joint is employed, akin to a Morse cone system. While this solution is viable, it does
introduce some challenges. For instance, the process of threading wires through multiple holes may lead
to increased signal interference and greater complexity during assembly.
Figure 3.4: Design Concept A employs two tubes for wire passage: (a) with a dual entry at the top for
chamber access, and (b) a perpendicular tube for wire passage to the piezoelectric sensors. (c) A detailed
view emphasizes the connection between the tubes, highlighting the wire passage hole and the superior
plate securing the second tube.
Option B involves a singular tube meticulously shaped to conform to the interior chamber design, as
illustrated in Figure 3.5 (a). The tube is seamlessly welded to a flat-faced plug, establishing a connection
with the chamber through the use of a T-connector, featuring inlets for water and sensor wires, as depicted
in Figure 3.5 (b). The wires traverse the interior of the tube and are precisely bent into the desired position,
as shown in Figure 3.5 (c). Once the tube is positioned at the water level within the chamber, there is
no need for additional sealing at this juncture. Consequently, this design offers enhanced flexibility for
adjusting the sensor height.
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Developing an Ultrasound-based Water Treatment System
Figure 3.5: Design Concept B employs a single curved tube for wire passage: (a) entering from the
bottom of the cylinder in a straightforward operation, (b) utilizing a double inlet accessory connected with
a threaded connection, and (c) establishing the wire connection to the piezoelectric sensors via the superior
passage on top of the tube.
Upon careful evaluation of both options, a comprehensive analysis reveals that option B stands out as
the superior choice. Its advantages are manifold, ranging from simplicity of design to cost-effectiveness
and heightened adaptability.
Option B simplifies the construction process by requiring fewer components, contributing to a more
efficient and straightforward system. Additionally, it eliminates the necessity for sealing tube holes,
marking a noteworthy enhancement in terms of both practicality and maintenance.
One of the most significant merits of option B lies in its flexibility in adjusting sensor height. This
attribute empowers the system to achieve acoustic acquisition at any position along the tube, providing a
versatility that is crucial for optimizing data collection.
In stark contrast, option A presents certain complexities, particularly in the integration process. The
requirement for distinct guides and a complex integration system introduces potential points of failure and
complicates the overall assembly.
Furthermore, option A’s reliance on multiple tubes introduces a higher probability of signal noise,
reduced wire resistance, and increased assembly difficulty, thereby presenting notable drawbacks.
Considering these factors collectively, option B emerges as the preferred selection. Its streamlined
design, cost-effectiveness, and heightened adaptability make it the most prudent choice for this application.
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Developing an Ultrasound-based Water Treatment System
With the design option already selected, it is now time to proceed with the implementation. The
tube bending process was meticulously carried out using a manual bending machine, with additional heat
assistance. The dimensions were finely tuned to ensure a precise fit within the chamber. At the bottom, a
T-connection was introduced, featuring dual outputs for both water input and wire passage, firmly secured
through tin welding.
The internal diameter of the tube is 10 mm, designed to accommodate a minimum of three sensors.
The wire diameter allows for a 3 mm gap when three sensors are in use. The tube’s length is designed to
prevent contact with water, eliminating the need for additional sealing, Figure 3.6 (a).
The completed bent tube is showcased in Figure 3.6 (b). Rigorous testing was conducted to identify
any potential leaks, and the results confirmed the integrity of the tube.
The tube conformation process involved a manual bending machine in the Engine Laboratory of the
Mechanical Engineering Department at the University of Minho. The initial attempts led to some marks on
the part, but no leaks were discovered during testing with water and compressed air.
The tube, T-joint, plug, and thread adapter form an integrated assembly. The plug was drilled to
accommodate the tube, and the thread adapter allows for secure attachment. The tube is attached to the
plug through embedding and subsequent welding.
Figure 3.6: Structural component to guide and attach all the wires from the sensor (a) Specifications for
tube dimensions and a technical drawing for manufacturing (b) Wended tube support for the wire passage
to the piezoelectric sensors after manufacturing.
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Developing an Ultrasound-based Water Treatment System
3.2 Piezoelectric Sensor Setup and Data Analysis
In this application, three piezo HS-PC40 from Hangzhou Altrasonic Technology Co. Ltd. elements were
employed. Each piezo disk featured a diameter of 50 mm and a thickness of 2 mm. According to the
data sheet provided by the manufacturer, see Annex I, the piezo disk exhibit a resonance impedance of
10 Ωat 1kHz, a direct capacitance of 11 nF, and an electromechanical coupling coefficient of a minimum
of 40%. The latter, measured with a LCR meter, was not specified by the manufacturer. This parameter
denotes the efficiency of energy conversion within piezoelectric materials, encompassing the conversion
of mechanical into electrical energy as well as vice versa [156].
To ensure compatibility with the chamber and to minimize signal interference during data capture,
the piezo disks were precisely cut into a square shape. This adaptation allowed the piezo to be treated as
having a square shape for analytical purposes. As a result, the electrical charges from the two possible
stress directions can be estimated using the following equations:
V31 =g33 ·F1
4·L(3.1)
Here, g33 represents the electric field generated by applied stress in direction 1, F1denotes the applied
force in direction 1, and L signifies the square length.
V33 =g33 ·F3·t
L2(3.2)
In this equation, g33 represents the electric field generated by applied stress in direction 3, F3is the
applied force in direction 3, L is the square length, and t is the ceramic thickness.
The piezo sensors, belonging to the category of active materials, are distinguished by their ability to
establish a strong correlation between mechanical and electrical quantities. These materials exhibit a
notable mutual coupling, enabling them to efficiently convert mechanical stimuli into electrical signals and
vice versa. Passive materials, on the other hand, constitute the remaining components of the devices
[156]. In Figure 3.7, the axes considered for the previous equation are illustrated.
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Developing an Ultrasound-based Water Treatment System
Figure 3.7: Piezoelectric sensor configuration after polarization. Image adapted from Puga et
al
. [156].
The ceramic piezoelectric elements, initially 50 mm of diameter, were cut into a 25 mm square. This
process wa challenging due to the material’s sensitivity to temperature changes and its inherent brittleness.
The presence of microstructural defects within the material further heightened the need for caution during
the cutting process. To mitigate the risk of fracturing, a cautious approach was adopted. The cutting
was carried out with slow, deliberate movements to minimize stress concentration along the cutting path.
Additionally, a cooling fluid was employed to reduce both the thermal gradient within the material and the
overall temperature. This cooling process aimed to preserve the material’s polar field, which is crucial for
its piezoelectric properties.
The piezoelectric sensors, are composed of ceramic elements coated with a layer of silver. On the
front part, Sensor 1 is coated with the same resin, Figure 3.8 (a), while the others are left in their original
form. To protect the wires and ensure secure electrical connections, an epoxy layer was applied to the
rear side of the sensors Figure 3.8 (b). This sensitive protective layer is crucial for enhancing electrical
conductivity and providing thermal protection. It prevents direct contact between water and wires while
also safeguarding the silver coating from ultrasound exposure.
Figure 3.8: Piezoelectric sensors for the acoustic reading with a (a) front view of sensors 1, 2 and 3 and
(b) the back view of the three once they have all the same construction.
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Developing an Ultrasound-based Water Treatment System
Having safeguarded the piezoelectric elements, the subsequent step involves processing the acquired
data. To achieve this, a program was developed in LabVIEW, encompassing three key sections: the main
menu, the Help menu, and the data acquisition menu.
The main menu offers users three distinct options: initiating the Data Acquisition process, accessing
the Help menu for guidance, or simply closing the program. This intuitive interface ensures easy navigation
and selection of desired actions.
Figure 3.9: Main Menu for the LabVIEW program with the Start, Help and Exit bottoms.
The LabVIEW program for the Main Menu is depicted in Figure 3.10. The structural arrangement for
the ”Help” and ”Start” buttons is outlined. The entire sequence is encapsulated within a ”Flat Sequence”
box, comprised of two distinct segments. The initial segment features a while loop cycle with an event
structure, while the second segment contains the command to terminate the program.
Focusing on the event structure, as depicted in Figure 3.10 (a), the code for activating the ”Start” and
”Help” menus is discernible. Pressing the ”Mais” button navigates to the ”Help” menu, whereas pressing
”Grave” directs the program to the recording menu. If the ”Exit” button (named as ”Ok”) is pressed, the
event structure transitions to a new state, terminating the while loop and facilitating the shift from the first
state in the sequence to the second, ultimately shutting down the program (Figure 3.10 b).
Selecting the Help menu provides access to a comprehensive guide, offering explanations of the entire
program and useful tips for organizing data effectively. The instructions provided in this menu are tailored
to simplify and optimize subsequent data processing in Python.
To facilitate seamless data treatment in Python, it is advisable to follow the naming and saving
conventions outlined in the Help menu. This systematic approach ensures that the data integrates
smoothly with the Python program.
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Developing an Ultrasound-based Water Treatment System
(a) (b)
Figure 3.10: LabVIEW code for the Main Menu with (a) sequence for the access to the Menu Start or Help
and (b) for close the program.
Additionally, a convenient feature is located in the lower right corner. When activated, this button
allows the user to download the Python program required for data treatment and generating FFT (Fast
Fourier Transform) graphics. This further streamlines the data analysis process and enhances the overall
user experience.
Figure 3.11: Help Menu with all the explanations for utilization of the program and all the options possible.
In Figure 3.12, the code for the Help Menu is presented. Much like the ”Main Menu,” this code
incorporates options to navigate to other menus. Specifically, pressing the button labeled ”Cancel” directs
the user back to the ”Main” menu, while selecting the button labeled ”Record” leads to the ”Start” menu.
To facilitate access to the external domain for downloading the Python code responsible for FFT and Force
graphics generation, a button is provided to guide the user through the file download process.
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Developing an Ultrasound-based Water Treatment System
Figure 3.12: LabVIEW Code for the Help Menu With Sequences for the Buttons.
Regarding to the menu for data acquisition, it is necessary to consider that data acquisition process
consists of two main components: real-time data visualization and user inputs. The graphics display
instantaneous voltage, corresponding Fast Fourier Transform (FFT), and calculate and display
instantaneous force on the sensors. This allows users to monitor and analyse measurements effectively.
The user interface for inputs allows modification of certain parameters and the decision on when to
save the data. To initiate data acquisition, users need to press the ”Play” button, after configuring the
acquisition parameters. For optimal results with three sensors and to achieve the maximum frequency
range, it is recommended to set the parameters to 83 kHz and 20 k samples per second.
The record function is activated only when the user presses the ”Record” button, enabling them to
specify the duration of the recording sample. This feature ensures precise and controlled data collection,
providing flexibility to capture data for specific periods as needed.
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Developing an Ultrasound-based Water Treatment System
Figure 3.13: Data Acquisition Menu with the FFT graphic, Impact Load and Voltage acquisition. It is
possible to set the recording time, the output file location, number of samples and rate and start and stop
the record.
In Figure 3.14, the Acquiring and Recording Menu operates by initiating data acquisition only when the
”Play” button is pressed. Upon meeting this condition, a countdown timer is activated. The duration of
the recording, denoted as ”slide 2,” is defined by the user within the ”User Interface.” Users can specify
the number of samples and the rate for data acquisition through the ”Number” and ”Rate” settings,
respectively. LabVIEW’s assistant is utilized for data acquisition, and the acquired signal undergoes noise
reduction processing.
To limit data acquisition above 9,000 Hz, a ”low-pass filter” is employed. This filter ensures that only
frequencies below the specified threshold are considered in the acquisition process.
The acquired data is presented through corresponding graphics. Prior to these graphics, a spectral
measurement is conducted to generate the FFT graphic. Additionally, an equation is applied to transform
the signal acquisition into Force readings.
For recording and exporting data, users can define the initial moment as mentioned earlier. Upon
pressing the ”Gravar” button, the data is recorded and exported to a ”.txt” file, following the predefined
time cycles. This functionality allows users to capture and export the acquired data for further analysis
and use.
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Developing an Ultrasound-based Water Treatment System
Figure 3.14: LabVIEW Code for Data Acquisition in the Recording and Acquisition Menu.
In the data analysis process, Python is employed to generate FFT graphs. The primary goal of this
program is to effectively eliminate noise and create text files containing frequencies of interest (10,000
Hz, 20,000 Hz, 30,000 Hz, and 40,000 Hz) along with their respective amplitudes in the FFT.
An important consideration during analysis is accounting for slight deviations in the output frequency
of the ultrasound. Therefore, a tolerance range of 1 kHz around the 20 kHz value is applied to ensure
accurate results. As mentioned previously, saving the file with a standardized name is crucial to facilitate
and optimize the Python program execution.
User input is minimal, as they only need to specify the first and last numbers of the acquisition
sample sequence and provide a name for the output file. The program will then read each file, generate
an individual FFT graph, and export the data as a single text file containing the maximum value for each
frequency of interest.
3.3 Experimental Conditions
To characterize the acoustic cavitation, the test protocol involve subjecting the sensors to varying
ultrasound conditions in two distinct chamber positions. To accommodate the unique behaviour of
ultrasound, particularly as power output increases, factors such as the influence of the horn and water
temperature come into play. The test methodology was deliberately designed to alternate between the
two extremes of power levels. This alternation between maximum and minimum power levels was
carried out methodically, with each power level maintained for a fixed duration of 18 seconds. During
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Developing an Ultrasound-based Water Treatment System
this interval, voltage samples were meticulously collected at regular 3-second intervals, resulting in the
acquisition of six voltage data points for each power level.
The decision to include a substantial number of sampling points in the experimental design was a
deliberate one, made with the goal of enhancing the quality and reproductive of the data. It was recognized
that our initial data collection efforts, which utilized fewer samples, had certain limitations. By significantly
increasing the number of samples taken, we ensured that the voltage data points closely mirrored the
actual conditions within the chamber. Consequently, this bolstered the reliability and robustness of the
obtained results.
It is also noteworthy that the power levels employed in the testing were controlled, with tolerances of
10W. These power levels were set at specific values: 70 W, 140 W, 280 W, 350 W, 420 W, 500 W, 600
W, 700 W. Furthermore, Sensors 1, 2, and 3 were positioned uniformly at the same height within the
chamber but strategically distributed to ensure comprehensive coverage. Position 1 was situated at 50
mm from the water level, while Position 2 was located at 250 mm from the top, Figure 3.15.
The data collection process was executed using the refereed program tailored for this specific purpose.
Subsequently, the collected data underwent treatment utilizing a Python program, to ensure consistency
and accuracy in the analysis. This methodology was essential for yielding meaningful insights into sensor
responses and their capacity to detect acoustic cavitation.
Figure 3.15: Test Positions 1 and 2. Position 1 is located at a distance of 50 mm from the water level,
while Position 2 is positioned 250 mm above it. The acoustic sensors are fixed to the interior structure.
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Developing an Ultrasound-based Water Treatment System
The piezoelectric sensors were individually calibrated due to variations resulting from the cutting
operations and epoxy application. It is intended to establish a calibration curve between the impact load
and the voltage. The calibration setup was identical for all three sensors, and the experimental
conditions were consistent and based on the study of Hujer et
al
. [157]. The setup, as shown in Figure
3.16, comprised a ruler, an acrylic guide, a slow-motion camera, a DAQ acquisition system connected to
a computer, and four different spheres. The DAQ acquisition employed was the NI 9205 from Texas
Instruments connected to the NI cDaq-9172 instrument.
Different spheres were used with varying dimensions and materials to achieve distinct impact loads
and characteristics. The spheres included an Alumina sphere with 2.02 g and mm diameter, two spheres
of Aluminium with 0.04 g and 0.40 g, and one sphere of stainless steel with 0.80 g. These spheres were
dropped from six different heights, 50 mm, 100 mm, 170 mm, 270 mm, 370 mm, and 470 mm through a
guide tube, with a stabilized pincer. This allowed to establish a relation between the range of impact loads
and ensured that the maximum impact load in the calibration remained less than the maximum impact
load from the cavitation. For the reading of the rebound it was used a camera with low speed recording.
Figure 3.16: Experimental Setup for Impact Test. The positions ’zero’ and ’rebounding’ are characterized
by their respective heights and velocities. Data acquisition from the presented piezoelectric element is
facilitated by the NI cDAQ 9172 system connected to the computer. The rebounding height is captured
using a slow-motion camera.
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Developing an Ultrasound-based Water Treatment System
The principle behind the test is that the impact of the spheres with the piezoelectric element will
generate a tension that can be measured and recorded. The interesting variables for force calculation are
shown in Equations 3.3 and 3.4.
F(avg) = 1
τ·∫t2
t1
F(t)dt (3.3)
F(avg) = m
τ·(v1+v2)(3.4)
where m is the mass of th ball, v1is the initial velocity (at point 1), v2the velocity on the point 2, and
τis the impact time of the sphere. This last parameter it is analysed on the recorded voltage acquisition
and corresponds to the piezoelectric voltage peak duration [157, 158].
Velocities from the point 1 to 2 can also be calculated with the following equation,
v1,2=√2·g·h1,2(3.5)
where h1,2it is the height of the ball from the sensor and g is the gravitational acceleration [157, 158].
The maximum force can be considered as the double of the average force,
Fmax = 2 ·Fav g (3.6)
Regarding to data acquisition, the 16 bit analogue module had 32 channels with a minimum and
maximum voltage acquisition of 96 µV and 10 V, respectively. The maximum conversion time was 4 µ·s,
resulting in a maximum sample acquisition rate of 250k samples per second. Considering three sensors,
the sample acquisition rate was divided among all channels. To capture the frequency range from 10 kHz
to 40 kHz, a minimum sampling rate of 80 kHz (twice the highest frequency) was set, resulting in a rate
of 83 kHz and a data collection interval of 12 µ·s.This parameters will be used in along the remaining
tests. In Table 3.2, are evident the parameter that were used along the laboratory tests.
Noise related to wire connections and surrounding sound waves influenced voltage acquisition. To
determine the minimal value for non-noise readings, various sensors were tested without any applied
force, and the average noise was found to range between 0 mV and 10 mV.
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Developing an Ultrasound-based Water Treatment System
Table 3.2: Data Acquisition Parameters for the NI cDAQ 9172.
Desired Frequency Range 9 kHz - 40 kHz
Sample Rate 83 kHz
Acquisition Interval 12 ms
Voltage Range 0.1 V - 10 V
However, the piezoelectric electrical response need the use of a tension divider. The output voltage
from the piezoelectric sensor exceeded 10 V, surpassing the limit of the NI cDAQ 9172. To mitigate this, a
voltage divider was implemented, Figure 3.17. This involved using a 200 Ohm resistance in conjunction
with a 10 Ohm resistance, resulting in a voltage drop of,
Voutput =Vinput ·R2
R1−R2
(3.7)
Voutput =Vinput ·10
200 −10 (3.8)
where Voutput it is the voltage output after the tension divisor, Vinput the initial voltage and R2and R1
the resistances.
Figure 3.17: Tension Divider for Tension Reduction: (a) Breadboard utilized for electrical connections. (b)
Electrical circuit for the tension divider.
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Developing an Ultrasound-based Water Treatment System
4. Experimental Evaluation
This chapter provides experimental evaluation results divided into two main sections. The first focuses
on the physical effects of cavitation, particularly the characterization using the developed piezoelectric
sensors. The second delves into the influence of ultrasound on water and adsorption systems. The
chapter concludes by offering a series of insights derived from the experimental evaluation.
4.1 Physical Analysis of Ultrasound Action on Water
4.1.1 Piezoelectric Calibration and Protective Layer Impact
During the calibration tests, it became evident that the three sensors, see Figure 3.8 exhibited different
behaviors. Interestingly, when a protective layer was applied, it was observed that the sensitivity of the
piezoelectric sensor decreased. The reduction in sensitivity was so significant that the piezoelectric sensor
failed to produce any voltage emission when a ball fell onto it. Subsequent testing with the maximum
impact load revealed that the voltage remained unchanged, and there were no discernible peaks on the
voltage acquisition graph, Figure 4.1.
This observation strongly suggests that the 0.2 mm Epoxy film used as a protective layer significantly
restricts the sensor’s sensitivity. Therefore, the protective layer negatively affects the sensor’s ability to
detect and respond to external forces. As seen in Figure 4.1, the voltage detection is less than the value
considered as noise. In that way, it was impossible to establish a calibration curve.
Figure 4.1: Voltage Measurement for Sensor 1 and its Respective Noise Threshold during the calibration
process.
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Developing an Ultrasound-based Water Treatment System
The calibration curve of the Sensor 2 shows a linear behavior of the sensor that can be described as
a linear relationship between the maximum impact load and the maximum voltage [157].
Figure 4.2: Calibration Curve for Sensor 2 with Voltage Variation in Response to Impact Load.
As the weight is change, the maximum voltage of the sensor varies a little. For 0.30 grams there is a
more linear growing tendency that for the other heights. This can be interconnected to the impact time.
Due to DAQ Acquisition limitation, the minimum time between samples were 12 µs, which corresponds
to 83 kHz. Wang et
al
. [159] shows that in similar conditions the impact time of the ball varies in less
than 12 µs. This suggests that the current sensors have limitations in data acquisition resolution. The
time impact does not vary so much across the time. For impacts of the heights of 0.30 grams and 0.88
grams, the impact time was the same, 36 µs. In the 2.02 grams ball case, the maximum impact time
was 60 µs and remains the same for all the cases. These results indicates that the tendency suggested by
the bibliography remains once that increasing the ball’s weight, the impact load increases as well. More
extended results could be seen on Appendix B and Appendix C.
This case is seen as for sensor 2, as for sensor 3 (see the sensors on Figure 3.8). Sensor 2 and
3 have some points that are dislocated from the linear tendency which can be directly connected to the
fact that impact time resolution and to experimental variations, mainly on the sensor’s impact site. In the
same way as sensor 2, the sensor 3 follows a linear tendency, creating a relation between the impact load
and the maximum voltage.
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Developing an Ultrasound-based Water Treatment System
Figure 4.3: Calibration Curve for Sensor 3 with Voltage Variation in Response to Impact Load.
Comparing both sensors, it is evident that they exhibit distinct slopes and theoretical sensitivities. The
sensitivity constant, derived from the rate of change of Voltage in relation to applied Force on the squared
line, indicates that sensor 2 has a sensitivity of 0.04 V/N, whereas sensor 3 boasts an equal sensitivity of
0.04 V/N. Unfortunately, the manufacture did not provide informations to compare.
Regarding the response to the impact, as depicted in Figure 4.4, it is evident that sensor 2 produces a
higher voltage under the same impact load. While this discrepancy becomes notable only for a 0.88 grams
sphere after 275 N, it raises the possibility of differing piezoelectric properties between the sensors. The
manufacturing process, specifically the cutting procedure, may influence their piezoelectric characteristics.
Another conceivable explanation could be associated with potential experimental errors. Despite utilizing
5 data points to establish the calibration curve, variations in the point of impact between the sphere and
the piezoelectric material might occur. Additionally, during rebound, the sphere could come into contact
with a lateral surface, leading to energy dissipation. Nonetheless, it is apparent that both sensors exhibit a
consistent growth pattern for both variables. Any disparities observed are likely attributable to experimental
inaccuracies and energy losses.
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Developing an Ultrasound-based Water Treatment System
Figure 4.4: Voltage as a Function of Impact Load: Sensor 2 exhibits a higher voltage reading for each
impact load. However, both sensors display similar temporal behavior, differing primarily in sensitivity.
The resistance and reliability of the sensors were evaluated through various tests in the chamber. The
initial test was conducted without data acquisition to assess the effects of ultrasound on the silver layer
of the ceramic and the ceramic itself. Ultrasound power was varied from 100 W to 800 W, in 100 W
increments, and each power level was applied for 10 s, totaling 90 s. The sensors were located on the
same position on the chamber, Figure 4.5 (b), but scattered around the chamber.
In Figure 4.5 (a), the degradation of the ceramic silver layer is visible at the end of the test for sensors
2 and 3. Notably, the degradation was not uniform between the two sensors, as sensor 3 exhibited less
deterioration compared to sensor 2. Sensor 2 also showed signs of breakage, with a noticeable fracture
running through the entire ceramic layer. However, it should be mentioned that despite this fracture, the
piezoelectric was still able to produce Voltage reading. The epoxy protection constrained the movements
of the ceramic, thereby preserving its piezoelectric functionality.
On the other hand, sensor 1, with the epoxy layer, remained unaffected as the epoxy provided protection
to the silver layer. Nevertheless, Figure 4.5 illustrates that the sensor was not entirely covered by the epoxy
layer due to the polishing process, causing some millimeter defects in the layer. These uncovered areas
were vulnerable to wear and tear caused by the action of ultrasound.
The tests revealed that the sensors without any protective layer are more subjects to degradation by
effect of ultrasound. However, without any more specific tests it is impossible to announce if the sensor
is compromised or not. More tests were done in order to ensure if the sensor is operation or not.
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Figure 4.5: Piezoelectric sensors after 90 seconds of cavitation at varying ultrasound frequencies - from
100 W to 900 W, with 10-second intervals. (a) The three sensors were at the same level on the chamber,
with 80 mm difference from the water level. (b) Sensor 1 exhibited damages only on areas with deficient
epoxy cover. Sensors 2 and 3 displayed damages on the surface layer.
4.1.2 Cavitation Monitorization with Piezoelectric Sensors
The investigation of the sub-harmonic (f/2) has proven to be a reliable parameter in understanding the
development of acoustic cavitation within a liquid solution [155]. Figure 4.10 displays the variation of the
sub-harmonic for the three sensors at different frequencies, for the Position 1, see Figure 3.15 for positions.
This study aims to discern the magnitude of the sub-harmonic as the frequency increases, shedding light
on the cavitation development.
In correlation with the studies of Eskin et
al
. [160] and Abramov et
al
. [161] three distinct zones have
been proposed. The first zone is referred to as the incipient cavitation, followed by the cavitation threshold
in the second zone, and the well-developed cavitation regime in the third. The transition between these
zones is believed to occur due to a significant increase in the acoustic signal of the sub-harmonic, signifying
the cavitation threshold has been reached, as suggested by Eskin et
al
. [160] and Puga et
al
. [155].
To construct the current graph, was calculated the magnitude of the acoustic signal at the
sub-harmonic point. Each data point on the graph represents an average derived from five
measurements, with the mean deviation indicated in each corresponding plot.
When examining the piezoelectric sensor responses within the cavitation field at ”Position 1”,
distinctive patterns emerge for each sensor, Figure 4.6. Sensor 3, located in this position, generally
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Developing an Ultrasound-based Water Treatment System
exhibits a magnitude similar to Sensor 1, with the exception of a noticeable drop at 340±10 W. Given
that this deviation is isolated, it is categorized as an anomaly and deemed a data error.
In contrast, Sensor 2 consistently displays irregular data points, indicating a potential issue with its
functionality. This inconsistency raises concerns about its reliability in providing accurate measurements.
Notably, a sharp increase in the acoustic signal is observed within the power range of 500±10 W
to 600±10 W for Sensor 3. Sensor 1 demonstrates a gradual and smooth increase, while Sensor 3
experiences a significantly sharper and higher rise across the entire spectrum. The discrepancy in the
sharpness of the increase between Sensor 1 and Sensor 3 may stem from differences in sensitivity or
from variations in cavitation distribution within the chamber. Even when positioned at the same height,
the propagation of acoustic waves is not uniform in all directions at a given point along the y-axis.
Taking all of this into consideration, and based on the information provided, this range is established
as the new threshold point for this specific position.
Figure 4.6: Magnitude variation of the sub-harmonic (f/2) for Sensors 1, 2, and 3 at Position 1. The
analysis is divided into three zones, Zone 1 (0 W to 500±10 W), Zone 2 (Beginning of cavitation, 500±10
W to 600±10 W), Zone 3 (Developed cavitation, after 600±10 W).
Looking to the responses of Sensors 1 and 3 across various powers, a similar growth pattern is evident,
with the exception at 60±10 W and 340±10 W. The spike at 340±10 W is deemed an anomaly and should
be excluded from this analysis. This sudden deviation may be attributed to the fact that, in this study, the
last cavitation reading was taken at this frequency. This implies that the water temperature may have
increased, consequently altering the cavitation response.
The gradual increase seen in almost all range in the acoustic signal, is momentarily interrupted by a
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Developing an Ultrasound-based Water Treatment System
sharp rise within the frequency range of 500±10 W to 600±10 W, mainly on Sensor 3. This could indicate
the cavitation threshold. However, this sharp increase is only seen for Sensor 3, being that Sensor 1 only
have a sharp increase at 700±10 W.
The noted disparity between the two sensors could be linked to the protective layer present on Sensor
1. This layer might render Sensor 1 less sensitive compared to Sensor 3. The protection provided by
the layer may serve as a dampening factor, resulting in reduced sensitivity to the acoustic signals. Other
condition is the position of the sensors. Despite their close proximity, the acoustic cavitation could not be
uniform across all points, leading to varying measurements, as it will be seen further.
Overall, despite minor disparities at specific frequencies, both sensors in ”Position 1” exhibit consistent
and nearly identical behavior in response to the acoustic signals. The presence of the protective layer in
Sensor 1 could be a contributing factor to the subtle variations observed between the two sensors.
Figure 4.7: Analysis of sub-harmonic magnitude variation for Sensors 1 and 3 at Position 1. Standard
deviation aside, line plots show consistent behavior, especially for lower values. Cavitation threshold lies
between 500 W and 600 W, marked by a sharp increase. Value at 350 W is negligible, stemming from an
instantaneous peak.
In this case, when the acoustic cavitation threshold is not readily discernible, it becomes imperative
to verify it through FFT graphics. Additionally, the analysis of sub-harmonic amplitudes across various
frequencies must also be corroborated by the FFT graphics derived from the acoustic readings. The
acoustic threshold is attained when the magnitude at the ultra-harmonic (3f/2) remains consistent as the
frequency escalates. The same behavior is expected for the remaining harmonics. This method serves to
substantiate the suggested threshold range through the observation of ultra-harmonics [155, 161].
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Developing an Ultrasound-based Water Treatment System
Figure 4.8 depicts the progression of magnitude for various harmonics, sub-harmonics, and ultra-
harmonics at power levels of 260±10 W, 500±10 W, and 700±10 W for Sensor 1 at Position 1. The
sub-harmonic (10,000 Hz) amplitude increases proportionally with the rise in power. This behavior is
similarly observed for the harmonics, showcasing a comparable peak amplitude at 260±10 W (Figure 4.8
(a)) and 600±10 W (Figure 4.8 (b)), with a more pronounced increase at 700±10 W (Figure 4.8 (c)).
In terms of ultra-harmonics, it is notable that increasing the power leads to an escalation in the ultra-
harmonic, although this trend is not as evident for the ultra-harmonic. However, the consistent rise in
magnitude around 30,000 Hz, combined with a similar pattern at 10,000 Hz, suggests the presence of
cavitation effects between 600±10 W and 700±10 W.
(a) (b)
(c)
Figure 4.8: Fast Fourier transform graphics for the sensor 1 at position 1 for (a) 260±10 W (b) 500±10
W and (c) 700±10 W.
Respecting to the Sensor 3, Figure 4.9, the analysis is similar. The presence of acoustic cavitation is
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Developing an Ultrasound-based Water Treatment System
demonstrated by the rise in both sub-harmonics and ultra-harmonics, followed by the stabilization of the
ultra-harmonics after 600±10 W [161].
(a) (b)
(c)
Figure 4.9: Fast Fourier transform graphics for the sensor 3 at the position 1 for (a) 260±10 W (b)
500±10 W and (c) 700±10 W.
Regarding to Position 2, the transition between the zones is observed between the 410±10 W and
500±10 W power. Within this range, a sudden increase in the magnitude of the acoustic signal is evident,
indicating the cavitation threshold has been surpassed. However, this observation is only clearly visible
for Sensor 1 and Sensor 3. Sensor 2 exhibits erratic behavior without any discernible linear relation. The
presence of a fracture in Sensor 2 might suggest that this issue is affecting the accuracy of the readings
obtained from this particular sensor. Further investigation is warranted to address this inconsistency in
Sensor 2’s behavior.
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Developing an Ultrasound-based Water Treatment System
Figure 4.10: Magnitude variation of the sub-harmonic for Sensors 1, 2, and 3 at Position 2. The analysis
is segmented into three zones: Zone 1 (0 W to 410 W ), Zone 2 (Beginning of cavitation, 410±10 W to
500±10 W), Zone 3 (Developed cavitation, after 500±10 W).
Upon comparing Sensor 1 and Sensor 3, a notable difference is observed in the strength of the
acoustic signal, with Sensor 3 showing a much stronger signal. Throughout all data points, the acoustic
signal is consistently stronger for sensor three, and at its peak, it reaches approximately 40% higher than
that of sensor one. However, after reaching the cavitation threshold, there is not a significant increase
in the acoustic signal. In fact, a slight decrease of around 5% is noticeable. This behavior suggests that
while cavitation has entered a well-developed regime, the ultrasound action might not be entirely stable.
During the experiments, it was observed that high ultrasound powers tend to be less stable, leading to
some variations in the acoustic signal input. This instability in the ultrasound action might explain the
observed decrease in the acoustic signal after reaching the cavitation threshold. Overall, the comparison
between Sensor 1 and Sensor 3, reveals that the absence of the protective layer in sensor three results in
a stronger acoustic signal.
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Developing an Ultrasound-based Water Treatment System
Figure 4.11: Analysis of sub-harmonic magnitude variation for Sensors 1 and 3 at Position 2. The cavitation
threshold is between 400±10 W and 500±10 W, marked by a sharp increase. Beyond this threshold, the
magnitude stabilizes with a slight decrease.
Analysis of sub-harmonic magnitude variation for Sensors 1 and 3 at Position 1. Standard deviation
aside, line plots show consistent behavior, especially for lower values. Cavitation threshold lies between
500±10 W and 600±10 W, marked by a sharp increase. Value at 350 W is negligible, stemming from
an instantaneous peak.
Similar to the methodology employed for Position 1, the confirmation of the cavitation threshold
hinges on the scrutiny of FFT graphics, specifically focusing on the fluctuations in sub-harmonics and
ultra-harmonics in response to power escalation [161]. In Figure 4.12, the variations in magnitude are
depicted for power levels of (a) 260±10 W (b) 500±10 W and (c) 700±10 W for sensor 1. As
anticipated, at 260±10 W, 3/2f and 2f exhibit a lack of stabilization. However, within the range of
500±10 W to 700±10 W, it is evident that 3/2f and 2f achieve stability and show an augmentation in
magnitude concurrent with the increase in power. This observation strongly indicates that the cavitation
threshold has been attained, thereby substantiating the previous hypotheses.
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Developing an Ultrasound-based Water Treatment System
(a) (b)
(c)
Figure 4.12: Fast Fourier transform graphics for the Sensor 1 at the Position 2 for (a) 260±10 W (b)
500±10 W and (c) 700±10 W.
Regarding to Sensor 3, the same behavior is seen. However, in this case, the increase of the
harmonic frequency (20,000 Hz), it is seen more at the power of 500±10 W. However, this is not a
problem because second bibliography [161], the ultra-harmonics 3f/2 and 2f, shows a better indicator of
acoustic cavitation. In this case, it is possible to see that there is an constant increase of the
ultra-harmonics and the stabilization of them, suggesting and confirmed the induction of acoustic
cavitation.
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Developing an Ultrasound-based Water Treatment System
(a) (b)
(c)
Figure 4.13: Fast Fourier transform graphics for the sensor 3 at the position 2 for (a) 260±10 W (b)
500±10 W and (c) 700±10 W.
As seen in Figure 4.7 and Figure 4.11, even employing five data points to characterize the acoustic
readings, it is evident that there is a notable standard deviation for nearly all points. Nevertheless, this
discrepancy does not significantly impact the final results, as the curve consistently follows a similar growth
pattern, even when considering the minimum values for each point. The elevated standard deviation
suggests the presence of noise, as well as other acoustic waves with varying frequencies and a non-uniform
distribution of cavitation within the chamber.
To test this hypothesis, the behavior of cavitation induced by ultrasound in water was studied.
As shown in Figure 4.14, it’s evident that cavitation exhibits fluctuations along both the ”xx” and ”yy”
axes over time. Across four distinct time points, each with a one-second interval, noticeable variations
in bubble water flux are observed. This highlights that water flow is inherently time-dependent, resulting
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Developing an Ultrasound-based Water Treatment System
in varying pressure fluxes on the water and, consequently, distinct acoustic readings on the piezoelectric
sensor. Consequently, making direct comparisons between the two positions is is not possible, as they
inherently involve different geometrical parameters of acoustic radiation and waveguide, potentially leading
to differing cavitation behaviors.
Additionally, these fluctuations along both axes explain why sensors positioned in the same location
might have different cavitation thresholds or measurements.
Figure 4.14: Bubble formation due to cavitation over 4 seconds. Cavitation flow changes in axial and radial
positions may interfere with acoustic readings due to waves propagating in different directions within the
same position.
In Figure 4.15, the formation of bubbles within the holes is clearly observable. It is worth noting that
the waveguide and the acoustic radiator demonstrate distinct behaviors when interacting with water. On
the waveguide, cavitation primarily occurs around the hole locations, generating elliptical flows outward
from these points, acoustic streaming. This geometric characteristic effectively increases the contact area
between water and ultrasound, intensifying the cavitation phenomena. However, it is important to highlight
that cavitation formation is not solely confined to the hole regions but also extends to the wall side.
As shown in Figure 4.15 (b), the waveguide perforations exhibit two distinct configurations. When
the waveguide is excited, the holes undergo a transformation, adopting an elliptical shape that oscillates
around their central axis. Initially, the central axis alignment is axial, while the others are radial.
This behavior is mirrored in the ultrasonic acoustic radiator. The acoustic radiator features two primary
sources of acoustic propagation, as illustrated in Figure 4.15 (a). Considering the axis of the ultrasound
revolution as a reference, it is possible to discern cavitation formation both along this axis and perpendicular
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Developing an Ultrasound-based Water Treatment System
to it. The wave propagation from the cylindrical wall (referred to as the xx axis) is an extension of what
occurs on the waveguide.
Regarding the bottom part of the horn, wave propagation occurs through the propagation of acoustic
waves along the same axis as the ultrasound. This propagation appears as an inverted mushroom shape
at the bottom and a conical shape at the top. Bubble formation is most pronounced at the point of contact
with the ultrasound and gradually diminishes visually with increasing distance from it, giving it a conical
shape. Simultaneously, the acoustic propagation gradually expands after some distance, until it reaches
the bottom of the chamber, resembling a mushroom.
This is a typical behavior for the propagation of cavitation bubbles when using sonotrodes with
cavitation formation on the same axis as the ultrasound [162]. The conical bubble structures are referred
in literature as common in cavitation produced by these devices [162]. In fact, based on the same
investigation, and focusing on the bottom part of the acoustic radiator, the bubble propagation suggests
that the quartz particles move towards the periphery, indicating that the vibration is stronger at the center
than at the periphery. This is depicted in Figure 4.15, which provides a schematic representation of the
observed phenomena. The amplitude of the propagation is higher at the center than at the periphery.
However, when establishing a comparison with the cavitation generated from the waveguide and the
acoustic radiator, it is evident that the cavitation bubbles have different configurations, and the propagation
is also distinct. Cavitation bubbles produced by the acoustic radiation suggest that the amplitude is higher
at the center and the propagation is in a conical shape. In contrast, at the contact surface between water
and the acoustic radiator, taking into account the cavitation bubble structures, the acoustic streaming is
propagated from the center to the outside [162].
However, the phenomenon observed here differs from that presented by the waveguide. Due to the
presence of holes, the propagation in the waveguide seems to amalgamate two distinct types of cavitation
bubble structures along with acoustic streaming. In this case, the cavitation bubble structure may not be
entirely discernible, but the presence of acoustic streaming is conspicuous.
Upon comparing the studies of Moussatov et
al
. [163] and Bai et
al
. [162] with the pattern illustrated
in Figure 4.15, it is possible to observe that along the waveguide, there are zones where acoustic streaming
occurs in isolation. Furthermore, it tends to shift from the center towards the periphery in some areas,
while in others, it moves from the periphery towards the center, forming a distinctive ”X” shape.
This behavior strongly suggests that the amplitude of vibrations is influenced by the presence of holes,
resulting in a geometric configuration where certain areas exhibit higher amplitudes while being surrounded
by regions of lower amplitudes, and vice versa.
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Figure 4.15: Cavitation generation by the ultrasound acoustic radiator (a) Ultrasound induces cavitation
with axial and radial movements, creating centrifugal flow. Axial movements at base generate cavitation-
aligned acoustic waves. (b) Acoustic streaming distribution along wave guide, low and high center
amplitude. (c) Conical bubble structure on ultrasound acoustic radiator tip.
In Figure 4.9, Figure 4.8, Figure 4.12, and Figure 4.13, discernible peaks emerge around 15,000 Hz,
25,000 Hz, and 35,000 Hz. Notably, these peaks exhibit lower magnitudes in comparison to those of
the sub-harmonics, harmonics, and ultra-harmonics. By examining the relationship between the
frequency at which the maximum voltage is attained for these peaks and its association with the
resonance phenomenon, it becomes evident that there exists a consistent difference of 1 harmonic
between each noise peak. This value aligns with the harmonic, as illustrated in Figure 4.16.
Given the traceable mathematical relation and the consistent presence of a peak between each
harmonic, distinct from one complete harmonic, it is proposed that these peaks result from the
resonance and refraction occurring within the chamber itself. The refraction of acoustic waves within the
ultrasound chamber gives rise to additional frequency peaks.
Regarding to the impact load reading by the sensor, it was considered the 10 most high values of all
reading for each point and calculated the mean. As it can be seen on Figure 4.17 (a), the standard average
error it is not high enough to interfere on the final results. Once that the transformation from voltage to
impact load is made by a equation, the standard deviation from the voltage can not be considered in the
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Developing an Ultrasound-based Water Treatment System
Figure 4.16: Analysis of the distribution of the noise on the voltage acquisition and it relation with the
sub-harmonic, harmonic and ultra-harmonic.
impact load. It was used just the mean values but always considering that the values does not impact
significantly the voltage acquisition.
Given that Sensor 2 is inoperable, Figure 4.5, and Sensor 1 lacks the necessary sensitivity to trace
the force calibration curve, Figure 4.1, only results from Sensor 3 were taken into consideration for force
readings. In Position 1, the maximum impact load value is 12.25 V, achieved at a power of 700±10 W.
As observed previously, a dip in voltage values at 410±W corresponds to a lower impact load.
Figure 4.17: (a) Voltage Values Recorded by Piezoelectric Sensor 1. (b) Corresponding Impact Load
Calculated Using the Previous Calibration Line and the mean voltage value.
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Developing an Ultrasound-based Water Treatment System
In Position 2, the behaviour similarly aligns with the sub-harmonic pattern over time. The maximum
recorded impact load is 15.25 N, achieved at a frequency of 500±10 W. Following this peak, the intensity
gradually diminishes until 700±10 W. As mentioned earlier, the occurrence of a peak was not anticipated,
as a linear and continuous growth was expected. However, it is noteworthy that the tests were conducted
sequentially, with the final test at the highest power level, resulting in elevated temperatures of both the
ultrasound equipment and water. This elevation in temperature induced some deviations from the normal
functioning of the ultrasound system.
Comparing with the research made by Wang et
al.
[159] the acoustic cavitation, at 0.3 mm of distance
between the source of cavitation and sensor, is 0.2 kN. In this case, the distance between them is 15 mm,
making it impossible to made a linear relation between them.
Figure 4.18: (a) Voltage Values Recorded by Piezoelectric Sensor 2. (b) Corresponding Impact Load
Calculated Using the Previous Calibration Line and the mean voltage value.
4.1.3 Resonance Frequency Analysis of Piezoelectric Sensors
As previously noted, Sensor 2 displays notable damage attributed to the cavitation effect (see Figure 4.5).
The FFT graph findings strongly indicate sensor impairment, making it unreliable for acoustic cavitation
measurements. To address potential test errors that could have affected sensor responses, the sensor’s
natural resonance was evaluated using a TRZ analyser. When examining the impedance of Sensor 2, the
TRZ analyser did not identify any significant variations. This reinforces the assessment that the piezoelectric
sensor is impaired and cannot be deemed suitable for precise measurements.
For the remaining sensors, it was compared the resonance frequencies in three phases of the
piezoelectric material, the original and final configurations, Figure 4.19. In this case, what is pretended is
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Developing an Ultrasound-based Water Treatment System
to understand what is the main consequence of applying an Epoxy layer and cut in a square the initial
ceramic disk. The first configuration is the initial one, without any geometrical change (Piezoelectric A).
The second configuration is the final configuration with the ceramic disks with new dimensions and with
an Epoxy film (Piezoelectric B).
Figure 4.19: Piezoelectric sensors with two geometries. Piezoelectric A represents the unmodified
piezoelectric, while Piezoelectric B denotes the final geometry and its corresponding Epoxy layer.
Concerning the original configuration, Figure 4.19 (a), Figure 4.20 illustrates that the resonance
frequency is 44,550 Hz, while the anti-resonance is at 45,480 Hz. These values fall within the tolerance
range of resonance indicated by the manufacturer, see Appendix A, that was 44±2 kHz.
Figure 4.20: Impedance graphic for piezoelectric A with the Resonance t 44,550 Hz and anti-resonance
at 45,480 Hz.
Turning the attention to the piezoelectric sensor with the epoxy layer, Piezoelectric B, Figure 4.19 (b),
it is observed that the first resonance fall in the expected value, 44,550 Hz, while the second fall out,
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Developing an Ultrasound-based Water Treatment System
46,500 Hz, Figure 4.21. The corresponding anti-resonance frequencies are 45,530 Hz and 47,520 Hz,
respectively.
(a) (b)
Figure 4.21: Impedance graph for Piezoelectric B, which includes the epoxy layer, two distinct resonances
and anti-resonance are evident: (a) at 44,550 Hz and 46,500 Hz and at (b) 46,500 Hz and 47,520 Hz.
When comparing both graphs, it becomes evident that both configurations exhibit one resonance
frequency within the expected range. Piezoelectric A and B share a similar primary resonance, differing
by a maximum of only 110 Hz, which is negligible, Table 4.1. However, the modification of the geometry
leads to a new resonance frequency at 46,500 Hz.
The analysis of these two sensors confirms that they adhere to the manufacturer’s specifications.
However, the resonance outside the specified range can be attributed to modifications in the geometry
and the addition of an epoxy layer to Piezoelectric B during its construction.
Furthermore, it is noteworthy that the epoxy layer, at this stage, does not appear to significantly affect
the behavior of the piezoelectric material. The resonance frequency remains consistent across different
sensors, indicating a similarity in their performance.
Table 4.1: Resonance and Anti-Resonance comparison between Piezoelectric A and B.
Resonance Anti-Resonance Resonance Anti-Resonance
Piezoelectric A 44,550 Hz 45,450 Hz - -
Piezoelectric B 44,550 Hz 45,560 Hz 46,500 Hz 47,550 Hz
The cavitation and wave propagation vary with the frequency of the ultrasound [106]. This variation is
influenced by the volume of water inside the chamber, which consequently affects the contact area between
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Developing an Ultrasound-based Water Treatment System
the ultrasound and the water. To analyse the relation between the contact area and the ultrasound’s effect
on water, a study was conducted. The ultrasound was brought into contact with water at different depths.
In this scenario, the point labelled as zero represents the initial contact between the water’s surface and
the tip of the ultrasound face, signifying the minimum possible contact between them. The other points
analysed were at depths of 80 mm (Position 1), 180 mm, 280 mm (Position 2) and 300 mm, 4.22 (a).
As depicted in Figure 4.22 (b), an increase in the contact area between the ultrasound and water
influences the resonance frequency. Progressing from the first to the last position, the ultrasound frequency
decreases from 19,650 Hz (at 0 mm depth) to aproximatdly 19,220 Hz (at 180 mm and 280 mm depths)
and 19,150 Hz (at 300 mm depth). Increasing the area of contact, the resonance decrease. It is also
evident that with an increase in depth, the impedance graph exhibits more noise. This phenomenon can
be attributed to the presence of resonance-induced noise in the water and its subsequent attenuation.
The existence of noise can be also linked to the emergence of new resonances. At a distance of 300
mm, a minor resonance is observable, potentially attributed to the substantial mass of water in direct
contact with the upper part of the ultrasound device. This gives rise to a secondary reaction, resulting
in the appearance of a new cavitation source above the ultrasound apparatus. Throughout the tests, this
phenomenon became conspicuous, causing instability in the system and introducing problematic behavior
in the ultrasound operation.
Figure 4.22: Ultrasound Resonance Test. (a) Conducted at different levels of submersion in water. (b)
Resonance at minimal water contact measured at 19,700 Hz. Decreasing submersion depth led to a
decrease in resonance frequency.
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4.1.4 Ultrasound Effects on Water and Water-Oil Mixture
Simultaneously, with the automation of the previous ultrasound system, a study was conducted using a
smaller ultrasound device to comprehend the water flow and variations in key water quality parameters.
This initial test focused on the behaviour of a water and oil mixture when applied the ultrasound
system. To conduct this experiment, a solution was prepared by blending 1 L of water with 10 mL of SAE
10W40 oil produced by Castrol. Ultrasound was applied to this solution for a total duration of 2 minutes,
operating in cycles of 15 seconds on and 15 seconds off. The ultrasound power was set at 65W with a
tolerance of 5W, resulting in a power intensity of 20.7 W·cm−2, calculated using Equation 2.12. A camera
was strategically positioned to capture the entire solution flow.
Figure 4.23: Flocculation and coagulation test on water-oil mixture: (a) Experiment: 500 mL beaker with
500 mL water and 10 mL SAE 10W40 oil. (b) Intermittent ultrasound treatment: 15 seconds on, 15
seconds off, for 2 minutes.
In Figure 4.24, the chronological sequence of events during the test is presented. At the initial time
point, as depicted in Figure 4.24 (a), representing the condition before activating the ultrasound, a thin
film of oil is visible on the surface of the water. The oil and water do not naturally mix due to their differing
polarities and densities, causing them to separate into distinct layers when combined [164].
As the experiment progresses to the 2 seconds mark, as depicted in Figure 4.24 (b), a distinctive white
mixture starts to take shape, forming an inverted mushroom-like structure originating from the ultrasound
tip. This phenomenon vividly illustrates the impact of ultrasound waves on the water. It provides insight
into the path of acoustic propagation along the revolution axis of the ultrasound, and it’s notable that the
diameter of acoustic influence tends to expand with distance from the ultrasound source. Additionally,
there is noticeable vortex formation and reflux along the beaker’s wall during this initial phase. However,
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Developing an Ultrasound-based Water Treatment System
it’s worth noting that this visible effect is primarily observed within the first two seconds.
Subsequently, the mixture becomes uniformly white, making it challenging to discern specific fluid
dynamics, as seen in Figure 4.24 (c). Nevertheless, based on initial observations, it is anticipated that the
water flow pattern remains consistent with what was presented in 4.24 (b). The intense mixing suggests
that the flow phenomena persist and simultaneously enhance the visual mixing of water and oil.
Upon concluding the three minutes of ultrasound application, the water-oil solution remains highly
turbid, with no signs of flocculation or coagulation initiation, as indicated in Figure 4.24 (d). In fact, the
ultrasound tends to emulsify the solution and hinders the flocculation/coagulation process. After one
week, the solution still appears white and shows no discernible changes.
The quick mixing of the two fluids, in conjunction with insights from the cited literature on the effects
of ultrasound on the increased efficiency of coagulation and flotation processes [66, 68, 165], suggests
that ultrasound could enhance the mixing between the solution and the coagulant. However, given the
absence of specific studies on the application of ultrasound systems to coagulation/flotation processes
for oil removal, the results obtained from the analysis of water flow behaviour serve as a basis for further
investigation. This study should be extended, introducing coagulants to explore their potential impact on
the overall process.
Figure 4.24: Mixture visual behaviour over 3 minutes. (a) Initial state pre-ultrasound. (b) Movement of
water mixture in the first second after ultrasound, forming an inverted mushroom-shaped white mixture.
(c)(d) By the second second, the mixture is entirely white.
To gain a deeper understanding of fluid movement at the bottom of the ultrasound acoustic radiator
and its implications for the movement of solids within the solution, an investigation was conducted by
studying the water flow with the integration of wax beads. As depicted in Figure 4.25 (a), the wave
propagation on this Ultrasound begins with the sound travelling through the water from the base of the
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Developing an Ultrasound-based Water Treatment System
acoustic radiator.This principle mirrors the approach employed at the base of the acoustic radiator in the
primary ultrasound system, serving as a reference point to comprehend the dynamics occurring within it.
It is noticeable that the flow propagation aligns with the axis of the horn’s output tip. The pressure waves
emanate from the bottom of the ultrasound transducer in a vertical direction, colliding with the beaker.
Consequently, the water molecules in this region are displaced outward, resulting in a continuous motion
phenomenon throughout the duration of the ultrasound application, as shown in Figure 4.25 (b). This
fluid movement appears akin to an inverted mushroom shape. The cavitation shape, as seen before,
correspond to a bubble structure, typical of ultrasonic horns of this type [163]
The molecules are pushed towards the beaker’s sidewall, concurrently generating a centrifugal flow
near the beaker’s wall. Observable features include regions of reflux and the creation of vortices, as
depicted in Figure 4.25 (c). This phenomenon is particularly pronounced at the onset and persists
throughout the ultrasound action.
Once cavitation is established, and the system reaches a stable phase, two distinct phenomena
become apparent. At the bottom, pressure waves continue to generate the centrifugal flow, while those
able to escape the ultrasound field ascend and, at the top, re-enter the cavitation field, resulting in their
descent, see Figure 4.25 (d). This process unfolds continuously, providing insights into wave propagation
patterns through this type of horn and the distribution of flows along the beaker.
Figure 4.25: Sequence of Water Flow Movements upon Contact with Ultrasound. (a) Initially, the wave
propagates along the same axis as the ultrasound. (b) Upon reaching the bottom, the flow tends to dissipate
towards the base, causing radial movement. (c) The flow now has two paths: it can ascend through the
sides, escaping ultrasound, or remain at the bottom as refluxes. (d) Escaped molecules are recirculated
to the bottom due to continued ultrasound action.
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Developing an Ultrasound-based Water Treatment System
4.2 Ultrasound Effects on Water Characteristics and
Adsorption
Before beginning the analysis of parameter variations over time, it is crucial to establish the method for
data analysis. The assessment of parameter variation will involve considering the relationship between the
initial and final values, as expressed by the equation,
C(%) = Ci−C0
C0
×100 (4.1)
where C is the variation from the initial point in percentage, Ciis the value at time i and C0is the
initial value. It is important to mention that the units on the initial values must be the same as Ci.
4.2.1 Impact of Ultrasound on ORP and pH
Focusing on the effects of cavitation on water characteristics, the investigation shifted towards examining
variations in pH and ORP for both tap water and ultra-filtrated water. To assess the influence of ultrasound
on water, a study was conducted to investigate the effects of ultrasound at a electrical power of 65 ±5
W, 20.7 W (±1.6 W·m−2) on a 500 mL beaker containing ultra-filtrated water or tap water. Every 18
seconds, pH and ORP were measured using the HI8424 equipment and recorded. In parallel, a similar
experiment was conducted without applying ultrasound, simply allowing the water to come into contact
with air. The experiment lasted for 144 seconds and aimed to understand the increase in reaction speed
facilitated by ultrasound.
Beginning with the analysis of ultra-filtrated water, particularly focusing on ORP, Figure 4.26 (a) provides
a clear visual of the impact of acoustic cavitation on the ORP. The initial 18 seconds witnessed a rapid
surge, marking a 2.52-fold increase. Following this initial surge, the application of ultrasound exhibited
minimal impact on the ORP, aligning closely with instances where ultrasound was not employed. The
values of ∆1 and ∆2 further underscored comparable rates of increase.
Comparing the pH, as depicted in Figure 4.26 (b), it is notable that in the first 18 seconds, the pH
decreased 2.29 times faster compared to when ultrasound was not applied. The difference in growth
rates persisted until around 40 s, after which the behaviors became similar. At 50 s, the difference in pH
between the two conditions was 6 units, which reduced to 4 units at 60 s and remained constant for the
rest of the experimental test.
The graphical representations of the pH and ORP data further support that ultrasound enhances
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Developing an Ultrasound-based Water Treatment System
chemical reactions in the water. The data suggest that ultrasound action promotes more oxidative
reactions, enhancing the oxidation process and accelerating chemical reactions. In this case, ultrasound
appears to act as a catalyst, exerting a significant effect initially, thereby intensifying its impact on the
water.
(a) (b)
Figure 4.26: Effects of acoustic cavitation on the ORP and pH of ultra-filtered water. (a) The ORP increases
2.52 times fast with ultrasound action and then stabilize. (b) The decreases 2.29 times faster and then
stabilize as well.
When observing the evolution of the same parameters for tap water, several interesting observations
were made. Without ultrasound action, the ORP did not exhibit any significant variation. However, when
ultrasound was applied, two distinct zones were observed. The first, referred to as Zone ”A” in Figure
4.27 (a), was characterized by a slight decrease in ORP. Following this initial period, ultrasound had a
pronounced effect, leading to a significant decrease in ORP values. Comparing the points at 40 s, 90 s,
and 140 s, the differences in ORP without ultrasound were 14 units, 24 units, and 28 units, respectively.
The action of ultrasound on tap water appears to enhance its capacity to donate electrons, resulting in
oxidation processes. This phenomena is constantly growing, within the study 142 s range.
Concerning the pH behaviour, as illustrated in Figure 4.27 (b), ultrasound induces a rapid increase of
20%. Subsequently, there is no significant difference between the use and non-use of ultrasound until the
72-second mark. At this point, ultrasound action prompts a swift pH increase over the next 18 seconds,
reaching a stable value. This maintained difference persists over time when ultrasound is not employed.
As the process of oxidation progressed, the increasing pH suggests that the solution released hydroxide
ions (OH-), which contributed to the reduction of another substance. However, this phenomena tends to
be more intense at certain point of the experiments.
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Developing an Ultrasound-based Water Treatment System
(a) (b)
Figure 4.27: Effects of acoustic cavitation on the ORP and pH of ultra-filtered water. (a) The ultrasound
action promotes an exponential decrease over the ORP values and (b) the same action promotes only a
difference on pH after 70 seconds.
Comparing the two cases, ultrasound had different consequences on the ORP and pH behavior. For
ultra-filtrated water, the ability to acquire electrons was higher and was further enhanced by ultrasound.
Additionally, oxygenation increased with ultrasound, as indicated by the rise in ORP, which is associated
with the influx of oxygen into the solution. Combining the increase in ORP with the decrease in pH confirms
that the solution’s oxidative potential is augmented.
The differences in pH and ORP behaviors for the two types of water can be attributed to the availability
of electrons in the solutions. Solutions with more electrons (tap water) will experience a decrease in
electron species (as they are donated to other substances), while solutions with fewer electrons will exhibit
an increase in electron concentration. This, coupled with the fact that the processes shown in Figures 4.26
and 4.27 demonstrate opposite behaviors under ultrasound, suggests that acoustic cavitation accelerates
the rate of natural reactions. This is further supported by the comparison of pH and ORP values with and
without ultrasound use. The graphs exhibit similar behavior, but ultrasound reduces the time taken to
reach the final values.
4.2.2 Ultrasound Impact on Adsorption Processes
Focusing now on the potential enhancement of adsorption through the concurrent application of
ultrasound and mechanical action. This research focus on the removal of both organic and inorganic
pollutants, specifically Ciprofloxacin and Copper. To ensure the robustness of the experiment, ultrasound
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Developing an Ultrasound-based Water Treatment System
and mechanical actions were applied in a staggered manner. The ultimate goal is to conduct a
comparison between the use of ultrasound and mechanical agitation, aiming to gain valuable insights
into the enhancement of adsorption through ultrasound.
Ultrasound action, Figure 4.28 (a) and mechanical action, Figure 4.28 (b), operating at a rotational
speed of 30 revolutions per minute (rpm), were carried out with a time lag between them to validate the
viability of the test. The ultrasound power was meticulously maintained at a consistent level of 65W, with
a permissible deviation of 5 W. This was achieved through a regulated cycle of 15 seconds ”ON” and 15
seconds ”OFF”, allowing precise control over the ultrasound application. The entire experimental duration
was meticulously standardized to 30 minutes. Different containers were used for each equipment due to
their unique characteristics: ultrasound was applied in a beaker, while mechanical action was executed
using a closed bottle.
Figure 4.28: Equipment used for the adsorption tests. (a) Ultrasound with the beaker with the solution
to treat. The beaker is in a water cooling system with a tank with water. (b) Rotational machine for the
mechanical action.
The initial step involved preparing a solution consisting of 500 mL of ultra-filtrated water, 8 mg/L of Cu,
and 2 grams of the organic compound, Nutrimais by Lipor. Subsequently, another solution was prepared,
comprising 500 mL of ultra-filtrated water, 8 mg/L of Cu, and 2 grams of Kaolinite.
To investigate the removal of organic pollutants, solutions were prepared, each containing 500 mL of
ultra-filtrated water, 15 mg/L of Ciprofloxacin, and specific adsorbents. One solution included 2 grams
of the Nutrimais (Organic Compound), while another incorporated 2 grams of Kaolinite. Additionally, a
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Developing an Ultrasound-based Water Treatment System
solution with 500 mL of ultra-filtrated water and 15 mg/L of Ciprofloxacin was prepared as a control
group.
Temperature measurements were recorded to understand their potential effects on the final results.
To enhance the affinity for adsorption, the OC compound and Kaolinite were introduced into the
solutions 30 minutes before the experiment commenced. At the onset of the experiment (minute 0),
reference samples were included for each prepared solution, serving as a baseline for comparison.
Subsequently, samples were extracted at specific time intervals, collected at minute 1, minute 5, minute
15, and minute 30. Notably, for ultrasound collection, no specific downtime was required, whereas, for
mechanical action collection from the bottle, a 1 minute pause was necessary between each collection.
Figure 4.29: Experimental procedure for the adsorption tests. Each experiment has 500 mL of ultra-
filtrated water, pollutant solution and adsorbent. In some cases, the adsorbent is not used. The time
points for the samples removal it were 0, 1, 5, 15 and 30 minutes.
To measure organic and inorganic concentrations, two distinct instruments were employed. For the
measurement of organic concentrations, it was made by the Chemical Engineering laboratory of University
of Minho by HPLC technique. Regarding the analysis of inorganic concentration, it was employed the
Hanna HI83399, a multi parameter photometer. Once that it was used concentrations above 5 mg/L,
it was necessary to dilute the initial solution. The initial solution was diluted in a 50% concentration
solution, with introduction with 50% in volume of ultra-filtrated water. Specific measurement procedures
were followed to obtain accurate readings.
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Developing an Ultrasound-based Water Treatment System
Figure 4.30: Hanna 83300 for the measurement of inorganic pollutants concentration on the samples.
To enhance the efficiency of the adsorption rate, it is crucial to differentiate the analysis for Kaolinite
and Organic Compound. As depicted in Figure 4.31 (a), Ciprofloxacin adsorption after one minute is higher
with mechanical action compared to ultrasound action. With mechanical action, adsorption reaches a
maximum of 66%, whereas with ultrasound, it reaches only 59%. However, it is evident that after 5
minutes, ultrasound-assisted adsorption surpasses mechanical action. Another phenomenon observed is
that ultrasound raises the adsorption threshold. The maximum adsorption rate achieved with Kaolinite
+ US is 71%, while MA + Kaolinite only reaches 68%. In terms of using ultrasound alone, its effects are
negligible, with a maximum removal of only 20%.
When employing Organic Compounds as adsorbents, the Ciprofloxacin removal rate reaches 69% at
the end of one minute with ultrasound assistance. Mechanical Action with Kaolinite only achieves 40%. As
shown in Figure 4.31 (b), the maximum removal rate for this adsorbent under these conditions is attained
with US + OC at the end of one minute, while MA + OC only reaches this level at the end of 15 minutes.
Ultrasound-assisted action significantly enhances the maximum adsorption when combined with both
Kaolinite and Organic Compounds. While MA + Kaolinite results in slightly higher Ciprofloxacin removal
after 1 minute, the difference is only 9%. However, when used alone, ultrasound demonstrates limited
efficacy in Ciprofloxacin removal. This weak performance of ultrasound aligns with existing literature,
which indicates that while sonochemistry can initiate oxidative processes, it may not lead to substantial
mineralization abilities [166]. Mineralization or removal needs to be facilitated by other AOPs processes
or adsorption [166].
Regarding temperature variations during the ultrasound process, there is an immediate increase
upon ultrasound application. After one minute, the temperature rises by 2ºC, and after 10 minutes, it
increases by approximately 8 ºC. While temperature may play a role in Ciprofloxacin removal, it is likely
not substantial, as the increase after one minute is only 2 ºC, and yet the removal rate reaches its
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Developing an Ultrasound-based Water Treatment System
maximum. Moreover, the removal rate does not experience a significant increase with ultrasound
application alone, even though the temperature rises by over 10 ºC by the end of the experiment.
(a) (b)
Figure 4.31: Ciprofloxacine removal rate and it temperature during the exposition time, combining the
ultrasound with (a) Kaolinite and with (b) Organic Compound.
In terms of utilizing ultrasound to enhance adsorption of heavy metals, we evaluated its combined use
with Kaolinite and Organic Compounds. As depicted in Figure 4.32 (a), Kaolinite does not demonstrate
effective behavior when combined with either Ultrasound or Mechanical Action. Specifically, Mechanical
Action assistance only yielded a 12% removal rate after one minute, while US + Kaolinite achieved only
4%. Ultrasound did not lead to an improvement in the removal rate, and similar to mechanical action (MA
+ Kaolinite), the rate remained above 20%, indicating a low removal potential. The sudden exponential
increase to 77% removal rate by US + Kaolinite after 15 minutes, following a period of constant stability
around 5%, suggests a potential error in the process.
However, when combined with Organic Compounds, Ultrasound significantly enhances the removal
rate, as shown in Figure 4.32 (b). After one minute, the removal reaches 82%, and it reaches a maximum
of 86% after 5 minutes, maintaining this level thereafter. This implies that within just 5 minutes, the
adsorbent reaches its maximum adsorbent rate, and after 1 minute, it has adsorbed 95% of its maximum
capacity. Conversely, MA + OC only achieves a 19% Copper removal rate after one minute, and even after
30 minutes, the removal rate continues to increase, reaching up to two-thirds of the maximum adsorbent
rate of US + OC.
In accordance with the findings detailed in the investigation conducted by Gupta et al. [88], the
synergistic application of ultrasound treatment and adsorption demonstrates a pronounced
enhancement in the adsorption kinetics. Notably, the accelerated rate of adsorption is evidenced by
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Developing an Ultrasound-based Water Treatment System
achieving an 80% removal efficiency within the initial minute of treatment, ultimately culminating in the
attainment of maximum removal efficiency after a 5-minute duration.
As observed in the case of Ciprofloxacin, the temperature follows a similar pattern as before. It does
not appear to have a significant impact on Copper removal, as the temperature increase is not followed
by an increase in pollutant concentration in the US + Kaolinite system. Moreover, in US + OC, the rapid
increase in removal rate is not accompanied by a similar temperature increase.
(a) (b)
Figure 4.32: Copper removal rate during the 30 minutes exposition time, combining the ultrasound with
(a) Kaolinite and with (b) Organic Compound.
4.3 Insights from the Experimental Analysis
The experimental data obtained from the aforementioned tests provides valuable insights into the
functionality of ultrasound in water and its associated impacts. Table 4.2 presents the key findings from
the chamber sensorization. The study involved the evaluation of three sensors: Sensor 1, 2 and Sensor 3
in two different chamber positions. Calibration’s equations were established, revealing distinct responses
to applied forces. Sensor 2 and 3 exhibited signs of wear after exposure to cavitation, in contrast to
Sensor 1 which remained unaffected.
Cavitation threshold assessments indicated that Sensor 1 and Sensor 3 share similar ranges, and
the cavitation was detected. Notably, the cavitation threshold comparing Position 1 and 2, show different
results. This offers a valuable insight into the cavitation pattern within the chamber, indicating that it is
not a linear phenomenon over time and position.
The noise equations revealed consistent patterns for Sensor 1 and Sensor 3, providing information on
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Developing an Ultrasound-based Water Treatment System
the levels of noise detected by these sensors, and the possible sources of it. The maximum peak cavitation
force on the sensors reached 15.25 N at position 2 and 12.25 N at an alternate position.
Table 4.2: Insights provided by the data analysis from the chamber sensorization.
Parameters Sensor 1 Sensor 2 Sensor 3
Equation of Calibration P1 V=−0.28 + 0.04 ·F V =−.20 + .04 ·F-
Wear after cavitation No Yes Yes
Cavitation threshold - P1 [410±10 ; 500±10] W - [410±10 ; 500±10] W
Cavitation threshold - P2 [500±10 ; 600±10] - [600±10 ; 700±10]
Noise Equation Fn
P eak = 15,000 + f·n-Fn
P eak = 15,000 + f·n
Maximum Impact Load - P1 - - 12.25 N
Maximum Impact Load - P2 - - 15.25 N
In Table 4.3, a comprehensive examination of experimental outcomes is presented, outlining the
effects of Ultrasound on different water types. Both Ultra-Filtrated and Tap waters underwent Ultrasonic
treatment, allowing for the measurement of pH and ORP values. Upon subjecting Ultra-Filtrated water to
Ultrasound, ∆ORP displayed a significant alteration, indicating a speed ratio of 2.52 at 18 seconds,
subsequently reducing to 1. Similarly, ∆pH exhibited a change from 2.29 at 18 seconds to a steady
state of 1.
Conversely, in the case of Tap water, data for ∆ORP at 18 seconds was unattainable due to its
inherently unpredictable behavior. Post the initial 18 seconds, Ultrasound application elicited a distinct
variation as described by the function −0.3·t−1.9, while the non-Ultrasound condition demonstrated
negligible change. Meanwhile, ∆pH remained relatively stable, with an initial reading of 1.2 at 18
seconds persisting through subsequent time intervals.
Table 4.3: Insights provided by the data analysis from the application of Ultrasound on water.
Water Type Parameters
Acquisition time point
Notes
18 s ]18;160] s
Ultra-Filtrated ∆ORP 2.52 1 -
∆pH 2.29 1
Tap ∆ORP - −0.3·t−1.9Just US provokes alteration on ORP
∆pH 1.2 1
Speed Comparison
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Developing an Ultrasound-based Water Treatment System
In the context of adsorption enhanced by ultrasound, Table 4.4 offers a comparative analysis of
pollutant removal efficiency achieved through ultrasound and mechanical action treatments using various
adsorbents.
Initially, ultrasound exhibited a notable impact within the first minute of application, particularly in
augmenting the adsorption of organic compounds. However, after this initial period, the results with
Kaolinite were less compelling. Mechanical action only slightly suppressed the removal of CIP, resulting
in a removal efficiency of only 60%. Nonetheless, it’s worth noting that there was an observable increase
in maximum removal with the application of ultrasound. As for the removal of Cu, the results indicated
insufficient removal rates.
Turning our attention to the Organic Compound adsorbent, ultrasound treatment demonstrated
impressive results, achieving a 69% removal of CIP within the first minute, surpassing the performance of
Kaolinite. This superiority in removal efficiency extended to the maximum pollutant removal.
Regarding Cu removal, ultrasound combined with the Organic Compound adsorbent achieved
remarkable rates, reaching 82% in the first minute and a maximum removal of 86%. In contrast,
mechanical action yielded significantly lower rates of 19% and 58%.
It is important to highlight that ultrasound alone did not lead to any considerable alteration in removal
efficiency.
Table 4.4: Insights provided by the data analysis from the aplication of Ultrasound with adsorption
processes.
Adsorbent Pollutant
Ultrasound Mechanical Action
1 min Max removal 1 min Max removal
Kaolinite CIP 60 % 72% 66% 69%
Cu 3% 76% 12% 20%
Organic Compound CIP 69% 74% 40% 69%
Cu 82% 86% 19% 58%
- CIP 12% 20% - -
Pollutant Removal
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Developing an Ultrasound-based Water Treatment System
5. Performance Assessment on a Wastewater Treatment Plant
To evaluate the efficacy of the assisted ultrasound system in wastewater treatment, a comprehensive
experimental study was conducted. This chapter outlines the experimental setup, methodology employed
during the experiment, and the subsequent results obtained from the treatment process. Finally, the
chapter concludes by presenting the key findings derived from the analysis of chemical and physical
parameters.
5.1 Experimental Conditions and Setup
The experimental test took place at Serzedo’s ETAR, wastewater treatment plant, and was collected treated
wastewater from the secondary decanter. The equipment installed contemplated the ultrasound (ultrasonic
device and respective chamber) and an air compressor in order to cool the transducer. To ensure that
the humidity produced by the air compressor does not damage the transducer, it was used an air filter,
Festo MS-LFR-B. Ultrasound management was made using the proper software that allows control every
parameter from the ultrasonic wave.
Figure 5.1: Experimental Setup for Ultrasound Cleaning in ETAR of Serzedo. The ultrasound unit is linked
to both the power supply and a computer for system control. The transducer is cooled using compressed
air supplied by an air compressor.
For evaluating the effects of the acoustic cavitation on the wastewater, it was defined 3 different
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Developing an Ultrasound-based Water Treatment System
acoustic power and 5 different collection points. The different acoustic power values were 200 W, 400 W
and 800 W. These are the variable conditions which allow evaluating the effect of the ultrasound in water at
different power values. The collection points were 2, 5, 10 and 20 minutes, being that at zero time, it was
measured the initial conditions. In order to evaluate the effects, were selected 12 different parameters:
chemical oxygen demand, total Nitrogen, Phosphate, Ammonium, Nitrate Nitrogen, total suspended solids,
pH, ORP, dissolved Oxygen, electrical conductivity, total dissolved solids and temperature.
The measurement was made in two different phases. A 500 mL beaker is used at each collection point,
and subsequently, the collected sample is subjected to instant measurements using the multi-parameter
HANNA HI98494. After the measurement of pH, ORP, dissolved Oxygen, electrical conductivity, TDS
and temperature, was separated a 80 mL sample to posterior laboratory analysis of COD, total Nitrogen,
PO4
−, N−NH4+and N−NO3
−. The other 420 mL were put back in the chamber, and the time between
the collection procedure and the restart of the acoustic cavitation was established as 1 minute.
Figure 5.2: Experimental Study Scheme with Real Wastewater: A 500 mL sample is collected at 0, 2,
5, 10, and 20 minutes, followed by analysis using the HANNA HI98494. An 80 mL sample is extracted
from the initial 500 mL for subsequent laboratory testing, while the remaining solution is returned to the
chamber.
At the outset of the experimental tests, initial values for the wastewater were measured. The initial
conditions for wastewater obtained from the secondary decantation process are presented in Table 5.1. It
is imperative to thoroughly elucidate each initial sample corresponding to the respective power level. The
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Developing an Ultrasound-based Water Treatment System
collected wastewater from the secondary decantation process comprised a 20 L sample.
Table 5.1: Physical and Chemical Parameters of Wastewater Before the Ultrasound Assisted Treatment
with each Different Power.
Power (W) Power (W)
Parameters 200 400 800 Parameters 200 400 800
CQO (mg/L)
25.9 13.1 46.8
pH
7.47 7.47 7.47
N
total
(mg/L)
2.67 2.39 3.05
ORP (mV)
14.9 14.9 14.9
PO
4
−
(mg/L)
2.3 2.21 2.24
DO (mg/L)
2.89 2.89 2.89
N
−
NH
4+
(mg/L)
0.593 0.642 0.632
Conductivity (
µ
S/cm)
2445 2445 2445
N
−
NO
3
−
(mg/L)
0.245 0.256 0
TDS (mg/L)
1222 1222 1222
SST (mg/L)
<7 <7 <7
Temperature (°C)
20.78 20.78 20.78
5.2 Analysis of Ultrasound Treatment Effects on Wastewater
Parameters
Table 5.2 displays the variations in variables throughout the study, considering different acoustic
intensities. Beginning with the variables that showed no variation, it is evident that Electrical Conductivity,
Total Dissolved Solids, and Total Suspended Solids remained constant over time. The limited fluctuations
in the latter two variables can be attributed to their low presence in the wastewater post-secondary
decantation. Consequently, the subsequent analysis will concentrate on the remaining parameters.
Table 5.2: Physical and chemical parameters for the wastewater treated with ultrasound along the
experimental test. Parameters at 0, 2, 5, 10 and 20 minutes.
Power (W)
Parameters 200 400 800
Time (min) 0 2 5 10 20 0 2 5 10 20 0 2 5 10 20
COD (mg/L)
25.9 26.1 44.9 55.9 63.9 13.1 37 42.5 46.3 60.6 46.8 39.1 44.6 47.5 61.4
N
total
(mg/L)
2.67 2.84 3.23 4.1 3.08 2.39 3.12 3.64 2.95 3.59 3.05 3.98 3.15 3.39 4.87
PO
−
4
(mg/L)
2.3 2.25 2.29 2.24 2.31 2.21 3.21 2.77 2.81 4.13 2.24 2.25 2.3 2.31 2.4
N
−
NH
+
4
(mg/L)
0.593 0.653 0.353 0.701 0.725 0.642 0.682 0.68 0.687 0.717 0.632 0.639 0.631 0.628 0.662
N
−
NO
−
3
(mg/L)
0.245 0.144 0.208 0.193 0.281 0.256 0.196 0.223 0.233 0.254 0 0.246 0.181 0.206 0.196
pH
7.47 7.04 7.42 7.52 7.44 7.47 7.57 7.53 7.49 7.32 7.47 7.65 7.58 7.47 7.42
ORP (mg/L)
14.9 86 56.4 41.5 27.4 14.9 25.9 33.5 27.4 16.9 14.9 20.9 22.6 19.5 11.1
DO
2.89 4.99 4.29 4.23 3.76 2.89 4.53 4.24 4.04 3.65 2.89 4.8 4.55 4.25 3.88
Conductivity (
µ
S/cm)
2445 2403 2452 2482 2543 2445 2451 2471 2497 2544 2445 2440 2450 2494 2537
TDS (mg/L)
1222 1205 1226 1242 1272 1222 1228 1235 1249 1272 1222 1220 1225 1247 1270
Temperature (ºC)
20.78 22.2 26.04 31.65 41.09 20.78 24.64 28.41 34 43.42 20.78 24.4 28.45 33.77 43.48
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Developing an Ultrasound-based Water Treatment System
Regarding pH and ORP, which serve as indicators of chemical reactions, Figure 5.3 illustrates distinct
behaviours in the initial two minutes. During this period, ORP experiences a rapid increase, while pH
exhibits the opposite trend. Subsequently, between 2 and 5 minutes, a reversal of reactions is observed:
pH increases rapidly, while ORP decreases, albeit at a slower rate. This trend of ORP decline persists until
the conclusion of the experiments, mirroring the pH’s behaviour but in the opposite direction. Ultimately,
after 20 minutes, the values return to their initial states.
In contrast, Figure 5.3 demonstrates that Temperature shows a nearly linear increase over the 20-
minute duration. Conversely, Dissolved Oxygen undergoes relatively minor changes. Similar to pH and
ORP, it appears that the cavitation effect is most pronounced within the initial 2 minutes, after which the
values gradually revert back to their initial states.
The rise in pH indicates that ultrasound generates more hydroxide ions, resulting in fewer hydrogen
ions and an abundance of hydroxide ions. This shift leads to an environment with higher levels of oxidizing
species, augmenting the solution’s oxidant potential. However, the ORP variation suggests a decreased
likelihood of electron transfer reactions occurring and a reduced probability of oxidation reactions taking
place.
After the initial 2 minutes, the capacity to generate additional hydroxide ions diminishes, leading to a
pH decrease followed by an ORP increase. The elevated ORP signifies that the solution gains a heightened
ability to accept electrons. With the reduction of hydroxide ions, the reactive species become more available
to undergo oxidation, accepting electrons. This behaviour implies that ultrasound exerts a substantial effect
initially but lacks the sustained power to mineralize additional pollutant species [167].
(a) (b)
Figure 5.3: Variation of parameters that are indicators of chemical reactions on wastewater treatment with
application of a acoustic power of 200 W. (a) pH and ORP (b) Temperature and Dissolved Oxygen.
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Developing an Ultrasound-based Water Treatment System
In reference to COD removal, as depicted in Figure 5.4, there is no discernible reduction; rather, an
increase in COD concentration is observed. In the initial two minutes, the value remains stable. However,
from minute 2 to 10, there is a notable and steep incline. In the final 10 minutes, this rate of increase
decreases, resulting in a flatter trajectory compared to the preceding period. Over the course of the first
to last minute, the COD concentration rises from 26 mg/L to 64 mg/L.
Figure 5.4: COD removal with application of a acoustic power of 200 W.
Focusing on other chemical parameters, Ammonium Nitrogen (N−NH+
4) exhibits an initial increase
within the first 2 minutes and between the tenth and last minute, as shown in Figure 5.5 (a). However,
after 5 minutes, the concentration experiences an abrupt fluctuation, suggesting a potential error in this
data point. Generally, the Ammonium Nitrogen concentration shows a slight overall increase, while Nitrate
Nitrogen (N−NO−
3) displays subtle fluctuations over time, ultimately returning to its initial value.
The rise in Ammonium Nitrogen may be correlated with a decrease in Ammonia levels. This increase
could be attributed to the chemical conversion of Ammonia to Ammonium, a less toxic compound.
Additionally, the elevated Ammonium Nitrate levels might be linked to an intensified decomposition of
organic matter.
As for Nitrate Nitrogen, the minimal variation may be attributed to low levels of dissolved oxygen.
In such circumstances, the reduced concentration diminishes nitrification efficiency, resulting in a less
effective biological nutrient removal (BNR) process and consequently higher ammonium concentrations
in the effluent. Notably, Dissolved Oxygen, Figure 5.3, shows no significant alteration throughout the
experiment, aligning with the stable trends observed in both Ammonium Nitrate and Nitrate Nitrogen
concentrations.
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Developing an Ultrasound-based Water Treatment System
Comparing Total Nitrogen and Phosphate, Phosphate demonstrates a linear increase from 2.7 mg/L
to 4.1 mg/L over 10 minutes, followed by a subsequent decrease of 3 mg/L. In contrast, akin to Nitrate
Nitrogen, Phosphate maintains a consistent value throughout the entire experiment, exhibiting no
substantial variations, Figure 5.5.
The increase in Total Nitrogen could be attributed to various factors. This rise might be linked to the
incomplete oxidation of nitrogen compounds, or the transformation of nitrogen species into other forms.
(a) (b)
Figure 5.5: Variation of parameters that are indicators of chemical reactions and biological and organic
reaction along wastewater treatment with application of a acoustic power of 200 W. (a) N−NH −
4and
N−NO−
3(b) Ntotal and P O−
4.
With an increase in acoustic power to 400 W, both pH and ORP exhibit different behaviours compared
to the 200 W setting. In contrast to the previous observation, where pH and ORP consistently changed
in opposite directions, here both parameters follow similar patterns. ORP increases until the fifth minute,
while pH peaks at the second minute, after which both values decline. In this case, it appears that
ultrasound exerts a more prolonged influence, as pH decreases to levels below the initial ones. However,
ORP tends to stabilize back to the initial values after the initial increase (see Figure 5.6).
This combined increase and subsequent decrease suggests that, at 400 W, the solution is conducive
to oxidation processes within the initial two minutes. However, once the cavitation ceases to promote the
formation of more hydroxide ions, the system’s oxidation potential substantially decreases.
Temperature continues its linear increase, mirroring the trend observed at 200 W. Dissolved Oxygen, on
the other hand, exhibits the same initial increase in the first two minutes followed by a decline. Comparing
the results to those at 200 W (see Figure 5.5 and Figure 5.6), it is evident that Dissolved Oxygen increases
between 0 and 2 minutes and then subsequently decreases. Elevating the ultrasound power intensity
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Developing an Ultrasound-based Water Treatment System
further accentuates this trend, leading to a higher concentration of Dissolved Oxygen at its peak.
(a) (b)
Figure 5.6: Variation of parameters that are indicators of chemical reactions on wastewater treatment with
application of a acoustic power of 400 W. (a) pH and ORP (b) Temperature and Dissolved Oxygen.
In terms of COD removal, there is no initial stabilization as observed at 200 W. Instead, there is
a notable surge within the first two minutes, marking the most significant increase during this period.
However, this increase continues steadily, displaying a linear progression after the second minute. From
the initial moment to the conclusion, the COD concentration rises from 12 mg/L to 60 mg/L. This trajectory
mirrors the behaviour observed at 200 W, as depicted in Figure 5.7.
Figure 5.7: COD removal with application of a acoustic power of 400 W.
Similar to the effects observed at 200 W ultrasound power, there is a notable increase in Ammonium
concentration within the first two seconds, while for Nitrate Nitrogen, the opposite effect occurs, resulting
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Developing an Ultrasound-based Water Treatment System
in a decrease. This trend continues after the initial two minutes, with Ammonium concentration steadily
increasing, albeit at a slower rate, and Nitrate Nitrogen returning to its initial value. Comparing the
variations in these parameters between 200 W and 400 W applications (Figure 5.5 (a) and Figure 5.5
(a)), it’s evident that the overall behaviour is similar. Ammonium experiences notable growth, particularly
in the initial two seconds. As for Nitrate, there’s a significant decrease in the first two seconds followed
by a subsequent increase until it reaches the initial value.
Turning to Total Nitrogen and Phosphate, both exhibit similar patterns, showing significant increases
in the initial two minutes (Figure 5.8 (b)). Comparing this to Figure 5.5 (b), it’s apparent that at 400 W
acoustic power, the peak in Total Nitrogen occurs earlier, shifting from 10 minutes to 5 minutes, and also
induces an increase in Phosphate, which was not observed at 200 W.
(a) (b)
Figure 5.8: Variation of parameters that are indicators of chemical reactions and biological and organic
reaction along wastewater treatment with application of a acoustic power of 400 W. (a) N−NH −
4and
N−NO−
3(b) Ntotal and P O−
4.
Similar to the trends observed in Figure 5.6 (a), both pH and ORP exhibit very similar behaviours over
time for acoustic powers of 400 W and 800 W, as shown in Figure 5.9 (a). At 800 W power, both pH and
ORP values experience significant increases in the initial two minutes. However, while ORP reaches its
maximum value at 5 minutes and then decreases, pH starts decreasing after the second minute. When
compared with the other power levels, it’s notable that at 800 W, the ORP value experiences a more
pronounced decrease from the initial value.
Temperature maintains the anticipated behaviour as seen previously, and Dissolved Oxygen
concentration confirms the established pattern of an initial increase in the first two minutes, followed by
a subsequent decrease. In this case, the final value still remains above the initial one (Figure 5.9 (b)).
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Developing an Ultrasound-based Water Treatment System
(a) (b)
Figure 5.9: Variation of parameters that are indicators of chemical reactions on wastewater treatment with
application of a acoustic power of 800 W. (a) pH and ORP (b) Temperature and Dissolved Oxygen.
In contrast to the previous COD concentration observations, at 800 W of acoustic power, there is a
decrease in COD concentration in the initial two minutes. Subsequently, there is a gradual increase until
the 10-minute mark. From that point on, the increase becomes more pronounced, extending until the
conclusion of the experiment (see Figure 5.10).
Figure 5.10: COD removal with application of a acoustic power of 800 W.
At 800 W, Ammonia exhibits a behaviour similar to that demonstrated at an intensity of 400 W. It’s
evident that there is a rapid increase in the first minute, followed by a slight decrease, and then another swift
increase (Figure 5.11). However, the pattern for Nitrate Nitrogen is opposite. Nitrate Nitrogen experiences
a substantial increase in the first two seconds, after which its concentration remains constant over time.
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Developing an Ultrasound-based Water Treatment System
Similar to the observations at 200 W and 400 W power levels, the peak of Total Nitrogen occurs earlier
than in the other cases, manifesting in the second minute. Following this peak, the behaviour decreases
before increasing again. On the other hand, in line with the concentration of Phosphorous for 200 W and
400 W, ultrasound action leads to an increase in this chemical concentration (see Figure 5.11).
(a) (b)
Figure 5.11: Variation of parameters that are indicators of chemical reactions and biological and organic
reaction along wastewater treatment with application of a acoustic power of 800 W. (a) N−NH −
4and
N−NO−
3(b) Ntotal and P O−
4.
It is evident that most significant modifications occur within the initial two minutes. During this time
frame, chemical parameters experience notable increases or decreases. Subsequently, there is a tendency
for the values to revert back to their initial states. This suggests that the primary impact of acoustic
cavitation occurs in the initial minutes, after which the effects begin to dissipate.
In terms of COD concentration, two distinct behaviours are observed. At 200 W and 800 W, the
concentration stabilizes or decreases in the first two minutes, followed by a subsequent increase. However,
this trend is not observed at 400 W, where COD increases rapidly in the first two minutes.
These results deviate from what is typically expected based on the literature [94–96]. However, they
could be related to phenomena mentioned in the same references. For instance, in the wastewater
treatment of pharmaceutical wastewater, a maximum removal efficiency of 8% at 30 minutes was
reported with ultrasound at an amplitude of 20% and a solution pH of 5. In another study on the tertiary
treatment of treated municipal wastewater, a maximum COD removal of 35% was achieved after 30
minutes. Throughout the process, no negative removal rates were observed. Nevertheless, upon
analysing the removal of organic compounds, it was noted that the concentration of two organic
components increased. Similar observations were made by other authors, suggesting that this
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Developing an Ultrasound-based Water Treatment System
phenomenon is attributed to the presence of organic pollutants adsorbed on suspended solids. The
physical action of ultrasound induces the size reduction of solids, releasing absorbed pollutants. This
could be the mechanism responsible for the increase in COD during ultrasound application.
The varying responses across different ultrasound powers may be attributed to the ultrasound’s
incapacity to effectively degrade and mineralize the pollutants [167]. The variation in COD across
different power levels suggest two mechanisms. The first involves degradation induced by ultrasound,
while the second involves the separation of organic compounds from the solids present in water. In the
initial moments, ultrasound possesses sufficient power to degrade and mineralize organic compounds.
At 200 W, the ultrasound lacks the power to entirely counteract the emission of organic compounds from
solids, resulting in an equilibrium between the two phenomena. However, at 800 W, when ultrasound
has more power, the COD concentration decreases. Subsequently, as it reaches the threshold for
organic compound degradation and mineralization, the COD starts to increase again.
At 400 W, no degradation occurs, which suggest that ultrasound has minimal effect at this power
level, or the wastewater sample contains more organic pollutants associated with solids. Comparing
the variations in Figure 5.12, it is apparent that the wastewater solution at 400 W has the lowest COD
concentration, implying that organic compounds may be more prevalent on the walls of solids.
Another piece of evidence supporting this is that even though the experiments start with different initial
COD concentrations, the final values converge to similar levels. This indicates that ultrasound increases
the separation between organic compounds and the walls of solids, leading to an increase in isolated
organic compounds in the water.
Another noteworthy phenomenon that may significantly influence the observed effects is the
concurrent increase in temperature during cavitation. As illustrated in Figure 5.3 (a), Figure 5.6 (b), and
Figure 5.9 (c), the temperature exhibits a rising trend over time. Bagal et al. [10] have reported that the
cavitation phenomenon is particularly favored within a temperature range of 25-30 ºC.
It is essential to consider the impact of temperature on the overall process, as several studies, including
those by Bagal et
al.
[10], highlight that the efficiency of pollutant degradation tends to decrease with
increasing temperatures. Certain investigations emphasize that pollutant degradation is more efficient at
temperatures below 30 ºC than at higher temperatures [18, 126, 129]. Consequently, the temperature
variation could potentially play a crucial role in the removal rate, with higher temperatures potentially
contributing to a reduction in overall efficiency.
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Developing an Ultrasound-based Water Treatment System
Figure 5.12: COD removal comparison for the three powers of 200 W, 400 W and 800 W.
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Developing an Ultrasound-based Water Treatment System
6. Conclusions
6.1 Piezoelectric Sensor for Cavitation Characterization
The sensors developed in this dissertation successfully met the initially outlined objectives. Alongside their
physical development, a real-time monitoring program was created to collect and process cavitation data.
The piezoelectric sensors exhibited low resistance to cavitation when not used with a protective resin
layer. In this case, one of the unprotected piezoelectrics was damaged, rendering it inoperative. On the
other hand, the piezoelectric with the epoxy layer showed no associated damage. However, the same
studies demonstrate that the 0.2mm layer hinders the ultrasound from having similar sensitivity to the
others. During sensor calibration, it was confirmed that the presence of this thickness of layer limits
sensitivity in readings, preventing its calibration.
Sensorization of the ultrasonic chamber allowed the conclusion that acoustic cavitation near the sensor
occurred around 500 W. However, it was also verified that this value could vary depending on the sensor’s
position. This aligns with what is visually observed, where it is possible to identify that cavitation and
acoustic streaming vary along the acoustic radiator and over time.
Monitoring of acoustic cavitation was performed through both subharmonic readings and FFT graph
readings of the data acquired by the sensor. Both methods allowed for establishing a relationship between
the increase in power and the onset and increase of acoustic cavitation. The existence of this phenomenon
ensures that the current dimensions of the ultrasound equipment are in accordance with what is expected.
In addition to characterization through harmonic readings, a relation was also established between
the potential difference generated by the piezoelectrics and the force to which the sensor is subjected. In
this case, the sensors were able to provide a reading of the force resulting from cavitation.
During the development of this sensor, one of the main questions was whether modifying its geometric
and physical properties would significantly influence the resonance frequency. In this case, the resonance
frequency after final geometry and the placement of the epoxy protective layer revealed that there are
no significant differences in these. However, it is important to note that in the second case, there is a
new resonance above the natural frequency. However, as it does not imply major differences in the final
reading, it can be considered that in this case, modifying the original sensor does not entail considerable
consequences.
Regarding the immersion level of the ultrasound in water, the results show that the maximum
immersion limit should be, at most, below 200 mm. Above this value, the resonance frequency varies
considerably.
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Developing an Ultrasound-based Water Treatment System
6.2 Assessment of Impacts of Ultrasound on Wastewaterw
Ultrasound proves to accelerate chemical reactions and bolstering radical presence, including H2O2and
H+. In the initial stages, its effects are notably pronounced. For instance, in ultra-filtered water, within
20 seconds, ultrasound leads to a 1.5-fold increase in ORP and a 2.29-fold surge in pH compared to
no action. In tap water, ultrasound causes a continuous ORP reduction, while without action, it remains
unchanged. These results affirm ultrasound’s potential in expediting oxidative processes, particularly in
the early stages.
In adsorption processes, ultrasound showcasing notable effectiveness. Within 1 minute, ultrasound
matches the Ciprofloxacin adsorption capacity with Kaolinite achieved by mechanical action. However,
with Organic Compound, ultrasound demonstrates a removal rate 1.75 times faster. For Copper removal,
ultrasound, applied with kaolinite, yields similar results, but with the Organic Compound, it boasts a
removal rate 4.3 times higher. This acceleration is confined to the first minute, where ultrasound propels
adsorption to its limit. This highlights ultrasound’s significant potential, especially in initial stages.
Results pertaining to adsorption also suggest that ultrasound amplifies the adsorption rate of an
adsorbent. Post-stabilization, it is evident that ultrasound’s maximum adsorption value surpasses that
achieved through mechanical action. The combined effect of accelerated adsorptive processes and the
potential increase in maximum adsorption capacity underscores ultrasound’s substantial promise.
When applied to wastewater, ultrasound exerts notable influence across various phases, with the most
significant impact occurring initially. Generally, ultrasound’s significance wanes after the initial action, as
parameters revert to their baseline values. This observation underscores ultrasound’s potential in driving
mechanical actions that trigger chemical reactions.
Notably, ultrasound’s application leads to the disintegration of organic substances previously adhered
to solids. This holds immense potential, as the separation of organic compounds from solids paves the
way for easier mineralization. This phenomenon is closely tied to the variation in COD during testing.
Moreover, higher applied power leads to greater initial degradation of organic compounds in the solution,
after which they begin to increase. Beyond the cavitation threshold (identified at 500 W), ultrasound
significantly impacts COD reduction, aligning with expectations.
In assessing other parameters like temperature, it is evident that its influence is minimal, both in
laboratory tests and within WWTP contexts. However, temperature elevation does impact ultrasound
efficiency, warranting efficient cooling measures for continuous operation.
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Developing an Ultrasound-based Water Treatment System
6.3 Future Works
Through the analysis of the obtained results, key areas for future equipment development have come to
light. Starting with sensors, an essential step is to delve into the study of the minimum protective layer
required. This layer aims to shield the sensor from cavitation while ensuring it remains sensitive enough
for accurate cavitation characterization.
Having validated the functionality of the sensors, it is now imperative to explore the maximum feasible
size for the chamber. This investigation aims to investigate the maximum possible diameter where still
exist cavitation. In connection with piezoelectric sensors, the utilization of signal acquisition equipment
with higher resolution is recommended for future endeavours. The existing equipment falls short in reading
interferences below 12 µs, hindering proper sensor calibration and comprehension of bubble effects. This
necessity is underscored by the proven requirement for comprehensive chamber monitoring, necessitating
multiple sensors and a higher sample acquisition rate.
Following chamber sensorization, the adoption of smaller sensors becomes imperative for seamless
accommodation within the chamber. This undertaking involves an exploration of new sensors, compact
yet operating on a similar principle. At the same time it is important to develop a temperature monitoring
system to regulate the temperature inside the chamber. While current equipment has cooling channels,
continuous temperature monitoring ensures water flow for cooling is initiated only when necessary.
Regarding to cavitation impact on water, it is necessary to develop an incremental introduction of
diverse solid and chemical substances is essential for evaluating Ultrasound’s impact on these elements.
The present work presents two potential paths for equipment evolution. The first path integrates
ultrasound for pollutant adsorption acceleration and optimization. This necessitates tests to validate
ultrasound’s efficacy in the initial minute and determine the minimum exposure time for maximum
adsorption. Additionally, exploring new adsorbents and assessing their adsorption capacities, with and
without ultrasound application, is vital.
Conversely, the alternative path envisions equipment tailored to water treatment, combining ultrasound
with other AOPs. Given ultrasound’s limitations in fully eradicating organic pollutants, coupling it with
processes like Ozone, Fenton, and H2O2for enhanced mineralization is proposed. Understanding the
requisite minimum concentrations, actual benefits of ultrasound use, and the distribution of degraded
pollutants post-mineralization are paramount for this equipment’s development. This insight will guide
subsequent steps and procedures for degraded pollutant elimination.
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Developing an Ultrasound-based Water Treatment System
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Appendix A - Piezoelectric Datasheet
The piezoelectric sensor was manufacture by the Hangzhou Altrasonic Technology Co., Ltd. that
provided the sensor parameter table present on Figure A.1.
Figure A.1: Data-sheet of the piezoelectric device provided by the manufacturer.
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Appendix B - Calibration Extended Data of Sensors 2 and 3
Table B.1: Experimental data of sensor 2 and corresponding calibration results with the 0.30 g sphere.
∆t(µm)V(V)h2(mm)h1(mm)v1(m/s)v2(m/s)m(kg)Favg(N)
36 0.43 18 50 0.99 0.59 0.30 13.43
36 0.42 20 50 0.99 0.63 0.30 13.70
36 0.43 15 50 0.99 0.54 0.30 12.99
36 0.40 16 50 0.99 0.56 0.30 13.14
36 0.45 17 50 0.99 0.58 0.30 13.28
36 0.80 45 100 1.40 0.94 0.30 19.83
36 0.80 45 100 1.40 0.94 0.30 19.83
36 0.75 43 100 1.40 0.92 0.30 19.65
36 0.78 43 100 1.40 0.92 0.30 19.65
36 0.75 42 100 1.40 0.91 0.30 19.56
36 0.91 48 170 1.83 0.97 0.30 23.69
36 0.90 47 170 1.83 0.96 0.30 23.61
36 0.96 49 170 1.83 0.98 0.30 23.78
36 0.97 46 170 1.83 0.95 0.30 23.52
36 0.93 50 170 1.83 0.99 0.30 23.86
36 1.25 54 270 2.30 1.03 0.30 28.22
36 1.23 50 270 2.30 0.99 0.30 27.89
36 1.24 54 270 2.30 1.03 0.30 28.22
36 1.21 48 270 2.30 0.97 0.30 27.72
36 1.22 48 270 2.30 0.97 0.30 27.72
36 1.40 53 370 2.69 1.02 0.30 31.47
36 1.48 63 370 2.69 1.11 0.30 32.25
36 1.41 54 370 2.69 1.03 0.30 31.55
36 1.48 65 370 2.69 1.13 0.30 32.39
36 1.45 58 370 2.69 1.07 0.30 31.86
36 1.64 65 500 3.13 1.13 0.30 36.10
36 1.69 62 500 3.13 1.10 0.30 35.88
Continued on next page
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Table B.1 – continued from previous page
∆t(µm)V(V)h2(mm)h1(mm)v1(m/s)v2(m/s)m(kg)Favg(N)
36 1.66 68 500 3.13 1.16 0.30 36.32
36 1.65 66 500 3.13 1.14 0.30 36.18
36 1.65 64 500 3.13 1.12 0.30 36.03
Table B.2: Experimental data from sensor 2 and corresponding calibration results with the 2.02 grams
sphere.
∆t(µm)V(V)h2(mm)h1(mm)v1(m/s)v2(m/s)m(kg)Favg(N)
60 1.46 12 50 0.99 0.49 2.02 49.68
60 1.46 13 50 0.99 0.51 2.02 50.35
60 1.49 14 50 0.99 0.52 2.02 50.99
60 1.45 12 50 0.99 0.49 2.02 49.68
60 1.42 10 50 0.99 0.44 2.02 48.26
60 1.46 12 50 0.99 0.49 2.02 49.68
60 1.46 13 50 0.99 0.51 2.02 50.35
60 1.49 14 50 0.99 0.52 2.02 50.99
60 1.45 12 50 0.99 0.49 2.02 49.68
60 1.42 10 50 0.99 0.44 2.02 48.26
60 4.12 50 170 1.83 0.99 2.02 94.83
60 4.17 45 170 1.83 0.94 2.02 93.12
60 4.25 48 170 1.83 0.97 2.02 94.16
60 4.10 48 170 1.83 0.97 2.02 94.16
60 4.15 52 170 1.83 1.01 2.02 95.49
Table B.3: Experimental data from sensor 2 and corresponding calibration results with the 0.88 grams
sphere.
∆t(µm)V(V)h2(mm)h1(mm)v1(m/s)v2(m/s)m(kg)Favg(N)
36 1.84 46 100 1.40 0.95 0.88 57.14
36 1.88 48 100 1.40 0.97 0.88 57.63
Continued on next page
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Table B.3 – continued from previous page
∆t(µm)V(V)h2(mm)h1(mm)v1(m/s)v2(m/s)m(kg)Favg(N)
36 1.80 42 100 1.40 0.91 0.88 56.11
36 1.78 48 100 1.40 0.97 0.88 57.63
36 1.82 46 100 1.40 0.95 0.88 57.14
36 1.27 21 50 0.99 0.64 0.88 39.67
36 1.16 22 50 0.99 0.66 0.88 40.04
36 1.13 24 50 0.99 0.69 0.88 40.75
36 1.25 19 50 0.99 0.61 0.88 38.91
36 1.25 20 50 0.99 0.63 0.88 39.30
36 2.58 75 170 1.83 1.21 0.88 73.87
36 2.50 72 170 1.83 1.19 0.88 73.28
36 2.75 73 170 1.83 1.20 0.88 73.48
36 2.80 76 170 1.83 1.22 0.88 74.07
36 2.75 72 170 1.83 1.19 0.88 73.28
36 3.82 100 270 2.30 1.40 0.88 89.99
36 3.61 92 270 2.30 1.34 0.88 88.60
36 3.79 95 270 2.30 1.37 0.88 89.12
36 3.61 94 270 2.30 1.36 0.88 88.95
36 3.88 96 270 2.30 1.37 0.88 89.30
36 4.87 150 370 2.69 1.72 0.88 107.18
36 4.86 142 370 2.69 1.67 0.88 106.06
36 4.60 145 370 2.69 1.69 0.88 106.48
36 4.83 145 370 2.69 1.69 0.88 106.48
36 4.79 140 370 2.69 1.66 0.88 105.77
36 5.52 160 500 3.13 1.77 0.88 119.19
36 5.42 165 500 3.13 1.80 0.88 119.86
36 5.24 162 500 3.13 1.78 0.88 119.46
36 5.45 163 500 3.13 1.79 0.88 119.59
36 5.36 168 500 3.13 1.82 0.88 120.25
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Table B.4: Experimental data from sensor 3 and corresponding calibration results with the 0.30 grams
sphere.
∆t(µm)V(V)h2(mm)h1(mm)v1(m/s)v2(m/s)m(kg)Favg(N)
36 0.287 13 50 0.990 0.505 0.30 12.670
36 0.241 12 50 0.990 0.485 0.30 12.502
36 0.235 15 50 0.990 0.542 0.30 12.987
36 0.296 10 50 0.990 0.442 0.30 12.144
36 0.254 11 50 0.990 0.464 0.30 12.327
36 0.423 18 100 1.401 0.594 0.30 16.902
36 0.497 23 100 1.401 0.672 0.30 17.558
36 0.401 20 100 1.401 0.626 0.30 17.174
36 0.476 21 100 1.401 0.642 0.30 17.305
36 0.465 23 100 1.401 0.672 0.30 17.558
36 0.655 32 170 1.826 0.792 0.30 22.186
36 0.759 35 170 1.826 0.829 0.30 22.494
36 0.603 30 170 1.826 0.767 0.30 21.973
36 0.625 36 170 1.826 0.840 0.30 22.593
36 0.707 30 170 1.826 0.767 0.30 21.973
36 0.937 38 270 2.302 0.863 0.30 26.815
36 0.986 40 270 2.302 0.886 0.30 27.005
36 0.901 38 270 2.302 0.863 0.30 26.815
36 0.985 45 270 2.302 0.940 0.30 27.460
36 0.935 42 270 2.302 0.908 0.30 27.191
36 0.903 48 370 2.694 0.970 0.30 31.049
36 0.856 52 370 2.694 1.010 0.30 31.384
36 0.852 52 370 2.694 1.010 0.30 31.384
36 0.926 56 370 2.694 1.048 0.30 31.708
36 0.886 50 370 2.694 0.990 0.30 31.218
36 1.428 93 500 3.132 1.351 0.30 37.980
36 1.456 100 500 3.132 1.401 0.30 38.403
Continued on next page
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Table B.4 – continued from previous page
∆t(µm)V(V)h2(mm)h1(mm)v1(m/s)v2(m/s)m(kg)Favg(N)
36 1.466 96 500 3.132 1.372 0.30 38.163
36 1.405 90 500 3.132 1.329 0.30 37.794
36 1.435 102 500 3.132 1.415 0.30 38.521
Table B.5: Experimental data from sensor 3 and corresponding calibration results with the 2.02 grams
sphere.
∆t(µm)V(V)h2(mm)h1(mm)v1(m/s)v2(m/s)m(kg)Favg(N)
60 1.800 8 100 1.401 0.396 2.02 60.495
60 1.966 13 100 1.401 0.505 2.02 64.160
60 1.728 12 100 1.401 0.485 2.02 63.493
60 1.816 10 100 1.401 0.443 2.02 62.070
60 1.925 10 100 1.401 0.443 2.02 62.070
60 1.323 6 50 0.990 0.343 2.02 44.896
60 1.227 5 50 0.990 0.313 2.02 43.890
60 1.237 8 50 0.990 0.396 2.02 46.683
60 1.103 5 50 0.990 0.313 2.02 43.890
60 1.359 5 50 0.990 0.313 2.02 43.890
60 3.622 20 170 1.826 0.626 2.02 82.575
60 3.658 25 170 1.826 0.700 2.02 85.064
60 3.365 24 170 1.826 0.686 2.02 84.588
60 3.326 21 170 1.826 0.642 2.02 83.096
60 3.483 17 170 1.826 0.578 2.02 80.929
Table B.6: Experimental data from sensor 3 and corresponding calibration results with the 0.88 grams
sphere.
∆t(µm)V(V)h2(mm)h1(mm)v1(m/s)v2(m/s)m(kg)Favg(N)
36 1.586 47 100 1.401 0.960 0.88 57.385
36 1.424 42 100 1.401 0.908 0.88 56.109
Continued on next page
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Table B.6 – continued from previous page
∆t(µm)V(V)h2(mm)h1(mm)v1(m/s)v2(m/s)m(kg)Favg(N)
36 1.550 45 100 1.401 0.940 0.88 56.883
36 1.457 41 100 1.401 0.897 0.88 55.845
36 1.565 40 100 1.401 0.886 0.88 55.577
36 1.001 21 50 0.990 0.642 0.88 39.675
36 1.052 21 50 0.990 0.642 0.88 39.675
36 1.167 23 50 0.990 0.672 0.88 40.401
36 0.946 18 50 0.990 0.594 0.88 38.518
36 1.888 24 50 0.990 0.686 0.88 40.752
36 2.097 75 170 1.826 1.213 0.88 73.873
36 1.965 73 170 1.826 1.197 0.88 73.478
36 1.976 75 170 1.826 1.213 0.88 73.873
36 2.102 72 170 1.826 1.189 0.88 73.278
36 2.065 70 170 1.826 1.172 0.88 72.874
36 3.036 90 270 2.302 1.329 0.88 88.240
36 2.955 92 270 2.302 1.344 0.88 88.597
36 3.124 84 270 2.302 1.284 0.88 87.145
36 2.906 96 270 2.302 1.372 0.88 89.299
36 2.569 90 270 2.302 1.329 0.88 88.240
36 3.365 140 370 2.694 1.657 0.88 105.770
36 3.659 146 370 2.694 1.692 0.88 106.624
36 3.257 152 370 2.694 1.727 0.88 107.461
36 3.545 142 370 2.694 1.669 0.88 106.057
36 3.254 144 370 2.694 1.681 0.88 106.341
36 4.563 152 500 3.132 1.727 0.88 118.101
36 4.215 159 500 3.132 1.766 0.88 119.057
36 4.127 161 500 3.132 1.777 0.88 119.326
36 4.157 156 500 3.132 1.749 0.88 118.650
36 4.456 165 500 3.132 1.799 0.88 119.859
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