Comparative Analysis of Hardened Concrete Properties and AI Prediction of SCBA Concrete

Abstract

This study investigates the hardened concrete properties, including compressive strength, tensile strength, and durability characteristics, of concrete incorporating sugarcane bagasse ash (SCBA) from Dabai and Samunaka. Furthermore, it explores the application of artificial intelligence (AI) using the Gemini AI model to predict the compressive strength of these SCBA concretes. Experimental results for compressive strength, tensile strength, sorptivity, and abrasion resistance are presented and compared. The performance of the AI model in predicting compressive strength based on mix design and SCBA source is evaluated. The findings highlight the influence of the SCBA source on the hardened concrete performance and demonstrate the potential of AI for strength prediction in SCBA concrete.