OPTIMIZATION OF COMPRESSIVE STRENGTH OF WOOD ASH CEMENT CONCRETE WITH BIDA NATURAL AGGREGATES USING ARTIFICIAL NEURAL NETWORK: A REVIEW

Vollständiger Abstract

Worum geht es in dieser Arbeit?

This paper aims to provide a comprehensive evaluation of current research on the Optimization of compressive strength of wood ash cement concrete with Bida natural aggregates using artificial neural network (ANN). The primary objectives are to assess the effectiveness of wood ash (WA) cement partial replacement, and Bida natural aggregates (BNA) in concrete production using ANN, and to ascertain the optimum replacement level of WA and future research directions. The methodology involves an extensive literature review, and analysis of case studies. Key findings highlight the optimum water cement ratio of 0.4, and WA replacement level of between 5-15% for optimum results of concrete involving WA. The study reveals that ANN can be used in the analysis of nonlinear relationship between cement quantity, aggregate ratio, curing duration and compressive strength of concrete. The review concludes with recommendations for future research, focusing on the use of WA to partially replace cement in concrete production using BNA.