Fly Ash-based Concrete Research Articles

Compressive Strength Prediction of Fly Ash-Based Concrete Using Single and Hybrid Machine Learning Models

The compressive strength of concrete is a crucial parameter in structural design, yet its determination in a laboratory setting is both time-consuming and expensive. The prediction of compressive strength in fly ash-based concrete can be accelerated through the use of machine learning algorithms with artificial intelligence, which can effectively address the problems associated with this process. This paper presents the most innovative model algorithms established based on artificial intelligence technology. These include three single models—a fully connected neural network model (FCNN), a convolutional neural network model (CNN), and a transformer model (TF)—and three hybrid models—FCNN + CNN, TF + FCNN, and TF + CNN. A total of 471 datasets were employed in the experiments, comprising 7 input features: cement (C), fly ash (FA), water (W), superplasticizer (SP), coarse aggregate (CA), fine aggregate (S), and age (D). Six models were subsequently applied to predict the compressive strength (CS) of fly ash-based concrete. Furthermore, the loss function curves, assessment indexes, linear correlation coefficient, and the related literature indexes of each model were employed for comparison. This analysis revealed that the FCNN + CNN model exhibited the highest prediction accuracy, with the following metrics: R2 = 0.95, MSE = 14.18, MAE = 2.32, SMAPE = 0.1, and R = 0.973. Additionally, SHAP was utilized to elucidate the significance of the model parameter features. The findings revealed that C and D exerted the most substantial influence on the model prediction outcomes, followed by W and FA. Nevertheless, CA, S, and SP demonstrated comparatively minimal influence. Finally, a GUI interface for predicting compressive strength was developed based on six models and nonlinear functional relationships, and a criterion for minimum strength was derived by comparison and used to optimize a reasonable mixing ratio, thus achieving a fast data-driven interaction that was concise and reliable.

Environmental impact of concrete containing high volume fly ash and ground granulated blast furnace slag

Concrete production is energy-intensive and has an adverse impact on the environment due to the raw materials involved. Currently, India has abundant reserves of fly ash and ground granulated blast furnace slag (GGBS). Despite various applications, fly ash often ends up in landfills. Given its abundance, there is a growing interest in utilising substantial quantities of fly ash in concrete production. In the current study, M30-grade concrete is designed with very high levels of fly ash and GGBS. Additionally, quick lime (QL) is incorporated as a supplementary agent to augment lime content. A total of twenty concrete mixes have been developed with different combinations of fly ash, GGBS, and QL. Results illustrate that the addition of QL does not show overall strength improvement to the GGBS-based mixes, but it impacts on fly ash-based mixes. The targeted design strength is achieved with 70% cement replacement with fly ash and QL. The strength development depends on the pozzolanic reaction initiated and the formation of hydration products in the system. The environmental impact of concrete is assessed by analysing its life cycle assessment using a cradle-to-gate approach. The energy requirement and kg-CO2 eq. emissions depend on the level of cement replacement. The fly ash-based concrete emits less kg-CO2 eq. and requires less energy than the GGBS-based mixes. Overall, the designed strength is achieved with 65% fly ash, requiring 59% less energy, reducing 54% CO2 footprint, 56% GWP100, 80% HTPinf, 46% ODPinf, and cost by 34% compared to OPC-based concrete.

The effect of graphene oxide-fly ash hybridisation on the hydration, microstructure and mechanical characteristics of cement concrete

Carbon-based nanomaterial graphene oxide (GO) can improve cement composites strength and toughness but reduce fluidity. Fly ash is the most common cement substitute for improved fluidity and durability, but early strength growth may be slower. The effects of GO and fly ash on concrete hydration, morphology and mechanical characteristics should be further investigated. GO addition to concrete at 0.025% and 0.05% was investigated by partially replacing cement with fly ash at 10% and 20% by weight. GO addition reduced the concrete fluidity, but the substitution of fly ash increased the fluidity. Moreover, GO compensated for the delayed strength growth of fly ash-based concrete at early-age. The strength properties of GO and fly ash-based concrete at 7 and 28 days are greater than control concrete. Hydration, morphology and elemental composition of concrete were characterised using TGDTA, SEM and EDX. The results demonstrated that GO accelerated cement hydration at early age. Furthermore, GO influenced the total hydration of concrete by expediting secondary hydration of fly ash at later age. Similarly, the morphology of concrete matrix was improved by interweaving hydrated products. This study suggests that using GO and fly ash to produce concrete is an effective process for achieving high performance.

Predictive modeling for depth of wear of concrete modified with fly ash: A comparative analysis of genetic programming-based algorithms

There has been increasing growth in incorporating fly ash as a supplementary cementitious material in concrete mixtures due to its potential to enhance the durability and strength properties of concrete. However, there is a lack of research on predicting the depth of wear of fly ash-based concrete. The laboratory methods available for estimating the depth of wear often involve destructive and expensive tests. Therefore, to avoid costly and laborious tests, this study utilized two machine learning methods, including multi-expression programming (MEP) and gene expression programming (GEP), to predict the depth of wear of fly ash-modified concrete. A comprehensive dataset of 216 experimental records was compiled from published studies for model training and validation. This extensive dataset encompasses the depth of wear as the target variable, along with nine explanatory parameters, namely fly ash, cement content, fine and coarse aggregate, water content, plasticizer, age of concrete, air-entraining agent, and testing time. The models were trained with 70% of the data, and the remaining 30% of data was used for validating the models. The models were developed by a continuous trial-and-error process and iterative refinement of hyperparameters until optimal results were achieved. The efficacy of the models was assessed via multiple statistical indicators. Furthermore, the SHapley Additive exPlanation (SHAP) was utilized for the interpretability of the model prediction from both global and local perspectives. The GEP model exhibited excellent accuracy with a correlation coefficient (R) of 0.989 (training) and 0.992 (validation). Similarly, the MEP model provided prediction accuracy with R values of 0.965 and 0.968 for training and validation sets, respectively. In addition, the MEP and GEP models outperformed the traditional multi-linear regression model. The SHAP interpretation revealed that testing time and age have a higher contribution in determining the depth of wear. The findings of this study can assist practitioners and designers in avoiding costly and laborious tests for durability assessment and promoting sustainable use of fly ash in the construction sector.

Novel agricultural waste based hardening accelerator for early strength development of fly ash-based concrete

Rapid urbanization is leading to a rise in demand for precast elements to reduce the time and cost of construction. However, precast elements consume the time to remove formwork during production depends on the early strength development of fresh concrete. On the other hand, thermal power plants produce a significant amount of fly ash, which also cause environmental issues. One solution to this problem is to use fly ash in cement and concrete to enhance their pozzolanic properties and address environmental concerns. However, using fly ash can delay the early strength development of concrete resulting deacceleration in the production cycle of precast elements. To speed up the process, some may opt for chemical-based hardening accelerator and high temperature curing. However, this may negatively impact the hydration kinetics of the concrete, pose environmental risks, and compromise the reinforced concrete’s durability.To overcome such limitations, impurity free C-S-H seed based hardening accelerator was synthesized from agricultural waste product namely, bagasse ash using novel chemical synthesis process which could effectively accelerates the early strength development of concrete without altering the conventional hydration process. The proposed synthesis process provides a platform for the reaction between the target calcium and silicate ions simultaneously eliminating the harmful elements (like chloride etc.) responsible for degradation of health of reinforced concrete structure.In order to study the effectiveness of a synthesized C-S-H seed, a blended ordinary Portland cement (OPC) was prepared by replacing 10%, 15%, and 20% of the cement weight with fly ash. Various amounts of the C-S-H seed were then added to the blend. Presence of developed C-S-H seed effectively reduced the setting time and eliminated the induction period during hydration of fly ash blended cement. Presence of additional seeds effectively reduces the critical free energy of nucleation which in turn accelerates the precipitation of hydration product responsible for the early strength development of fly ash-based concrete. Based on the setting time and heat of hydration analysis, it has been observed that the presence of C-S-H seed has the potential to accelerate the early strength gain process of fly ash-based concrete.

Novel machine learning applications on fly ash based concrete: An overview

A machine learning technique provides rapid access to various information models, approaches, complex systems, and algorithms. In the present scenario the artificial neural network, multiple linear regression, support vector machine, water cycle algorithm, and linear regression have much accessible. Continuously advancements of these techniques become a high impact on civil engineering, especially for the construction and infrastructure sector. In the present study, the historical perspective of research and development and application of machine learning techniques on fly ash-based concrete is presented. The models, algorithms, and approaches developed for predicting engineering properties of fly ash-based concrete were also discussed. These predictions using machine learning techniques have been much impacted on fly ash utilization in concrete. The utilization of fly ash in concrete also has revolutionary impacts on the environment and human health in the future. Machine learning is a useful and powerful technique that can predict concrete engineering properties and represent the scientific challenge in the construction and infrastructure sectors.

Developing a Model Based on the Radial Basis Function to Predict the Compressive Strength of Concrete Containing Fly Ash

A supplemental pozzolanic material such as fly ash may result in a reduction in the concrete’s adverse environmental effect by reducing the discharge of carbon dioxide throughout the cement production procedure. This pozzolanic material also enhances the mechanical characteristics as well as the durability of concrete material. Considering the boundless passion for utilizing fly ash and conducting extensive research studies, the extent to which this supplement can be added to concrete has a limitation equal to almost one-third of cement material’s weight. In the current study, a model based on the Radial Basis Function (RBF) is developed to estimate the compressive strength of concrete containing various amounts of fly ash at any arbitrary age. Having parameters used as inputs in ANN modeling such as concrete additives and characteristics of fly ash, the output was compressive strength. It was concluded that the estimated results agree well with the experimental measurements with an MSE of 0.0012 for the compressive strength. Simple and practical equations are proposed to present a simple means to determine the compressive strength of fly ash-based concrete.

The data-driven research on bond strength between fly ash-based geopolymer concrete and reinforcing bars

Bond strength between fly ash-based concrete (FGPC) and rebars is a vital index for ensuring the reliability and safety of reinforced concrete members. Thus, prediction and analysis of ultimate bond strength between FGPC and rebars are performed based on machine learning data-driven methods in this paper. A latest database including 137 samples from the published papers in the last decade is established. Four machine learning algorithms that include Lasso regression, Support Vector Regression (SVR), Random Forest (RF) and Extreme Gradient Boosting (XGB) are adopt for the construction of prediction models, and model evaluations are carried out by using four metrics (R2, RMSE, MAPE and MRE). The comparison between machine learning models and empirical models based on experiments is finished. Besides that, the feature importance is analyzed based on RF and XGB models. The results show that the machine learning models have a better prediction performance than the empirical models, where the RF and XGB models are optimal estimators with R2 of over 0.84 on testing set. Lasso and SVR models possess stronger generalization ability than RF and XGB models. The relatively important influence factors are compressive strength of FGPC (fc), reactivity modulus of precursors (RM), the ratio of cover thickness to diameter of rebar (c/d) and the ratio of anchorage length to diameter of rebar (l/d). Increasing slag content, fc, RM, and c/d are beneficial to enhancement of bond strength. The recommended values of fc, RM, c/d and l/d are 50 MPa, 0.7, 4.5 and 5.0 respectively.

Separation of unburned carbon from coal fly ash: Pre-classification in liquid–solid fluidized beds and subsequent flotation

Coal fly ash, which is the solid waste produced during the coal combustion and utilization, causes serious environmental problems. The preparation of concrete from coal fly ash has been proven helpful in potentially improving its value and reducing its environmental impact to a certain extent. However, the presence of unburned carbon components affects the performance of coal fly ash-based concrete. In this study, unburned carbon is separated from coal fly ash by pre-classification and subsequent optimized flotation, wherein the factors influencing are explored. The results show that under the pre-classification function of the inflatable-inclined liquid–solid fluidized bed, the underflow product is enriched in unburned carbon particles, with loss-on-ignition (LOI) and yield (Yo) values of 11.58 % and 72.87 %, respectively. Further, the underflow product is flotated for a cleaner carbon product, which is affected by the stirring rate (W) and the amount of collecting agent (C) and foaming agent (Fo). Optimized flotation (i.e., C = 18 kg/t, Fo = 6.5 kg/t, W = 1600 rad/min) results in the maximum combustible recovery rate of the flotation concentrate (89.89%), with LOI of 41.80 % and Yo of 18.51 %, yielding unburned carbon products for fuel. After mixing the flotation tailings with the pre-classified overflow production, the LOI of the formed ash-rich product is 1.73% with Yo of 81.49%, prepared into concrete. Thus, the proposed pre-classification and flotation process can improve the quality of coal fly ash. The results provide a theoretical basis for the harmless and resource treatment of coal fly ash.

Comparison of the Flexural Behavior of High-Volume Fly AshBased Concrete Slab Reinforced with GFRP Bars and Steel Bars

Fiber-reinforced polymer (FRP) rods are advanced composite materials with high strength, light weight, non-corrosive properties, and superior durability properties. Under severe environmental conditions, for concrete structures, the use of glass-fiber-reinforced polymer (GFRP) rods is a cost-effective alternative to traditional steel reinforcement. This study compared the flexural behavior of an OPC concrete slab with a high-volume fly ash (HVFA) concrete slab reinforced with GFRP rods/steel rods. In the fly ash concrete slabs, 60% of the cement used for casting the slab elements was replaced with class F fly ash, which is emerging as an eco-friendly and inexpensive replacement for ordinary Portland cement (OPC). The data presented include the crack pattern, load–deflection behavior, load–strain behavior, moment–curvature behavior, and ductility of the slab specimens. Additionally, good agreement was obtained between the experimental and nonlinear finite element analysis results using ANSYS 2022-R1. The study also compared the experimental moment capacity with the most commonly used design standard ACI 440.1R-15. This investigation reveals that there is a huge potential for the utilization of GFRP rods as reinforcement in fly ash concrete slabs.

Comparative Study of Experimental and Modeling of Fly Ash-Based Concrete.

The application of supplementary cementitious materials (SCMs) in concrete has been reported as the sustainable approach toward the appropriate development. This research aims to compare the result of compressive strength (C-S) obtained from the experimental method and results estimated by employing the various modeling techniques for the fly-ash-based concrete. Although this study covers two aspects, an experimental approach and modeling techniques for predictions, the emphasis of this research is on the application of modeling methods. The physical and chemical properties of the cement and fly ash, water absorption and specific gravity of the aggregate used, surface area of the cement, and gradation of the aggregate were analyzed in the laboratory. The four predictive machine learning (PML) algorithms, such as decision tree (DT), multi-linear perceptron (MLP), random forest (RF), and bagging regressor (BR), were investigated to anticipate the C-S of concrete. Results reveal that the RF model was observed more exact in investigating the C-S of concrete containing fly ash (FA), as opposed to other employed PML techniques. The high R2 value (0.96) for the RF model indicates the high precision level for forecasting the required output as compared to DT, MLP, and BR model R2 results equal 0.88, 0.90, and 0.93, respectively. The statistical results and cross-validation (C-V) method also confirm the high predictive accuracy of the RF model. The highest contribution level of the cement towards the prediction was also reported in the sensitivity analysis and showed a 31.24% contribution. These PML methods can be effectively employed to anticipate the mechanical properties of concretes.

Evolution Effect of Nano-Glass Powder on the Strength Performance and Microstructure of High-Volume Fly Ash-Based Concrete Incorporated with Effective Microorganisms

Evolution Effect of Nano-Glass Powder on the Strength Performance and Microstructure of High-Volume Fly Ash-Based Concrete Incorporated with Effective Microorganisms

Alkali Activated Fly Ash-Based Concrete: Evaluation of Curing Process Using Non-Linear Ultrasonic Approach

Abstract This paper investigates the applicability of the nondestructive testing and evaluation (NDT&E) method using ultrasonic signals to monitor the curing of alkali-activated fly ash-based concrete (AAFC). The evaluation was carried out on AAFC specimens with two different water/binder (W/B) ratios of 0.3 and 0.5 and after curing at 60 °C for 7, 14, and 28 days, respectively. The signals are recorded and analyzed using linear and non-linear ultrasonic techniques. The results show that the non-linear ultrasonic technique has a clear advantage over the linear ultrasonic technique when monitoring the curing of AAFC specimens with a lower W/B ratio. However, the specimens with the higher W/B ratio do not undergo proper curing and therefore do not show clear distinctions between the curing times measured from the two ultrasonic techniques. The unconfined compressive strength (UCS) of the AAFC specimens at different W/B ratios and curing times is also measured. The UCS results showed a good correlation with the ultrasonic results.

Experimental and analytical investigation on the age-dependent tensile strength of low-calcium fly ash-based concrete

In this study, the age-dependent splitting and flexural tensile strength have been investigated by incorporating the various percentages of fly ash in the plain concrete mixes. The partial replacement of cement by fly ash was varied from 0 to 60% on an equal weight basis. Standard concrete specimens were cast for measuring splitting and flexural tensile strength at different ages, i.e., 7, 28, 56, 90, 150, and 180 days, for all plain and fly ash concrete mixes. Experimental results show that the fly ash produced a significant effect on the tensile strength of concrete mixes. It has been observed that the fly ash concrete mixes gain considerable tensile strength with respect to age beyond 28 days. In the low-calcium fly ash concrete mixes, the rate of development of tensile strength from 28 to 180 was observed higher in comparison with the plain concrete mixes. The assessment of the existing models for the estimation of age-dependent tensile strength recommended by design codes and researchers with experiments has also been done on various mixes of plain and fly ash concrete. New models to predict the age-dependent splitting and flexural tensile strength of concrete having different percentages of fly ash are proposed. The present experimental and analytical study will be helpful for the designers and practicing engineers for fixing preliminary dimensions of reinforced and prestressed concrete members and mix proportioning of low-calcium fly ash concrete mixes.

Evaluation of bond performance of glass fiber rebars embedded in sustainable concrete

This paper presents experimental and statistical investigations of the bond performance of sand-coated glass fiber rebars (GFRP) embedded in three types of concrete. The need for corrosion-free materials has become more wanted to avoid the high-cost of corrosion repairs. Glass fiber is a strong candidate to replace steel reinforcement in concrete structures due to its cost-effectiveness and great corrosion resistance. On the other hand, the production of cement generates substantial amount of carbon dioxide, therefore other alternatives are in high demand. Fly ash is considered one of these alternatives used to fully or partially replace cement in concrete to avoid the problem of carbon dioxide emission. In this study, other than conventional concrete (CC), 50% and 70% replacement of cement with fly ash were implemented as two types of high-volume fly ash concrete (HVFAC). Twenty-four cylindrical specimens were pullout-tested following the Réunion Internationale des Laboratoires et Experts des Matériaux, systèmes de construction et ouvrages (RILEM) recommendations. The parameters evaluated in this study were: rebar type, rebar diameter, and concrete type. In addition to the experimental work, statistical analyses were conducted including predictions of GFRP’s bond strength, peak toughness, and post-peak toughness. Test results showed that, despite the type of concrete used, peak bond strengths of GFRP rebars were lower than those of mild steel, but the post-peak strength were higher in GFRP bars. In addition, GFRP rebars were microstructurally and chemically examined, and there were no visual signs of any microstructural and chemical attack resulted from the fly ash-based concrete.

Experimental study of effect additional water on high performance geopolymer concrete

The Earth Summit 1997 in Kyoto (Japan), industrialized countries agreed to reduce gas emissions by 21% to avoid global warming due to greenhouse effect with the release of CO2 into the air. From the research result, cement industry sector all over the world contributes about 8 - 10% of total CO2 emission. This number is quite high and if there is not a special action to reduce, CO2 emissions will continue to increase along with the rapid development of infrastructure in various parts of the world including in Indonesia. To support greenhouse effect reduction efforts due to CO2 emissions and environmental conservation, civil engineers in the world are taking steps to achieve Sustainable Concrete Technology, in order to create “Green Concrete”. For that reason in the direction of “Green Concrete”, innovation is needed to reduce or replace cement in the concrete mixing. The ash waste electrical power generating plants of fly ash is a material containing many SiO2 and Al2O3 which can be used to replace the overall of cement in concrete. Geopolymer concrete is a fly ash-based concrete that replaces the entire cement in its manufacture. Workability in mixing geopolymer concrete is very low, due to the rapid reaction of the alkaline solution when it reacts with fly ash. To improve the workability can be added water at the time of mixing. The fly ash used in the mixing from the Paiton power plant in East Java with grain size 12.06 μm with round granules and chemical composition of fly ash containing SiO2, Al2O3 and Fe2O3 with a total of 75.151%. The planned compressive strength of the concrete is 45 MPa, with a variation of 8M, 12M and 16M NaOH molarity and the ratio of NaOH and Na2SiO3 is 1. Addition of water in concrete mixing with variations of 15, 17.5, 20, 22.5 and 25 liters / m3. The results of this study indicate that the more addition of water in the manufacture of geopolymer concrete can also increase the value of slump, but the excessive addition of water will result in a decrease in the compressive strength of the concrete caused by a decrease in the concentration of the alkaline solution. High molarity values will require additional water to reach the same slump value compared to lower NaOH molarity. With the same mix design, the optimal compressive strength at 8M NaOH was 48.18 MPa with 17.5 liters/m3 of water added with a slump of 12 cm, for 12M NaOH the optimal compressive strength was 51.65 MPa with the addition of 20 liter/m3 with 10 cm slump, while for 16M NaOH the optimum compressive strength is 59.70 MPa with 22.5 liters/m3 of water added with a 5 cm slump. The higher the NaOH molarity will result in a higher compressive strength value and geopolymer concrete compressive strength at early age is higher than conventional concrete.

Assesment of Pozzolanic Performance of Sugarcane Bagasse Ash

AbstractSugarcane bagasse ash is obtained as a by-product from cogeneration combustion boilers in sugar industries, and is reported to be a useful supplementary cementitious material in concrete. A clear evaluation of pozzolanic activity of sugarcane bagasse ash is imperative to achieve its effective utilization in concrete instead of being disposed as a waste in enormous quantities. Pozzolanic activity of raw sugarcane bagasse ash and a processed sample of the same was assessed by five different standard methods in this study. The methods used were: strength activity index test, lime reactivity test, Frattini test, electrical conductivity test, and lime saturation test. In addition, chemical and mineralogical analyses were also performed on the bagasse ash. Durability performance of concrete with bagasse ash blended cement was evaluated and compared with fly ash-based concrete. The results from the studies indicate that raw bagasse ash has low pozzolanic activity due to presence of fibrous carbon particl...

A mix design procedure for low calcium alkali activated fly ash-based concretes

This paper presents a systematic approach for selecting mix proportions for alkali activated fly ash-based geopolymer concrete (GPC). The proposed mix design process is developed for low calcium Class F fly ash activated geopolymers using sodium silicates and sodium hydroxide as activator solutions. A review of the literature reveals that there are no published comprehensive approaches in designing mixes for GPC. In this paper the key factors that determine the characteristics of GPC mix are identified. The authors consider the water to geopolymer solid (W/GPS) and alkaline liquid to fly ash (AL/FA) ratios as direct measures of strength and workability. The ratio of alkaline liquid to water (AL/W) is identified to be most closely linked to the strength of GPC mixes. The paper presents detailed examples of mix designs for various strengths.

Improving the energy efficiency in buildings while reducing the waste using autoclaved aerated concrete made from power industry waste

Production of autoclaved aerated concrete (AAC) from power industry waste cinders represents a progressive technology for processing of industrial waste in a new form of building material with good qualities. Despite these positive aspects, the share of cinder concrete in the building industry is less popular. The low popularity is partially caused by the poor aesthetic of cinder concrete in comparison with sand-based AAC; however, the main cause is the slightly smaller thermal and moisture qualities of fly ash-based AAC, respecting uncertainty because there are no supporting scientific research and publications about it. This paper is dedicated to a study of the thermal and moisture properties of the cinder concrete and mutual behaviour with the sand-based AAC. It was determined that fly ash-based AAC demonstrated slightly larger moisture sorption in comparison with sand-based concrete under similar conditions. On the contrary, the thermal insulating properties of fly ash-based concrete, as indicated by the heat conductivity, exhibits less moisture influence in comparison with sand-based AAC. Concerning volume changes, fly ash-based AAC showed, in the condition of low moisture, slightly better properties when compared with autoclaved aerated sand concrete.

Strength-Cementitious Material-Water Relationship for Proportioning of Fly Ash-Based Concrete

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