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The focus of this study is to forecast the 28-day compressive strength and split tensile strength of concrete with various percentages of jute and coconut fibres mixed with quarry dust. The response surface methodology (RSM) and the artificial neural networks (ANN) methods were adopted for 3 variable process modelling (coconut fibres of 0% to 2.5%, jute fibres of 0% to 2.5%, and quarry dust of 0% to 25% by weight of cement). The RSM Box−Behnken design (BBD) method was adopted to design the experiments. Test results showed that compressive strength of 34.6 N/mm2 was obtained for concrete with 0% jute, 0% coir, and 12.5% quarry dust. Similarly, the maximum split tensile strength of 3.8 N/mm2 was obtained for concrete with 1.25% jute fibres, 1.25% coconut fibres, and 12.5% quarry dust. ANOVA and Pareto charts were used to assess regression models for response data. Each progression variable’s statistical significance was assessed, and the resulting models were expressed as second-order polynomial equations. Levenberg−Marquardt (LM) algorithm with feed-forward back propagation neural network was used for assessing the compressive strength and split tensile strength of concrete. The statistical data, root mean square error (RMSE), mean absolute error (MAE), mean absolute and percentage error (MAPE), and determination coefficient (R2) show that both techniques, ANN and RSM, are effective tools for predicting compressive strength and split tensile strength. Furthermore, RSM and ANN models have a high correlation with experimental data. However, the response surface methodology model is more accurate.

Ferrocement composites have uniform distribution and high surface area to volume ratio of reinforcement, which identifies them as a good strengthening material for use in structural applications. Because of these properties, they are considered as a substitution for some conventional structural strengthening methods. In this study, ten reinforced concrete (RC) beams of size 1220 mm × 100 mm × 150 mm were strengthened with ferrocement composites using a galvanized square weld, having volume fractions of 1.76% and 2.35%. For this study, ferrocement composites with mortar 1:2, w/c 0.4, and steel slag, with a 30% weight fraction of fine aggregate, are considered. The experimental results showed that the first crack load and the ultimate load are higher for RC beams strengthened with ferrocement having a volume fraction of 2.35% (Vr) and a steel slag replacement of 30%. Theoretical predictions were made based on the elastic moment approach; the ratio between the prediction to experimental moment capacity ranges between 0.99 and 1.04. The outcomes show that ferrocement is an effective strengthening technique for deficient reinforced concrete members

This study aimed to develop accurate models for estimating the compressive strength (CS) of concrete using a combination of experimental testing and different machine learning (ML) approaches: baseline regression models, boosting model, bagging model, tree-based ensemble models, and average voting regression (VR). The research utilized an extensive experimental dataset with 14 input variables, including cement, limestone powder, fly ash, granulated glass blast furnace slag, silica fume, rice husk ash, marble powder, brick powder, coarse aggregate, fine aggregate, recycled coarse aggregate, water, superplasticizer, and voids in mineral aggregate. To evaluate the performance of each ML model, five metrics were used: mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE), coefficient of determination (R2-score), and relative root mean squared error (RRMSE). The comparative analysis revealed that the VR model exhibited the highest effectiveness, displaying a strong correlation between actual and estimated outcomes. The boosting, bagging, and VR models achieved impressive R2-scores in the range of 86.69%–92.43%, with MAE ranging from 3.87 to 4.87, MSE from 21.74 to 38.37, RMSE from 4.66 to 4.87, and RRMSE between 8% and 11%. Particularly, the VR model outperformed all other models with the highest R2-score (92.43%) and the lowest error rate. The developed models demonstrated excellent generalization and prediction capabilities, providing valuable tools for practitioners, researchers, and designers to efficiently evaluate the CS of concrete. By mitigating environmental vulnerabilities and associated impacts, this research can significantly contribute to enhancing the quality and sustainability of concrete construction practices.

Design of Experiment approach is adopted for deriving progression variables comprising jute fibres, bamboo fibres, and silica fumes. To obtain the optimal combination of progression variables, the effect of progression variable on the strength properties of concrete, Box–Behnken design of Response Surface Methodology was adopted. Totally four responses like compressive strength and split tensile strength at 14 days and 28 days were considered. Regression models for responses were tested using Analysis of Variance (ANOVA) and Pareto chart. The statistical importance of each progression variable was evaluated, and the attained models were articulated in second-order polynomial equation. The outcomes showed that addition of jute fibres, bamboo fibres, and silica fumes has enhanced the strength properties, but higher level of fibres incorporation exhibited reduction in strength. Surface plot, Pareto chart, and regression analysis outcomes show that the most substantial and influence factor at 14 days and 28 days for compressive strength is Jute fibres and for split tensile strength is both jute and bamboo fibres. The percentage of error of the validation tests is less than 4% for compressive strength and less than 3% for split tensile strength.

The performance of structural composites during loading has always been a concern for the designers and construction industry since the reinforced concrete structure was discovered. In this study, lateral load–displacement behavior of beam–column joints wrapped with aramid fiber is evaluated using both experimental and numerical analysis subjected to torsional moment (beam-eccentric loading). Three categories of reinforcement concepts are adopted for the preparation of the beam–column joints, where members are wrapped with aramid fiber at the joints, and others are not fortified with aramid fibers. Prior to testing, the structural composites are cured for maximum 28 days into water. The beam–column joints are subjected to lateral load at a point near the column end of the beam–column connection, and the corresponding deflections are measured until the member fails. Based on the test results, ductility and energy absorption capacity are evaluated. The findings of the numerical investigation of beam–column joint show there is not much variation in the experimental and numerical analysis; it is clearly found that aramid fiber wrapping provided large rigidity in the joint, and it is also prolonged the final failure of the joints. This study shows that in addition to the conventional reinforcement, providing the hanger reinforcement and the diagonal reinforcement improves the rigidity of the beam–column joints during severe loadings, as this study described.

Bending tests were conducted on ferrocement laminates containing chicken mesh and steel slag. The fundamental goal of the examination was to investigate the effects of partial substitution of fine aggregate by steel slag in cement mortar combining chicken mesh of different volume fractions as reinforcement in thin ferrocement laminates. The following variables were investigated: (a) volume fraction of chicken mesh as 0.94%, 1.88%, 2.82%, and 3.77% and (b) level of steel slag substitution from 0% to 50% by weight fine aggregate. Results show that ferrocement laminates with chicken mesh of volume fractions of 3.77% and 30% substitution of fine aggregate with steel slag display better performance in terms of load deflection behaviour, first crack load, ultimate load, energy absorption, and ductility ratio when related with other specimens. An analytical model has been proposed to predict the ultimate moment carrying capacity of ferrocement laminates under flexure to validate the experimental results.

The construction industry significantly contributes to global CO 2 emissions, with cement production being a major factor. Concurrently, large quantities of crushed fly ash brick (CFAB) waste accumulate due to manufacturing defects. In this study, CFAB powder was developed as a supplementary cementitious material (SCM) by partially replacing cement in concrete mixes at 5%, 10%, and 15% by weight. Mechanical testing revealed that 5% CFAB replacement improved 28‐day compressive and flexural strengths by 21% and 33%, respectively, which was attributed to enhanced pozzolanic activity and the formation of calcium silicate hydrate (C–S–H) phases, as confirmed by scanning electron microscopy (SEM), energy‐dispersive X‐ray spectroscopy (EDAX), X‐ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR) analyses. Higher replacement levels reduced strength due to dilution effects. These findings demonstrate that CFAB can serve as a reactive low‐carbon binder, promoting sustainable concrete production and waste valorization aligned with circular economy goals.

The present work focused on the experimental study of the mechanical, thermal and acoustic properties of cement composite reinforced using Posidonia oceanica (PO) fibers. For this purpose, parallelepipedic specimens of dimensions 270 mm × 270 mm × 40 mm and cubic specimens of dimensions 150 mm × 150 mm × 150 mm were prepared with a water-to-cement ratio of 0.50 by varying the volume of fibers (Vf) from 0% to 20%. Properties such as compressive strength, thermal conductivity, thermal diffusivity, standardized level difference and sound transmission class were examined. The compressive strength of the specimens was determined using the rebound hammer test, while the thermal measurements were performed with the steady-state box method. The results showed that the addition of PO fibers improved the compressive strength of the mixtures and produced a maximum value of 33.60 MPa for a 10% volume of fiber content. Thermal conductivity and thermal diffusivity decreased significantly with the addition of fibers for all the mixtures. The experimental investigation also showed that the sound transmission class of PO-fiber-reinforced cementitious composites decreased as the fiber volume increased due to an increase in air voids in the mixtures.

High-performance concrete (HPC) is obtained by inclusion of mineral admixtures like silica fumes and fly ash to the normal concrete. Consumption of natural materials such as sand, natural aggregates, and limestone produces environmental degradation. Similarly, industrial by-products such as fly ash, silica fume, and ferro slag need to be safely disposed of without negatively impacting the environment. The problem being addressed in this study is the need to develop high-performance concrete (HPC) that is durable and environmentally friendly. In recent years, the use of natural aggregates and ferro slag as partial replacements for traditional aggregates has gained attention as a sustainable alternative in the production of concrete. However, there is limited research on the effect of these materials on the mechanical and durability properties of HPC under varied curing conditions. In this current research, high-performance concrete of M60 grade with partial substitution of coarse aggregate with ferro slag aggregate was formed as per the recommendations of the American Concrete Institute with the inclusion of fly ash and silica fume. Natural coarse aggregate was partly substituted by ferro slag aggregate in proportions from 0% to 40%. Partial substitution of cement was made with 15% of fly ash and 10% of silica fumes. Specimens of normal concrete mix (MF0) and modified ferro slag aggregate concrete mix (MF20, MF30, and MF40) were prepared and subjected to acid test, sulphate test, and alternate wet and drying tests to assess the compressive strength of the concrete mixes. Central composite design (CCD) of RSM modelling was adopted to recommend a regression model to forecast the compressive strength of concrete under wetting drying test, acid test, and sulphate attack. Further, natural aggregate, ferro slag, and duration of curing were considered as basic variables to suggest the model. Regression models for response data were evaluated using analysis of variance (ANOVA) and Pareto charts. The results show that the mix MF30 (30% substitution of natural aggregate by ferro slag aggregate) had higher compressive strength. The residual compressive strength at 270 days under alternate wetting and drying, acid attack, and sulphate attack was obtained as 62 MPa, 62.50 MPa, and 66.50 MPa, respectively. Similarly, the percentage loss of weight was obtained as 12.92%, 12.22%, and 6.60% for alternate wetting and drying, acid attack, and sulphate attack, respectively. The findings of the analysis of variance (ANOVA) indicate that the most significant factors influencing the variables CSWD,CSAT, and CSST are natural aggregate, ferro slag, and curing period. The regression models for CSWD,CSAT, and CSST are extremely significant, as shown by the ANOVA and Pareto chart analyses.

This study presents an empirical investigation into the flexural characteristics of concrete beams that are reinforced with glass fiber‐reinforced polymer (GFRP) bars, as well as concrete beams reinforced with traditional steel reinforcements with partial replacement of fine aggregate by granite powder. The study examines four full‐sized beams with dimensions of 100 mm × 150 mm × 1000 mm, which are reinforced with either steel or GFRP bars. The parameters tested comprise the type of tension reinforcement (steel reinforcement grade Fe 500 and GFRP bars) and granite powder substitution of 24% by weight of fine aggregate. Under a four‐point loading test, the research explores the flexural behavior, together with the relationship between load and deflection, flexural capacity, and mode of failure. The experimental investigation indicates that the first crack load increased by 2% for beams CBCP and 7.3% for GFRPCP; similarly, the percentage increase in load‐bearing capacity is 6.3% for GFRPCP with GFRP bars with 24% of granite powder substitution for fine aggregate. Similarly, the maximum deflection of reinforced concrete beams reinforced with GFRP bars with 24% granite powder is less when compared to those reinforced with steel bars. The numerical research conducted involved the creation of non‐linear finite element models for all the tested beams. A key innovation in this work lies in the combined utilization of non‐corrosive GFRP bars and granite waste, aiming to enhance both durability and sustainability. Under four‐point bending tests, beams reinforced with GFRP and granite powder exhibited improved load‐bearing capacity and reduced deflection compared to their steel‐reinforced counterparts. The study also develops and validates a non‐linear finite element model (FEM) using ANSYS, which shows strong agreement with experimental outcomes. This study presents an empirical investigation into the flexural characteristics of concrete beams that are reinforced with glass fiber‐reinforced polymer (GFRP) bars, as well as concrete beams reinforced with traditional steel reinforcements with partial replacement of fine aggregate by granite powder. The study examines four full‐sized beams with dimensions of 100 mm × 150 mm × 1000 mm, which are reinforced with either steel or GFRP bars. The parameters tested comprise the type of tension reinforcement (steel reinforcement grade Fe 500 and GFRP bars) and granite powder substitution of 24% by weight of fine aggregate. Under a four‐point loading test, the research explores the flexural behavior, together with the relationship between load and deflection, flexural capacity, and mode of failure. The experimental investigation indicates that the ultimate load‐bearing capacity of concrete beams reinforced with GFRP bars with 24% of granite powder substitution for fine aggregate surpasses that of steel‐reinforced beams. Similarly, the maximum deflection of reinforced concrete beams reinforced with GFRP bars with 24% granite powder is less when compared to those reinforced with steel bars. The numerical research conducted involved the creation of non‐linear finite element models for all the tested beams. The numerical results obtained from these models exhibit a high level of agreement with the experimental data.