Analyzing the compressive strength, eco-strength, and cost–strength ratio of agro-waste-derived concrete using advanced machine learning methods
Source abstract
Abstract
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 and cementitious attributes as well as environmental and cost benefits. In addition, performing lab tests to optimize mixed proportions of concrete with different SCMs takes considerable time and effort. Therefore, the creation of estimation models for such purposes is vital. This study aimed to create interpretable prediction models for the compressive strength (CS), eco-strength (ECR), and cost–strength ratio (CSR) of DPA–ESP concrete. Gene expression programming (GEP) was employed for model generation via the hyperparameter optimization method. Also, the importance of input features was determined via SHapley Additive exPlanations (SHAP) analysis. The GEP models accurately matched experimental results for the CS, ECR, and CSR of DPA–ESP concrete. These models can be used for future predictions, reducing the need for additional tests and saving effort, time, and costs. The model’s accuracy was confirmed by an R 2 value of 0.94 for CS, as well as high values of 0.91 for ECR and 0.92 for CSR, as well as lower values for statistical checks. The SHAP analysis suggested that test age was the most critical factor in all outcomes.
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Research context
OpenAlex topics: Recycled Aggregate Concrete Performance · Innovative concrete reinforcement materials · Innovations in Concrete and Construction Materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Civil and Environmental Engineering, College of Engineering, King Faisal University , Al-Ahsa , 31982 , Saudi Arabia
Department of Civil Engineering, COMSATS University Islamabad , Abbottabad , 22060 , Pakistan
References (69)
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