The present global environment is facing growing issues linked to production of concrete, mostly due to high consumption of concrete as the dominating construction material globally. In today's climate of environmental sustainability, recycled concrete production using RA (recycled aggregates) requires a more holistic approach. This study examined how recycled aggregate (RA), metakaolin, silica fume and fly ash affect mechanical characteristics (compressive strength, split tensile strength), and durability characteristics (acid resistance, absorption, sorptivity) of concrete. The objective of this investigation is to figure out how the potential of RA based concrete can be improved so that they can be used to their maximum extent. To achieve the desired outcome, the study involved testing three distinct groups of concrete samples, each containing different percentages (25%, 50%, and 75%) of recycled aggregate (RA) with a constant amount of silica fume, (25 kg/m³). The first group was used as the control mix, while the second group incorporated 10% fly ash, and the third group included 15% metakaolin. The findings of this research show that the RA concrete mechanical properties as well as durability can be significantly improved by incorporating 15% metakaolin and 10% fly ash. The investigation involves the examination of all ternary blends within two distinct acidic environments, specifically a 5% hydrochloric acid (HCl) solution and sulfuric acid (H₂SO₄). Both the ternary mixes (metakaolin and fly ash) with the combination of silica improve all characteristics. The quality assurance, cost analysis and the reduction of CO₂ emissions are carried out, utilizing RA (recycled aggregates) as a substitute for NA (natural aggregate). In case of producing superior structural concrete, it is recommended based on results to limit the replacement percentage of recycled aggregate (RA) to a maximum of 50% in presence of 10% fly ash and 15% metakaolin, otherwise the RA replacement percentage should not be more than 25%.

Achieving high-strength concrete (HSC) with sustainable supplementary cementitious materials (SCMs) remains a significant challenge in the construction industry. Although glass powder has shown promise as a partial cement substitute, its specific impact on HSC growth is still unclear. This study aims to evaluate the compressive strength (CS) of high strength glass-powder concrete (HSGPC) using machine learning (ML) models and enhance predictive accuracy through hybrid optimization techniques. A dataset comprising 598 points was compiled, considering cement, glass powder, aggregates, water, superplasticizer, and curing days as key input parameters. Three standalone ML models—K-Nearest Neighbors (KNN), Random Forest (RF), and Extreme Gradient Boosting (XGB)—were trained, with RF achieving R² = 0.963 and XGB achieving R² = 0.946 on the test set. To further enhance performance, XGB was optimized using Particle Swarm Optimization (PSO), Firefly Algorithm (FA), and Grey Wolf Optimizer (GWO). Among these, XGB-GWO demonstrated the highest accuracy, with R² improving to 0.991 and MSE decreasing significantly from 83.95 to 14.42, resulting in an 82.82% error reduction. SHAP, PDP, and ICE analyses identified superplasticizer dosage, curing days, and coarse aggregate as the most influential parameters affecting compressive strength (CS). PDP and ICE validated these findings, showing reduced strength gains beyond 600 kg/m³ of cement and a decline beyond 800 kg/m³ of coarse aggregate. This study highlights the potential of ML-driven optimization for sustainable concrete design, offering an efficient, data-driven approach to optimizing material proportions for high-strength, eco-friendly concrete.

The increasing demand for sustainable construction materials has led to the incorporation of Palm Oil Fuel Ash (POFA) into concrete to reduce cement consumption and lower CO₂ emissions. However, predicting the compressive strength (CS) of POFA-based concrete remains challenging due to the variability of input factors. This study addresses this issue by applying advanced machine learning models to forecast the CS of POFA-incorporated concrete. A dataset of 407 samples was collected, including six input parameters: cement content, POFA dosage, water-to-binder ratio, aggregate ratio, superplasticizer content, and curing age. The dataset was divided into 70% for training and 30% for testing. The models evaluated include Hybrid XGB-LGBM, ANN, Bagging, LSSVM, GEP, XGB and LGBM. The performance of these models was assessed using key metrics, the coefficient of determination (R2), root mean square error (RMSE), normalized root means square error (NRMSE), mean absolute error (MAE) and Willmott index (d). The Hybrid XGB-LGBM model achieved the maximum R2 of 0.976 and the lowest RMSE, demonstrating superior accuracy, followed by the ANN model with an R2 of 0.968. SHAP analysis further validated the models by identifying the most impactful input factors, with the water-to-binder ratio emerging as the most influential. These predictive models offer the construction industry a reliable framework for evaluating POFA concrete, reducing the need for extensive experimental testing, and promoting the development of more eco-friendly, cost-effective building materials.

The major challenge for the construction industry is to design and produce sustainable construction materials that are efficient in their performance and can be affordable for construction projects. The objective of this study is to determine the viability of incorporating waste products such as sugarcane bagasse ash (SCBA) to produce concrete with polypropylene (PP) fibers. SCBA is an industry waste that has certain pozzolanic properties, however, it shows limited mechanical properties when used as a cement replacement. To improve the mechanical and durability performance, metakaolin (15%) and PP fiber (0.5%, 1%, and 1.5%) were incorporated in the SCBA blend as a ternary additive. Some of the important characteristics explored include compressive strength, tensile strength, density, water absorption, acid resistance, and sorptivity. The study reveals that the incorporation of 15% metakaolin in the composite enhanced the compressive strength by 7%, 8.2%, and 9.1% for PP fiber additions of 0.5%, 1%, 1.5%, while the acid resistance enhanced by 4%, 6% and 8% relative to the control mix for the same value of pp fiber. Furthermore, cost evaluation confirms that the overall costs of concrete with 15% metakaolin and 5% SCBA were 12.2% less than the control concrete, thus making this option economically feasible. This research proves that the inclusion of SCBA, metakaolin, and PP fibers into the concrete mixture brings a sustainable approach that enhances mechanical properties and durability while assisting sugar manufacturing plants in the proper disposal of wastes.

As a matter of fact, although RCA is inferior to that of NA (natural aggregate) in terms of performance, RCA is currently being used extensively in concrete production as a sustainable solution due to global increasing construction waste. To overcome these limitations, several mechanisms and supplementary cementitious materials (SCMs) have been investigated in the recent past. This study investigates the combined effect of natural fiber coconut (0%, 0.5%,1%,1.5% and 2%) and activated fly ash (mechanically and chemically) on performance of recycled concrete aggregate (RCA). Four concrete compositions were studied: a control group with varying RCA percentages and no fly ash, second group with 30% inactive fly ash, third group with 30% mechanically activated fly ash, and a fourth group with 30% chemically activated fly ash. The findings revealed that the addition of 30% chemically activated fly ash with 1.5% CF increased compressive strength by 25%, tensile strength by 17% for 100% RCA mix, While strength losses for the same mix are 7.18% after one month and 22.14% after three months of acid exposure. Scanning electron microscopy further validates the enhanced packing density and effective crack filling in the optimized mixes, highlighting their superior performance. This approach holds significant potential for advancing sustainable development pathways in high-performance structural concrete, particularly in regions prioritizing green building solutions.

The use of recycled aggregate (RA) as a partial or full replacement of natural aggregate (NA) is a suitable method of concrete production that has positive impacts on the environment. However, recycled aggregate concrete (RAC) has relatively lower strength and durability than that of normal concrete. To improve concrete performance, silica-fume (SF) was added with 2.5% increment up to 7.5% and metakaolin (MK) is added with a 2.5% decrement from 15 to 7.5%. The concrete with 50% RA, 10% MK and 5% SF showed notable advancement in performance after 28 days of curing. At 28 days of curing, the concrete samples had 31.5 MPa compressive strength, 5.7 MPa splitting tensile strength, and 10.6 MPa flexural strength, a strength improvement of 5.19%, 16.47%, and 8.52% over control concrete. Ultrasonic pulse velocity (UPV) indicated a 16.13% increase alongside a 20.87% reduction in water absorption which confirmed stronger bond performance and better durability of modified concrete. RCA content influences acid resistance negatively when reaching 75% RCA shows maximum deterioration. In addition, the fire resistance of such concrete resulted in higher performance at different temperature conditions for the concrete. This is due to the small particles of silica fume and metakaolin which acted as major factors and led to performance enhancements by filling in the concrete matrix gaps. The combination provides affordable, sustainable construction alternatives. Experiments show that SCMs can produce high-performance recycled concrete for modern building construction.