Optimization of adobe clay bricks based on the raw material properties (mathematical analysis)

Abstract

This research studies the effects of composition and granulometry analysis of 139 heavy clays on the important characteristics of wet and adobe clay bricks. ANN models were obtained with high prediction accuracy in training cycles (r2): 0.580–0.907. Standard score analysis (SS) is performed to evaluate the optimal content of raw materials to gain adobe bricks. Optimal macro-oxides content was 53–66% SiO2, 4.6–7.5% Fe2O3, 12.5–18.2% Al2O3, 0.9–8.8% CaO, 1.2–3.6% MgO. The optimal quantity of alevrolite-sized particles varied between 46 and 65%, and clay-sized particles contents ranged from 20.4 to 40.6%.