Sustainable strategy of eggshell waste usage in cementitious composites: An integral testing and computational study for compressive behavior in aggressive environment

The effectiveness of cementitious composites in an aggressive environment is the primary issue since their performance deteriorates when exposed to harmful elements. Also, to promote sustainable building materials, waste materials are gaining popularity. This work employed testing followed by machine learning (ML) modeling to study the impact of eggshell powder (ESP) in cement mortar exposed to an acidic environment. The ESP was used to partially replace cement and sand, and the samples were subjected to a 5% H2SO4 solution. The dataset obtained through experimentation was utilized to construct ML-based predictive models for the reduction in compressive strength (CS) of cement mortar. According to the test results, the integration of ESP controlled the loss of cement mortar when used at lower substitutional levels. The lowest reduction in CS was seen when ESP was used as a cement substitute of 5%, which was up to 7.71% lower, and as a sand substitute of 7.5%, which was up to 7.03% lower than the same mix placed in plain water as a reference. Furthermore, the developed ML models exhibited a satisfactory level of concurrence with the experimental findings, thereby indicating their potential applicability in assessing the CS reduction percentage in cement mortar that incorporates ESP subse-quent to an acid attack.