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Flow in the human lung. The streamlines (right) are colored by the velocity magnitude and indicate the complex structure of the flow. Most of the streamlines enter the right primary bronchus due to the geometrical asymmetry of the lung model. The close-up and the cut-planes (left) show in-plane velocity vectors in the left lobar bronchus and evidence the development of Dean vortices. (For the interpretation of the color in this figure, the reader is referred to the web version of this article.)
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The deposition of aerosol particles, e.g., fine dust particles, diesel aerosols, or wood dust, in the human lung is responsible for many respiratory diseases. Small respirable particles can cause inflammations of the bronchi, coughing, allergic reactions, and even lung cancer. The deposition of such aerosols in a realistic model of the upper human...
Contexts in source publication
Context 1
... discussed in [5,47] the flow in the human lung is highly intricate, i.e., the complex geometry of the lung is responsible for the development of various secondary flow structures. Fig. 5 analytical sedimentation velocity simulated sedimentation velocity Figure 6: Comparison of the analytical and simulated sedimenta- tion velocity of a particle in a fluid at rest. The graph shows the relative error e of the particle and the analytically obtained refer- ence sedimentation velocity vz,a in percent. The time is normalized ...
Context 2
... geometry is ob- served. Most of the streamlines enter the right bronchus, i.e., most of the particles follow the same path and are expected to deposit in the right lung. This uneven dis- tribution is caused by the asymmetry of the lung model, i.e., the core flow is unequally split at the first tracheo- bronchial bifurcation. The close-up in Fig. 5 shows five cut-planes located in the right primary bronchus. The distributions of the in-plane velocity vectors evidence the complex vortical flow structure in this region. To be more precise, due to the Reynolds number and the curva- ture of the first bifurcation, which resembles a pipe bend configuration, the development of Dean ...
Citations
... A study using LBM by Lintermann et al. [22] investigated the deposition of 2.5-10 µm particles with various densities representing dust and a 100 µm particle representing a special case of highly loaded flow by such particles, e.g., in coal mines or carpenters' workshops. A realistic tracheobronchial tree of an adult male down to the sixth generation of branching was used in the simulation. ...
... Patient-Specific Models: Some studies have opted for models reconstructed from actual patient scans to provide an authentic representation of the respiratory system, as illustrated in Figure 7 [71][72][73][74][75][76][77][78][79][80][81]. The complexity of these realistic models is often dictated by the requisite precision and the scope of the research. ...
... Yet, acquiring these with high precision remains a formidable task [54,55]. Compounding this issue, CFD simulations often resort to simplifications, either by assuming steady-state conditions or overlooking minute turbulence effects, which consequently sews seeds of uncertainty in the results [58,66,67,72,77,86]. The dynamic nature of airflow, characterized by transient behaviors like turbulent flows skirting obstacles or mutable ventilation conditions, adds another layer of complexity [56,59,62,67,76,79,80,87]. ...
The United States has witnessed a concerning surge in the incidence of diseases like Coal Workers’ Pneumoconiosis (CWP), despite numerous efforts aimed at prevention. This study delves into the realm of respiratory health by investigating the deposition of dust particles within the respiratory tract and lungs. By analyzing particles of varying sizes, shapes, velocities, and aerodynamic diameters, we aim to gain a comprehensive understanding of their impact on deposition patterns. This insight could potentially drive changes in dust exposure protocols within mining environments and improve monitoring practices. The interplay of several critical factors, including particle characteristics and an individual’s breathing patterns, plays a pivotal role in determining whether particles settle in the lungs or are exhaled. This paper provides a comprehensive literature review on Respirable Coal Mine Dust (RCMD), with a specific focus on examining particle deposition across different regions of the airway system and lungs. Additionally, we explore the utility of Computational Fluid Dynamics (CFD) in simulating particle behavior within the respiratory system. Predicting the precise behavior of dust particles within the respiratory airway poses a significant challenge. However, through numerical simulations, we aspire to enhance our understanding of strategies to mitigate total lung deposition by comprehensively modeling particle interactions within the respiratory system.
... Harmful particulate matter enters the body through the human respiratory system and may induce lung cancer, pneumoconiosis, and many other respiratory diseases [27], while most of the effects are irreversible, such as pulmonary heart disease and severe asthma [28][29][30]. It is generally accepted that the location of particle deposition is dependent on the particle diameter or size. ...
... Lintermann et al. [28] researched the deposition of aerosols in the human upper tracheobronchial airway by using a unidirectional coupled Euler-Lagrange method to investigate particle flow. Aerosol flow was also accompanied by particle solvers by simulation with the Lattice Point-Boltzmann method. ...
Respirable particulate matter (RSP) is currently very harmful to the human body, potentially causing pulmonary silicosis, allergic rhinitis, acute bronchitis, and pulmonary heart disease. Therefore, the study of the deposition pattern of RSP in the human respiratory system is key in the prevention, treatment, and research of related diseases, whereby the main methods are computer simulation, in vitro solid models, and theoretical analysis. This paper summarizes and analyzes past deposition of RSP in the respiratory tract and also describes them in specific case studies such as COPD and COVID-19 patients, based on the review of the evidence, direction, and focus of future research focusing on simulation, experimentation, and related applications of RSP deposition in the respiratory tract.
... These PMs are composed of both organic and inorganic (SOx, NOx, F -) ( (Kassotis et al., 2017), (Kampa & Castanas, 2008)) species, minerals (such as calcite, dolomite, anorthite, and feldspar) ( (Badarinath et al., 2010), (Ghose & Majee, 2007)), and soil dust. Solid particles with diameters, d < 2.5 µm (PM2.5) and <10 µm (PM10), are of prime importance as they can enter lungs (Lintermann & Schröder, 2017), and their prolonged exposure can even cause cancer ( (Betha et al., 2014), (Timonen et al., 2006), (S. Wu et al., 2014)). ...
Access to clean air is a fundamental right; however, there has been a growing concern regarding air pollution. Particulate matter (PM) and greenhouse gases are affecting the environment and the health of human beings globally. There is a need to understand how dust particles soil the surface of solar cells. Moreover, there is a need to create better face masks to offer protection against these pollutants. Indoor CO2 levels are rising, which needs to be addressed by using simple absorbents. Humidity and breathing rate provide important information on the individual's physiological state and are deeply impacted due to exposure to polluted air. Therefore, a humidity sensor that can also monitor the breathing pattern provides early awareness for the user before any signs of health deterioration.
... Several numerical simulations were performed [17,[21][22][23][47][48][49] to avoid the simplifications of analytical solutions. The majority of numerical studies evaluated different fluids as mucus similar to experimental ones [7,8,16,17,50,51]. ...
Assessment of mucus velocity variations under different conditions including viscosity variation and boundary conditions is useful to develop mucosal-based medical treatments. This paper deals with the analytical investigation of mucus–periciliary velocities under mucus–periciliary interface movements and mucus viscosity variations. The results for mucus velocity show that there is no difference between the two cases under the free-slip condition. Therefore, power-law mucus can be substituted with a high viscosity Newtonian fluid since the upper boundary of the mucus layer is exposed to the free-slip condition. However, when the upper boundary of the mucus layer is under nonzero shear stress levels, including cough or sneeze, the assumption of a high viscosity Newtonian mucus layer is invalid. Moreover, mucus viscosity variations are investigated for both Newtonian and power-law mucus layers under sneeze and cough to propose a mucosal-based medical treatment. The results indicate by varying mucus viscosity up to a critical value, the direction of mucus movement changes. The critical values of viscosity in sneezing and coughing for Newtonian and power-law mucus layers are 10–4 and 5 × 10–5 and 0.0263 and 006.024 m2 s−1, respectively. Therefore, the pathogen entry into the respiratory system can be prevented by varying mucus viscosity during sneeze and cough.
... The velocity was seen to increase near this outlet, due to the reduced cross-section of the tube-like geometry-with an identical phenomenon recorded previously. 58 In Figures 2C and D, vector distributions represent the airstream directions, with longer vectors indicating higher velocities. The vector velocity profile at G0 became parabolic before splitting, in both models. ...
Particles longer than 5 μm and with a length/diameter ratio >3 are defined as fibers. Asbestos or other fibers are still identified in residential environments due to the emission from asbestos‐used building materials. The respiratory system is the primary route of asbestos exposure; under a longer residence time, asbestos‐related adverse health effects are inevitable. Currently, asbestos fibers have been replaced with man‐made vitreous fibers (MMVFs); however, studies have revealed some similar biological effects of MMVFs with asbestos. Therefore, MMVFs‐induced diseases need to be determined by analyzing their deposition characteristics and foci in human respiratory tracts. In this study, we used computational fluid dynamics method to investigate fibers' airflow and deposition patterns in two realistic human respiratory models. Two drag models were used to predict the deposition of uniform 1 μm (asbestos) and 3.66 μm (carbon fiber‐CF) diameter, 15–300 μm long fibers. Two drag models provided comparable results with the experimental data. Comparatively, asbestos deposition was independent of fiber length, while CF deposition increased proportionally to fiber length. The highest level of local deposition was detected in the anterior nasal cavity. The results obtained from this study can extend current knowledge of human vitreous fiber exposure‐related lung diseases.
... The current particle TD model is a one-way coupling model that takes into account particle movement driven by airflow but ignores particle impacts on the airflow (Chen et al., 2021;Lintermann and Schröder, 2017). Agglomeration between the particle and water may occur due to external forces such as van der Waals, electrostatic, and capillary forces. ...
Understanding nano-particle inhalation in human lung airways helps targeted drug delivery for treating lung diseases. A wide range of numerical models have been developed to analyse nano-particle transport and deposition (TD) in different parts of airways. However, a precise understanding of nano-particle TD in large-scale airways is still unavailable in the literature. This study developed an efficient one-path numerical model for simulating nano-particle TD in large-scale lung airway models. This first-ever one-path numerical approach simulates airflow and nano-particle TD in generations 0-11 of the human lung, accounting for 93% of the whole airway length. The one-path model enables the simulation of particle TD in many generations of airways with an affordable time. The particle TD of 5-nm, 10-nm and 20-nm particles is simulated at inhalation flow rates for two different physical activities: resting and moderate activity. It is found that particle deposition efficiency of 5-nm particles is 28.94% higher than 20-nm particles because of the higher dispersion capacity. It is further proved that the diffusion mechanism dominates the particle TD in generations 0-11. The deposition efficiency decreases with the increase of generation number irrespective of the flow rate and particle size. The effects of the particle size and flow rate on the escaping rate of each generation are opposite to the corresponding effects on the deposition rate. The quantified deposition and escaping rates at generations 0-11 provide valuable guidelines for drug delivery in human lungs.
... Recently, Lintermann and Schröder [61] studied the pressure variation and flow behavior in tracheal stenosis. Then, they showed that the value of the flow velocity was less than 100 m/s for a tracheal diameter of 1 mm. ...
Airway stenosis is a global respiratory health problem that is caused by airway injury, endotracheal intubation, malignant tumor, lung aging, or autoimmune diseases. A precise understanding of the airflow dynamics and pharmaceutical aerosol transport through the multi-stenosis airways is vital for targeted drug delivery, and is missing from the literature. The object of this study primarily relates to behaviors and nanoparticle transport through the multi-stenosis sections of the trachea and upper airways. The combination of a CT-based mouth–throat model and Weibel’s model was adopted in the ANSYS FLUENT solver for the numerical simulation of the Euler–Lagrange (E-L) method. Comprehensive grid refinement and validation were performed. The results from this study indicated that, for all flow rates, a higher velocity was usually found in the stenosis section. The maximum velocity was found in the stenosis section having a 75% reduction, followed by the stenosis section having a 50% reduction. Increasing flow rate resulted in higher wall shear stress, especially in stenosis sections. The highest pressure was found in the mouth–throat section for all flow rates. The lowest pressure was usually found in stenosis sections, especially in the third generation. Particle escape rate was dependent on flow rate and inversely dependent on particle size. The overall deposition efficiency was observed to be significantly higher in the mouth–throat and stenosis sections compared to other areas. However, this was proven to be only the case for a particle size of 1 nm. Moreover, smaller nanoparticles were usually trapped in the mouth–throat section, whereas larger nanoparticle sizes escaped through the lower airways from the left side of the lung; this accounted for approximately 50% of the total injected particles, and 36% escaped from the right side. The findings of this study can improve the comprehensive understanding of airflow patterns and nanoparticle deposition. This would be beneficial in work with polydisperse particle deposition for treatment of comprehensive stenosis with specific drugs under various disease conditions.
... The current particle TD model is a one-way coupling model that considers particle movement due to airflow but ignores particle effects on airflow [61,62]. When the particle volume concentration is larger than 15%, two-way models that account for particle-particle interaction are needed. ...
For respiratory health risk assessment, it is essential to evaluate the transportation and deposition (TD) of pollutant particles in human lung airways, which are responsible for lung diseases. Studies to date improved the knowledge of the particle TD in airways. However, the understanding of the TD of different pollutant particles in realistic airways has not been fully understood. This study investigates TD of three types of pollutant particles: traffic, smoke and dust, with various sizes ranging from nano- to micro-scales in the mouth–throat and tracheobronchial lung airways of a human lung using computational fluid dynamics (CFD). Three different physical activities are considered: sleeping, resting, and intense breathing, corresponding to inhalation flow rates of Qin = 15, 30 and 60 L/min, respectively. Nearly 99.8% of 10-μm traffic particles are deposited in the upper lung airways considered here. However, the TD efficiency of 10-μm dust particles is reduced to 64.28% due to the reduction in particle density. Nanoparticles have a much smaller deposition efficiency than microparticles because impaction effect of microparticles is stronger. Only less than 10% of 5-nm traffic particles are deposited in the airways for all three flow rates, allowing over 90% of particles to reach the deep lung. An important finding is that the effects of density on the particle TD of nanoparticles are much weaker than that of microparticles. At 15 L/min flow rate, the difference between the deposition efficiencies of the heaviest traffic particles and the lightest dust particles is only 3.5%. The effects of particle density on the deposition efficiencies of nano- and micro-particles are different from each other because impaction and diffusion dominate the TD of nano- and micro-particles, respectively. Density only affects impaction significantly but has little effect on diffusion.
... A TLB method employed in this study has been previously used in [1,14,23,28,31,32,35,36] to simulate respiratory flows. The code has been extensively validated in [15,17,31]. ...
Physics-based analyses have the potential to consolidate and substantiate medical diagnoses in rhinology. Such methods are frequently subject to intense investigations in research. However, they are not used in clinical applications, yet. One issue preventing their direct integration is that these methods are commonly developed as isolated solutions which do not consider the whole chain of data processing from initial medical to higher valued data. This manuscript presents a workflow that incorporates the whole data processing pipeline based on a Jupyter environment. Therefore, medical image data are fully automatically pre-processed by machine learning algorithms. The resulting geometries employed for the simulations on high-performance computing systems reach an accuracy of up to 99.5% compared to manually segmented geometries. Additionally, the user is enabled to upload and visualize 4-phase rhinomanometry data. Subsequent analysis and visualization of the simulation outcome extend the results of standardized diagnostic methods by a physically sound interpretation. Along with a detailed presentation of the methodologies, the capabilities of the workflow are demonstrated by evaluating an exemplary medical case. The pipeline output is compared to 4-phase rhinomanometry data. The comparison underlines the functionality of the pipeline. However, it also illustrates the influence of mucosa swelling on the simulation.
Workflow for enhanced diagnostics in rhinology.
