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Abstract
A R T I C L E I N F O Keywords: Concrete Strength prediction Maturity method Thermal curing Crossover effect A B S T R A C T The maturity method is widely used to estimate early-age concrete strength. However, the traditional maturity models exhibit limited predictive capability for late concrete strength under thermal curing conditions due to the influence of the "crossover effect". This study developed a curing scheme for Standard Portland cement concrete in the absence of supplementary cementitious materials at temperatures ranging from 5 • C to 50 • C and analyzed the temperature variations inside thermally cured concrete specimens. The findings reveal that an increase in curing temperature and time between 30 • C and 50 • C and 8 and 72 h respectively led to an increase in the early strength and a decrease in the late strength of concrete, due to the "crossover effect". Additionally, a linear relationship was found between curing temperature and the late strength reduction coefficient. Utilizing this relationship, a modified maturity model that considers the "crossover effect" was proposed, improving the accuracy of predicting concrete strength under thermal curing conditions (with a prediction error of less than 10%). The research outcomes are of significant guiding significance for winter construction by ensuring the quality of concrete, reducing construction accidents, and improving construction efficiency.
... This process assists construction managers in making informed decisions regarding the timely removal of formwork [10]. Moreover, suboptimal concrete strength can lead to cracking and compromised durability [11][12][13]. Multiple structural failures have been attributed to the premature removal of formwork, highlighting the critical nature of accurate early-age concrete strength assessment. ...
Concrete is one of the most widely used building materials due to its durability and cost-effectiveness. Accurate prediction of its compressive strength during early stages is crucial for construction project management, particularly for decisions related to formwork removal and scheduling subsequent activities. Traditional methods for strength assessment, such as concrete cube testing, are labor-intensive and may not represent in-situ conditions accurately. This study introduces an innovative, cost-effective IoT-based system using the maturity method to predict concrete compressive strength in real-time. The proposed system leverages easily accessible hardware and open-source software to provide real-time data on concrete strength development, enhancing monitoring accuracy and operational efficiency. We employed the Nurse-Saul maturity equation and developed a comprehensive calibration process to establish a reliable maturity-strength relationship. The system’s implementation was tested on an actual construction site, focusing on optimizing sensor layout and ensuring continuous data transmission. Results demonstrated high accuracy of strength predictions, with percentage errors within acceptable limits as per ASTM standards. Challenges such as Wi-Fi connectivity, power management, and basic data security were addressed during the deployment phase. The study highlights significant cost savings and improved monitoring capabilities compared to traditional methods, providing a practical solution for construction project managers. Future research will focus on scaling the system for larger projects, integrating advanced analytics, enhancing data security, and developing wireless sensor setups to reduce labor further and improve efficiency. This research underscores the transformative potential of low-cost IoT systems in the construction industry, offering practical solutions for real-time concrete strength monitoring.
... The main elements of concrete are coarse aggregate, water, cement, and fine aggregate [2]. Even though concrete is used extensively, it might not be easy to anticipate its strength at different stages [3]. Naderi & Kaboudan [4] conducted an experimental study of the effect of aggregate type on concrete strength and permeability and observed that coarse aggregates comprise the majority of the concrete mix; they can significantly affect the permeability and strength of concrete. ...
In the field of Reinforced Concrete Construction, concrete emerges as the predominant and extensively employed construction material. Concrete comprises a solid, chemically inert granular substance called coarse aggregate (CA) bonded with cement and water. Compared to fine aggregate or cement, CA has a larger volume of concrete. By examining the characteristics of the coarse aggregate using various laboratory testing processes, the coarse aggregate may be properly used in concrete. Bangladesh is experiencing significant growth in its infrastructure industry due to the construction of mega projects nationwide. For the building of RCC in Bangladesh, coarse aggregate is mainly procured from two sources in Bangladesh, and another is imported from China. This study aims to develop a clear understanding of aggregate and concrete strength quality for different coarse aggregates and track changes in the appearance of CA from multiple sources in China and Bangladesh. Coarse aggregates were collected from four prominent sources: Jaflong and Bholaganj (Bangladesh), Shandong, and Jiangsu (China). ACV (aggregate crushing value), gradation, voids, and unit weight; AIV (aggregate impact value), absorption, specific gravity, and resistance to abrasion-induced deterioration; and Los Angeles (LA) machines' impact tests have been conducted for all sources of CA. The concrete cylinder was made and tested for all sources of CA with the same ratio of cement, sand, and water to know the concrete strength for different CAs.
... SVM is a supervised learning algorithm used for classification and regression [69]. This algorithm finds the optimal hyperplane in the feature space to predict samples and ensures the predictive model's generalization capability by maximizing the optimal hyperplane. ...
This study proposed a procedure to optimize the mixture proportion of geopolymer using machine learning (ML) and multi-objective optimization (MOO) model, which enhances the compressive strength and minimizes the carbon emission and costs. The experiment was preliminary carried out to analyze the workability, compressive strength, microstructure, and pore characteristics of fly ash/slag-based geopolymer. The results showed that the higher replacement ratio of slag established positive effects on the hardening as well as porosity improvement due to the coexistence of CSH and NASH-type binders, especially for a ratio was no more than 60%. Considering the performance of geopolymers is often influenced by multiple factors such as material composition and curing conditions, which could not be solved by traditional methods. A database containing 836 samples was established to analyze the prediction performance of six ML models by using Bayesian optimization. The GPR model has good generalization ability, with R2 being 0.99 (0.99) on the testing set (testing set). Furthermore, the reliability of the ML models was evaluated by the tests conducted in this paper. The feature importance analysis utilizing SHAP method indicates that Age, HM, and SS were key parameters influencing the compressive strength of geopolymer. The proposed MOO model can effectively evaluate the trade-offs between compressive strength, carbon emission, and costs, and all Pareto solutions for bi-objective and three-objective provided the optimal mixture schemes. On this basis, the design procedure proposed in this paper can give the scheme of geopolymer materials with different requirements (given mixture scheme and given design strength).
This study aims to establish a development model for the compressive strength of 3D printed concrete (3DPC) under the coupling influence of temperature and humidity, utilizing the maturity method. Initially, diverse curing conditions were applied to 3D printed specimens, incorporating varying temperatures (10 °C, 20 °C, 40 °C) and relative humidity levels (100% RH, 80% RH, 60% RH, 40% RH), with strength value assessed at different ages. Subsequently, a maturity model for humidity modification was proposed, and the model was calibrated through experimental results. The results show that the strength of the specimens increases over time, irrespective of the variations in curing temperatures and humidity levels. Moreover, with a decrease in humidity level, a more pronounced decline in strength is observed. Furthermore, the anisotropy index values of the rate constant in the Y-direction specimen, when cured at temperatures of 10 °C and higher humidity conditions, such as 100% RH and 80% RH, exhibit significant variations across different temperatures and moisture levels, leading to increased anisotropies. The modified maturity model can be used to predict and evaluate the strength development of 3D PC under different environmental conditions with high accuracy.
This research contributes to the understanding of linear $\alpha$-simplex and $\alpha$-MacDonald Codes, their representations through Gray images, and their applications in multi-secret sharing schemes, thereby advancing the theoretical foundations and practical implementations in the fields of coding theory and information security.
This book contains includes contributions of all participants of the 14th Symposium on Generating Functions of Special Numbers and Polynomials and their Applications (GFSNP 2024). It is also available at the following link: https://gfsnpsymposia.com/wp-content/uploads/2024/03/final_proceedings_book_of_gfsnp2024.pdf
In Civil Engineering field, the compressive strength of concrete is a key parameter to design concrete structures and evaluate existing structures. Conventionally the measurement of the strength requires a considerable amount of time (~28 days) and cost. Thus, this paper comprehensively reviews the literature on strength prediction models focusing on the prediction mechanism and its prediction precision. The literature demonstrates that various techniques including mathematics and statistics, analytical, numerical, computational, homogenization and multi-scale model have been employed to develop a model. An analytical model which simply correlates compressive strength and strength influencing factors was first introduced based on a statistical analysis of experimental data and the ideology of concrete technology. With the advancement of concrete technology, those analytical models fail to account for the complexity of strength affecting factors and compute less accurate results. Although Machine Learning (ML) techniques have proven superior accuracy for estimating the mixture proportions and mechanical properties of novel concrete with complex cementitious material, the prediction mechanism is being ‘black box’ which limits its wide application. Since the microstructure of hydrated cement paste was identified as a strength controlling factor in concrete, several models have been developed simulating the hydration of cementitious materials and thus bridging between nano and macro properties such as compressive strength and young’s modulus of concrete. Even though those microstructural models give comparable results with experimental data, various assumptions and hypotheses were considered during the model development. In addition, some of the models could not directly correlate the macro properties of concrete. The review presented in this paper is strong evidence of the need for a powerful model which realistically predicts the mechanical properties of concrete incorporating fundamental physics and chemistry, thermodynamic consideration, bonding and packing arrangement between particles.
Along with the construction industrialization degree, precast concrete components are being utilized more and more frequently in construction to speed up the process and guarantee the quality of structural concrete. In order to make the precast concrete components reach the required strength quickly and speed up the turnover of formwork, various rapid concrete curing methods emerge. Steam curing, direct electric curing, and microwave curing are the widely studied rapid curing methods. Rapid curing methods promote early strength growth by changing the internal and external temperature and humidity of concrete, but may lead to late strength shrinkage, increased internal micro-cracks, coarsening of pore structure and other problems. Based on the comprehensive analysis of the curing principles of the three rapid curing methods, this paper reviews the effects of the three rapid curing methods on the hydration process, properties, and microscopic pore structure of concrete. The shortcomings of different rapid curing methods, and the corresponding topics of future research.
Quality assurance of concrete used in structures requires in-situ monitoring of early age compressive strength development. Unlike traditional approaches, accurate estimation of early age concrete strength using maturity method can be effectively used to optimise critical construction operations, prevent performance issues and even structural failure. According to the concrete maturity method, concrete strength development is strongly linked to curing temperature and relative humidity. This paper presents an overview of in-situ monitoring strength in concrete structures using the maturity method. Various maturity functions and strength-maturity relationships are summarised. Advanced technological monitoring systems, including both wired and wireless technologies, used for determining concrete strength, temperature, and maturity are discussed with an emphasis on fully automated real-time monitoring systems. Examples of applying the maturity method in monitoring of in-situ strength in various concrete structures are highlighted and compared to the traditional method (e.g. concrete cylinder testing). As a result, the maturity method is a reliable indicator of the in-situ strength to ensure the safety of various structural concrete elements during construction. The paper concludes by stressing some areas where further investigations could provide important insights into the advancements of the field.
Concrete is composite material consisting of cement, fine aggregate and coarse aggregates. The ingredients of cement are highly expensive and also create a very bad impact on the environment due to the hazardous emission of carbon dioxide in the troposphere. Therefore, the researchers and scientists are in search of eco-friendly construction materials. In this regard, sticky rice pulp, Samanea Saman pod and human hair are organic materials that can be used by some percentage to enhance the quality of construction work and curtail the cost of construction. This review paper is focused on utilization of sticky rice pulp, Samanea Saman pods and human hair in concrete which is a new concept. This review paper also insights the application of sticky rice pulp, Samanea Saman pods and human hair in concrete in terms of its working and mechanical properties. In future this review, engineering application of concrete with the above organic materials will help to provide a guide for environment friendly building materials.
The evolution of nanotechnology introduced novel materials that can be used to enhance the mechanical behaviour of concrete and other materials. The enhancement ratio depends on the type and percentage of the nanomaterial. A prediction model that can estimate the compressive strength of concrete made with nanomaterials is still lacking. Such models are considerably needed for the design and analysis of reinforced concrete structures made with nanomaterials. Gene expression programming (GEP) was used in this research to develop a prediction model that can estimate the compressive strength of concrete modified with carbon nanotubes (CNTs), nano-silica (NS), nano clay (NC), and nano aluminum (NA). A total of 94 data points were collected from several tests found in the literature to develop the GEP model. Two GEP models were developed where the first one neglects the effect of NC and NA while the second GEP model considers their effect. The models were then verified using statistical evaluation. The GEP models have high R² values of 94% and 92.5% and low mean absolute error of 4.6% and 2.9% of all data for the first and second GEP model, respectively. A parametric study is then performed to further validate the GEP models by investigating the sensitivity of their parameters to the compressive strength of nano concrete. The trends of the GEP model are in agreement with the overall trends of the experimental results available in the literature. The compressive strength of concrete predicted using the GEP model increases with the addition of CNTs, NS, and NC, while it decreases with NA. This confirms the accuracy of the GEP models.
The Modified Nurse-Saul function relies on (a) a relationship between concrete compressive strength and the Nurse-Saul maturity index, (b) an “acceleration” factor and (c) a “temperature efficiency” factor. The “acceleration” compresses a certain percentage of hydration or strength development into a smaller time interval. The strength development rate is therefore increased because of the “compression” of the hydration interval. Had the hydration at higher curing temperatures been as efficient in contributing to the compressive strength as at lower temperatures then the “acceleration” factor would be equal to the “compression” factor. Procedures are described to determine these factors from isothermally cured concretes. They are then used in an iterative procedure to predict/estimate the strength development for adiabatically cured concretes. The predictions/estimates are shown to be significantly more accurate than those from the Nurse-Saul and Arrhenius maturity functions.
Cement-based materials (CBMs) such as pastes, mortars and concretes are the most frequently used building materials in the present construction industry. Cement hydration, along with the resulting compressive strength in these materials, is dependent on curing temperature, methods and duration. A concrete subjected to an initial higher curing temperature undergoes accelerated hydration by resulting in non-uniform scattering of the hydration products and consequently creating a great porosity at later ages. This phenomenon is called crossover effect (COE). The COE may occur even at early ages between seven to 10 days for Portland cements with various mineral compositions. Compressive strength and other mechanical properties are important for the long life of concrete structures, so any reduction in these properties is of great concern to engineers. This study aims to review existing information on COE phenomenon in CBMs and provide recommendations for future research.
This study aims at predicting and modeling the 7; 28 and 56 days compressive strength of a concrete containing concrete’s recycled coarse aggregates and that, for different range of cement content and slump. To achieve this, the response surface methodology (RSM) and the artificial neural networks (ANN) approaches were used for three variable processes modeling (cement content in the range of 300 to 400 kg/m3, percentage of recycled coarse aggregate from 0 to 100% and slump from 5 to 12 ± 1 cm). The results indicate that the compressive strength of recycled concrete at 7, 28 and 56 days is strongly influenced by the cement content, %RCA and slump (p < 0.01). It is found that the compressive strength at 7, 28 and 56 days decreases from 22.62 to 18.56, 34.91 to 28.70 and 37.77 to 32.26 respectively with increasing in RCA from 0 to 100% at middle levels of cement content and slump. The results in statistical terms; relative percent deviation (RDP), mean squared error (MSE), root mean square error (RMSE), determination coefficient (R2) and adjusted coefficient (R2adj), reveals that the both approaches ANN and RSM are a powerful tools for the prediction of the compressive strength. Furthermore, ANN and RSM models are very well correlated with experimental data. However, artificial neural network model shows better accuracy.
Concrete undergoing early frost damage in cold weather will experience significant loss of not only strength, but also of permeability and durability. Accordingly, concrete codes like ACI-306R prescribe a minimum compressive strength and duration of curing to prevent frost damage at an early age and secure the quality of concrete. Such minimum compressive strength and duration of curing are mostly defined based on the strength development of concrete. However, concrete subjected to frost damage at early age may not show a consistent relationship between its strength and durability. Especially, since durability of concrete is of utmost importance in nuclear power plant structures, this relationship should be imperatively clarified. Therefore, this study verifies the feasibility of the minimum compressive strength specified in the codes like ACI-306R by evaluating the strength development and the durability preventing the frost damage of early age concrete for nuclear power plant. The results indicate that the value of 5 MPa specified by the concrete standards like ACI-306R as the minimum compressive strength to prevent the early frost damage is reasonable in terms of the strength development, but seems to be inappropriate in the viewpoint of the resistance to chloride ion penetration and freeze-thaw. Consequently, it is recommended to propose a minimum compressive strength preventing early frost damage in terms of not only the strength development, but also in terms of the durability to secure the quality of concrete for nuclear power plants in cold climates.
The maturity method is a technique to account for the combined effects of time and temperature on the strength development of concrete. The method provides a relatively simple approach for making reliable estimates of in-place strength during construction. The origin of the method can be traced to work on steam curing of concrete carried out in England in the late 1940s and early 1950s. As a result of technology transfer efforts by the Federal Highway Administration, there is renewed interest in the method within the United States. The purpose of this paper is to review of the basic concepts underlying the method and to explain how the method is applied. The review focuses on work carried out by researchers at the National Institute of Standards and Technology (formerly the National Bureau of Standards).
During the last two decades a considerable amount of effort has been devoted to the analysis of the influence of both training and testing sample size on the design and performance of pattern recognition systems. These questions are interesting to practitioners as well as theoreticians, because the small-sample effects can easily contaminate the design and evaluation of a proposed system. For applications with a large number of features and a complex classification rule, the training sample size must be quite large. A large test sample is required to accurately evaluate a classifier with a low error rate. The design of a pattern recognition system consists of several stages: data collection, formation of the pattern classes, feature selection, specification of the classification algorithm, and estimation of the classification error. In this paper, we will discuss the effects of sample size on feature selection and error estimation for several types of classifier. In addition to surveying prior work in this area, our emphasis is on giving practical advice to today's designers and users of statistical pattern recognition systems
By replacing cement in concrete production with rice husk ash (RHA), the amount of cement used and its environmental impact can be reduced. The objective of this study is to accurately determine the compressive strength of rice husk ash (RHA) concrete using a machine learning model. Stacking is an excellent fusion strategy. It uses meta-learner to better learn the prediction results of multiple base learners and improve the performance of the mode. In this research, a stacking ensemble learning-based compressive strength prediction model for rice husk ash (RHA) concrete is developed. The ensemble learning model is the first layer of the stacking model; the linear regression model is the second layer. The optimal configuration of base learners was experimentally determined, and the stacking model was contrasted with other mainstream methods. Using the base learner XGBoost model, the importance of the input feature variables was assessed. The findings reveal that the created stacking ensemble learning model can successfully fuse the prediction outputs of base learners and increase the predictive accuracy of the model. The performance evaluation indices of the established stacking model are as follows: RMSE = 2.344, MAE = 1.764, and R² = 0. 987. The developed models were compared with previous studies and the model accuracy was better than previous studies. The developed model was applied to the new dataset and the model showed good performance. The cement and age are the two most important parameters impacting the compressive strength of rice husk ash (RHA) concrete.
A freeze-thaw cycle test, nuclear magnetic resonance (NMR) T2 spectrum test, uniaxial tensile test, and uniaxial compression test were designed to study the service conditions of engineered cementitious composites (ECC) in a freeze-thaw (FT) environment in cold areas. The degradation law of the mechanical properties and damage characteristics of the pore structure of ECC with three water-binder ratios (M1: W/B = 0.24, M2: W/B = 028, and M3: W/B = 0.32) are discussed. The results demonstrate that the number of micropores and mesopores in the ECC specimens increases with an increase in the number of freeze-thaw cycles (FTs), thus gradually increasing the porosity. The uniaxial tensile strength (UTS) and uniaxial compressive strength (UCS) decrease gradually with increasing number of FTs. After FTs300, the porosity of the three groups increases by 43.83%, 59.39%, and 59.16%; the loss ratios of UTS are 26.16%, 24.47%, and 19.63%; and the loss ratios of UCS are 31.52%, 27.98%, and 27.30%, respectively. Based on the mechanical properties and pore structure test results of ECC, relation models of the UTS and UCS of freeze-thaw damaged (FTD) ECC with porosity were constructed according to the simplified center hole model of ECC and the elastic mechanics theory. To further disclose the FT evolution laws of uniaxial tensile/compressive strengths (UT/CS), the relationship models of UT/CS and number of FTs with the degree of FTD were deduced. The constructed models and test results were compared with those of some classical porosity-strength models. It was found that the constructed models met the requirements of satisfactory reliability and applications.
A broad experimental program has been performed to characterize the hydration and strength development of a Class G oil well cement under various curing temperatures from 15 to 87 °C. The progress of hydration was monitored by isothermal calorimetry, thermo-gravimetric analysis, and quantitative X-ray diffraction based on Rietveld refinement; while the strength development was evaluated by both nondestructive ultrasonic tests and destructive crush tests. Test results indicate that heat of hydration, non-evaporable water content and degree of hydration of the cement follow approximately linear relationships, which are largely independent of curing temperature; the obtained proportionality constants agree well with those estimated by previously proposed empirical equations. The influences of curing temperature on the hydration rate and strength development rate can be modeled by an equivalent age method coupled with the Arrhenius law. The apparent activation energy obtained from hydration analysis was higher than that obtained from strength development analysis.
The steam curing temperature and duration of manufactured sand concrete result from the comprehensive consideration of early strength growth rate and late strength. The effects of steam curing temperature and duration on the compressive strength during the constant temperature stage were studied experimentally to identify an economical and practical steam curing regime. Moreover, the heat of hydration, temperature change and microstructure were analyzed under different steam curing temperatures. After steam curing at 40 °C for 6 h, the hydration products covered only a small area, leaving unhydrated cement and leading to low early-stage strength. When the high-temperature steam curing duration exceeds 48 h, the hydration products are not uniformly distributed, and the C-H-S crystals tend to grow into a reticular structure with large voids, which results in an additional decrease in strength at the late stage. The results show that the duration of the constant temperature stage of steam curing at 40 °C, 50 °C and 60 °C should be controlled at 6.2–31 h, 4–19 h and 2.7–13 h, respectively. The classical maturity theory overestimates the strength of concrete at high temperatures of the steam curing stage. This paper shows how the maturity function can be modified by considering the thermal damage of the high-temperature steam curing, resulting in a more accurate strength estimation.
The heat evolution during the hydration of cement was examined by multiple calorimetric methods: isothermal, oscillating isothermal, as well as temperature scanning tests in the temperature range from 15 °C to 95 °C. The apparent activation energy (Ea) of several different types of cements were all found to decrease significantly with temperature. Type of additives and water to cement ratio had little influence on the temperature dependence of Ea. The correlation between Ea and temperature may be mathematically simplified to a step function, where Ea is a nonzero constant below a critical temperature (Tcr) and reduces to zero above that temperature. The proposed model of Ea was combined with a scale factor model to simulate the influence of curing temperature on the hydration kinetics of cement with significantly improved accuracy compared to an earlier model.
The unstable change of early temperature field during concrete curing of box girder could lead to the thermal deformation and autogenous shrinkage deformation of concrete, make the concrete crack early, and even affect the subsequent mechanical performance. In order to study the variation law of the early-age temperature field of the box girder concrete and to seek the method to control the variation of the temperature field of the box girder concrete, the No.0 box segment with the most complex structure and the largest volume in the bridge was selected as the research object. The early-age temperature field of No.0 box segment after pouring was simulated by Midas/FEA and the correctness of the simulation was verified by field measurement. Then the time-history law of early-age temperature field of the box girder under the coupling effect of hydration heat and ambient temperature was studied, and the time-history law of the early-age temperature field of the box girder was investigated by changing different concrete curing parameters. The results show that the larger the local size is, the larger the temperature difference is. The selection of formwork’s material and thickness should integrate the factors of formwork bearing capacity and thermal insulation performance. The reasonable selection of formwork can effectively control the core temperature and the temperature difference between the inside and outside of the box girder. Formwork installation temperature and wind velocity have a great influence on the temperature difference between the inside and outside of the box girder. The research results can provide technical support for controlling the early-age temperature field changes of box girder concrete, be used to provide a theoretical basis for the best selection of formwork and the selection of the best concrete curing conditions, and help to improve efficiencies in the uses of human capital, energy, and building materials in engineering construction.
Temperature evolution and compressive strength prediction of early age concrete are of great interest for designers and contractors in cold weather. In this study, a calculation method based on a C# program was first put forward to estimate the temperature evolution of concrete with thermal insulation curing. Then the compressive strength was predicted in terms of the commonly accepted maturity-strength equation. This calculation method was verified feasible because of good consistency between the measured results and the calculated temperature as well as the compressive strength of concrete at different ages. The effects of insulation material thickness, thermal conductivity, surface area-volume ratio, ambient temperature and initial concrete temperature on the cooling law of concrete under thermal insulation curing were further discussed. Therefore, this work can provide theoretical analysis and numerical calculation for predicting the temperature evolution and compressive strength before the construction of cold weather concretes, which can effectively help engineers design and optimize the curing method of concrete.
A multitude of structural health monitoring options are currently being investigated to address the reliability of concrete infrastructures at different stages of their service life. This review presents the recent achievements in the field of sensors developed for monitoring the health of concrete infrastructures. The focus of this review is on sensors developed for monitoring parameters including temperature, humidity, pH, corrosion rate, and stress/strain and the sensors particularly fabricated based on fiber optic, Bragg grating, piezoelectric, electrochemical, wireless and self-sensing technologies. Several examples of developed concrete monitoring sensors (from laboratory concepts to commercialized products) together with their various benefits and drawbacks as well as open research problems will be discussed in this paper.
The strength and E-modulus of concrete are decisive parameters when it
comes to ultimate limit state design, serviceability limit state design, and early
age crack assessment. The properties of concrete are generally determined in the
laboratory under 20 °C isothermal conditions and then used as the basis for
calculations under realistic temperature conditions. It is well-known, however, that
the curing temperature affects both the rate of property development in concrete and
the “final value” of a given property. The current study investigated the effect of
a realistic temperature history on the compressive cube strength, the tensile
strength, and the tensile E-modulus for two concretes, a reference concrete and a
fly ash concrete. Concrete specimens were subjected to either (1) 20 °C isothermal
curing conditions, or (2) realistic temperature curing conditions for 14 days and
then 20 °C isothermal conditions, until they were tested after 28 and 91 days.
Parallel tests performed in a Temperature-Stress Testing Machine were also used to
evaluate the results. The reference concrete showed a general reduction in strength
and E-modulus when subjected to a realistic curing temperature, whereas the fly ash
concrete showed an 11% increase in the 28-day E-modulus when cured under realistic
temperature conditions. Furthermore, in both isothermal and realistic curing
temperature conditions, the fly ash concrete showed a pronounced property
development beyond 28 days, which could not be described by the material model
currently used.
The compressive and tensile strength of high-performance concrete (HPC) is a highly nonlinear function of its constituents. The significance of expert frameworks for predicting the compressive and tensile strength of HPC is greatly distinguished in material technology. This study aims to develop an expert system based on the artificial neural network (ANN) model in association with a modified firefly algorithm (MFA). The ANN model is constructed from experimental data while MFA is used to optimize a set of initial weights and biases of ANN to improve the accuracy of this artificial intelligence technique. The accuracy of the proposed expert system is validated by comparing obtained results with those from the literature. The result indicates that the MFA-ANN hybrid system can obtain a better prediction of the high-performance concrete properties. The MFA-ANN is also much faster at solving problems. Therefore, the proposed approach can provide an efficient and accurate tool to predict and design HPC.
This study is investigated with the prediction of the compressive strength of early-age bisphenol F-type epoxy resin concrete when using the maturity method. When testing the compressive strength of epoxy resin concrete, the strength development started from an age of 20 h at a curing temperature of 0 °C, and the difference between the compressive strengths at the ages of 6 h and 168 h was markedly reduced at a higher curing temperature. Thus, it appeared that the bisphenol F-type epoxy resin concrete was heavily affected by curing temperature. In addition, there were significant differences in strength development based on the hardener type. When calculating the maturity index, it was appropriate to use data up to the age of 72 h, and it appeared that the appropriate value of the constant n is 0.4 in the equation proposed by Ohama, et al. The maturity index was more heavily affected by curing temperature than curing age, and there was a significant difference depending on the hardener type. This study reviewed three prediction models, and when using the dose-response curve model, the coefficient of determination (R²) was the largest, so this is the model that should be used. Although it is possible to apply this model differently based on the hardener type, it was determined that there would be no problem even if a prediction model combining all the test data on the three hardeners was used. In conclusion, when using the prediction model deduced in the study, it was possible to easily predict the early-age compressive strength of bisphenol F-type epoxy resin concrete, and to prove that the maturity method is a non-destructive test useful for cast-in-place applications.
Description
escribes the effects of different temperatures on the strength development, static and cyclic behavior, elasticity, maturity functions, and permeability of various concretes and mortars.
The rate constant for strength development of a particular concrete mixture is the initial slope of the relative strength-versus-age curve at constant temperature curing. The form of the rate constant versus temperature function is needed to describe the combined effects of time and temperature on strength development. This study investigates the relationship between the rate constant and curing temperature. Based on strength gain data for concrete and mortar specimens made with Type I cement and cured at 10, 23, and 40 C (50, 73, and 104 F), the following conclusions are drawn: (1) strength gain can be represented by a three-parameter hyperbolic function; (2) the rate constant is a nonlinear function of curing temperature and a simple exponential function describes this relationship; (3) tests of appropriate mortar specimens provide the information needed to predict relative strength development of the corresponding concrete; and (4) the proposed rate constant model accurately describes the development of relative strength as a function of the equivalent age.
Abstract In this study, maturity method was used to estimate in-place strength of large concrete placements. Four 6-foot (1.8 m) cube concrete blocks were constructed in four different locations, and the strength development curves for these concrete mixtures were established using 6 by 12 inch (150 by 300 mm) cylinder specimens collected from the construction site. Activation energy values for the concrete mixtures were determined in the laboratory and used for equivalent age calculations. Sacrificial temperature sensors embedded throughout the depth of the concrete cubes were used to monitor temperature histories in specific locations up to 28 days. Equivalent age was employed to estimate in-place concrete strength based on the collected temperature histories. Four inch (10 cm) diameter core samples, with 6-foot (1.8 m) in length, were taken from the cubes at 4, 28 and 56 days after construction and the core strengths were compared with the predicted strengths using maturity relationships. Results show that the predicted in-place concrete strength is always higher than the actual core strength on top surface locations. Results from three different cubes show that core compressive strength from mid-section were within ±15% of the predicted values and core results from the bottom section were generally higher than the predicted values.
The paper traces the development of a function between time and temperature, which makes it possible to refer the process of hardening of concrete at varying temperature to hardening at constant temperature.
It is further shown that it is possible to predetermine the temperature of concrete during hardening when properties of concrete, sizes and shape of the specimen, insulation and external temperature are known. The time temperature function can also be applied to the development of strength. The validity of the theory is demonstrated by the results of tests upon 27 American and 3 Danish cements.
This paper summarizes the conclulions drawn from experimental work carried out at the Cement and Concrete Association Research Station and elsewhere concerning the principles underlying steam curing at atmospheric pressure.
It is shown that if the temperature gradient of the concrete after the time of mixing does not exceed a certain value, the concrete gains strength during and after treatment in relation to its “maturity” (reckoned in temperature-time) approximately in accordance with the same law as holds for normally cured concrete. Concrete which is raised in temperature more rapidly is shown not to obey this law, and to be adversely affected in strength at a later age.
The use of the too rapid early temperature rises often employed in practice introduces various opposing variables which suggest optimum temperatures, delayed treatments and other arrangements of the curing cycle; such expediencies are unnecessary, however, if a slow initial temperature gradient is used.
The paper contains tables of results supporting these conclusions, and an appendix in which a possible cause of the phenomena is suggested.
There is a significant gap between the current knowledge of structural concrete, as reflected in building standards and the actual construction of structures using the maturity method. To address this situation, an experimental study was planned for the purpose of developing and validating a procedure for estimating concrete strength by the maturity method. The main difference between the procedure developed in this study and the ASTM standard is in the adaptation of the former to the semi-probabilistic method of limit states. This new procedure was employed to determine the structurally safe times for the removal of formwork in false tunnels.
The collapse of the natural-draft hyperbolic concrete cooling tower unit no. 2 at the Pleasants Power Station at Willow Island, West Virginia has been investigated. This investigation included onsite inspections, laboratory tests of construction assembly components and concrete specimens, and analytical studies. Based on the results of these field, laboratory and analytical investigations, it was concluded that the most probable cause of the collapse was due to the imposition of construction loads on the shell before the concrete of lift 28 had gained adequate strength to support these loads. The analysis of the shell indicates that the collapse initiated at the part of the shell in lift 28 where cathead no. 4 was located. It further showed that calculated stress resultants at several points in that part equaled or exceeded the strength of the shell in compression, bending and shear. The failure of these points in that part of the shell would have propagated to cause the collapse of the entire lift 28.
The development of microstructure and compressive strength of three blended cement pastes hydrated at temperatures ranging from 10°C to 60°C is described. The replacement materials were pulverised fuel ash (PFA), volcanic ash (VA), and ground, granulated blast furnace slag (GGBFS), and the blended cements had the same compositions as those reported in previous studies. The cement pastes were cured under water and tested for compressive strength at various time intervals over a period of 1 year. The only blended cement paste that had substantially improved strength compared with the neat cement paste was that containing blast furnace slag, especially at 60°C. Selected samples were examined by backscattered electrons in scanning electron microscopy (SEM). Generally, the microstructures of the pastes cured at 60°C showed greater apparent porosity than those cured at 10°C. The mechanism of hydration of the various blended cements is discussed.
The hydration of two Mexican Portland cements has been investigated at five temperatures in the range from 10 to 60°C. Samples were tested after eight periods of hydration during which they were immersed in water for between 1 day and 360 days, using quantitative X-ray diffraction, thermogravimetry, compressive strength determination, and scanning electron microscopy. Increased temperature initially accelerated the hydration of the four major anhydrous phases present in both cements. In the longer term, however, a reduced degree of hydration was observed for the alite and ferrite phases, accompanied by decreased compressive strength and increased apparent porosity.
Removal of formwork can be made in a short time by early-strength gain of concrete with heat treatment. The effects of accelerated curing temperature and fine aggregate on early strength as well as the relationships between early strength–28-day strength and strength maturity have been examined. Cube concrete specimens produced with a 10-cm constant slump value, 0.59 w/c ratio, and with two different types of fine aggregate were subjected to three-phase cure processes. These cure processes include a 1-h preheating process after having replaced concrete in the mould, the cure application process, and finally the last waiting period for 2 h that is aimed at minimizing the effects of thermal stresses. Each of the specimen groups was cured at different temperatures for different periods (6 or 18 h). At the end of curing and on the 28th day, cube compressive strengths were determined. Therefore, it was seen that it is possible to estimate 28-day strength beforehand with reasonable accuracy.
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