Compressive Strength Prediction of Building Blocks from Lightweight Raw Materials: A Neural Network Approach

Abstract

This paper presents a neural model to predict the compressive strength of building blocks using lightweight raw materials cured up to 28 days. The combination of raw materials is crucial to develop low cost building blocks with specific properties and acceptable mechanical strength. The model avoids testing a new mixture of building materials and provides new alternatives to design new components at low cost