V3I7P86

Experimental Assessment and Machine Learning-Based Optimization of Groundnut Shell Bio-Bricks

Jadhav Swati Ramrao ^1*,  S. P. Sharma² , L. S. Mahajan³ 

Abstract

This study investigates the development of sustainable bio-bricks incorporating groundnut shell (GNS) waste as a partial fine aggregate replacement with cement, fly ash, and hydrated lime to produce eco-friendly masonry materials. Bio-bricks containing 20–60% GNS were evaluated for mechanical, physical, thermal, and durability properties. The optimum mix satisfied Indian Standard requirements for first-class bricks, exhibiting adequate compressive strength, low water absorption, reduced density, negligible efflorescence, and superior thermal insulation. Hydrated lime mortar enhanced masonry performance, increasing compressive and shear strength. Response Surface Methodology and Artificial Neural Network models accurately predicted material properties, with ANN achieving R² > 0.99. The proposed masonry system improved energy efficiency, reduced life-cycle costs, and offers a sustainable, low-carbon alternative for energy-efficient building construction.

Keywords:

Sustainable, Strength, Mortar, concrete, ML