Analyzing the efficacy of waste marble and glass powder for the compressive strength of self-compacting concrete using machine learning strategies

REVIEWS ON ADVANCED MATERIALS SCIENCE, Journal Year: 2024, Volume and Issue: 63(1)

Published: Jan. 1, 2024

Abstract Self-compacting concrete (SCC) is well-known for its capacity to flow under own weight, which eliminates the need mechanical vibration and provides benefits such as less labor faster construction time. Nevertheless, increased cement content of SCC results in an increase both costs carbon emissions. These challenges are resolved this research by utilizing waste marble glass powder substitutes. The main objective study create machine learning models that can predict compressive strength (CS) using gene expression programming (GEP) multi-expression (MEP) produce mathematical equations capture correlations between variables. models’ performance assessed statistical metrics, hyperparameter optimization conducted on experimental dataset consisting eight independent indicate MEP model outperforms GEP model, with R 2 value 0.94 compared 0.90. Moreover, sensitivity SHapley Additive exPlanations analysis revealed most significant factor influencing CS curing time, followed slump quantity. A sustainable approach design presented study, improves efficacy minimizes testing.

Language: Английский

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Sustainable Lightweight Concrete Designed with Modified Solidified Wastewater Sludge as Partial Replacement of Cement

Sustainability, Journal Year: 2025, Volume and Issue: 17(3), P. 945 - 945

Published: Jan. 24, 2025

The requirement for high-quality drinking water and the treatment of wastewater prior to discharge into environment results in generation sludge. As with any high-volume materials, beneficial reuse applications are being sought promote sustainable environmental solutions. This research examined possibilities producing lightweight concrete using modified solidified sludge as a partial replacement cement. Wastewater was by addition aluminum oxide magnesium silicate hydrate. properties were examined, well influence cement concrete. Besides testing physical mechanical four mortar mixtures, an additional analysis willingness final users accept novel material containing addressed. obtained samples indicate that 20% is upper limit sludge’s application. prepared (in amount 20%) tested hardened state. permeability reduced 33.3% Both mixtures showed good frost resistance. maximal measured reduction compressive strengths 7.6%. Citizens’ perceptions responses regarding materials emphasize importance comprehensive education their future acceptance.

Language: Английский

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Analyzing the compressive strength, eco-strength, and cost–strength ratio of agro-waste-derived concrete using advanced machine learning methods

REVIEWS ON ADVANCED MATERIALS SCIENCE, Journal Year: 2025, Volume and Issue: 64(1)

Published: Jan. 1, 2025

Abstract Agro-waste like eggshell powder (ESP) and date palm ash (DPA) are used as supplementary cementitious materials (SCMs) in concrete because of their pozzolanic attributes well environmental cost benefits. In addition, performing lab tests to optimize mixed proportions with different SCMs takes considerable time effort. Therefore, the creation estimation models for such purposes is vital. This study aimed create interpretable prediction compressive strength (CS), eco-strength (ECR), cost–strength ratio (CSR) DPA–ESP concrete. Gene expression programming (GEP) was employed model generation via hyperparameter optimization method. Also, importance input features determined SHapley Additive exPlanations (SHAP) analysis. The GEP accurately matched experimental results CS, ECR, CSR These can be future predictions, reducing need additional saving effort, time, costs. model’s accuracy confirmed by an R 2 value 0.94 high values 0.91 ECR 0.92 CSR, lower statistical checks. SHAP analysis suggested that test age most critical factor all outcomes.

Language: Английский

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Advancing Sustainable Concrete Using Biochar: Experimental and Modelling Study for Mechanical Strength Evaluation

Sustainability, Journal Year: 2025, Volume and Issue: 17(6), P. 2516 - 2516

Published: March 13, 2025

Innovative and creative solutions are needed to reduce the substantial carbon footprint of concrete industry using low-carbon materials. Biochar has been recognised as an environmentally efficient material for production. Also, it is required build interpretable predictive models advance modelling-based mix design optimisation. This study uses biochar a cement substitute in assesses mechanical strength lab tests followed by modelling approaches. Two types derived from olive pits wood were used 2.5 5 wt.% cement. Cubes, cylinders, beams cast test concrete’s compressive, tensile, flexural strength. The data develop validate prediction compressive (CS) linear regression gene expression programming (GEP) techniques. Moreover, SHapley Additive exPlanation (SHAP) analysis was performed evaluate influence parameters on CS. results showed that pit more effective enhancing than due reduced particle size. optimal replacement levels CS split tensile GEP model effectively captured non-linear behaviour accurate approach adopted this can be optimise formulations concrete. These findings highlight potential sustainable substitute, contributing development greener with improved performance. Integrating into production significantly lower industry’s footprint, promoting responsible construction practices while maintaining structural integrity.

Language: Английский

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Implementation of agro-industrial by-products in expansive soil amelioration: design of experiment approach

AI in Civil Engineering, Journal Year: 2025, Volume and Issue: 4(1)

Published: March 17, 2025

Language: Английский

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Explicable AI-based modeling for the compressive strength of metakaolin-derived geopolymers

Case Studies in Construction Materials, Journal Year: 2024, Volume and Issue: 21, P. e03849 - e03849

Published: Oct. 22, 2024

Language: Английский

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