ISSN : 2663-2187

PREDICTION OF RESIDUAL STRENGTH OF RECYCLED AGGREGATE CONCRETE BY USING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING TECHNIQUES

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Rashmi K ,R. Premsudha, Shrikant Sarjerao Bobade, Konduru Anand, L. Vishnu Vardhan Reddy, E.S. Karthic
ยป doi: 10.48047/AFJBS.6.7.2024.1088-1095

Abstract

The sustainability of construction and its impact on the environment are becoming increasingly important to researchers and policymakers. As an eco-friendly option, recycled aggregate concrete (RAC) is gaining popularity. This study investigates the mechanical properties of RAC under outrageous circumstances, especially after openness to high temperatures. Key findings regarding the residual strength of RAC were synthesized through a comprehensive literature review. Inventive cross breed AI models were then evolved to foresee compressive strength, flexural strength, versatility modulus, and elasticity of RAC post-high temperature openness. With R2 values ranging from 0.91 to 0.96, these models performed well and provided professionals in the industry with equations that were simple to use. In addition to advancing sustainable construction, this work provides useful tools for everyday use.

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