Compressive Strength Prediction Using Linear Regression Method

Year 2023, Volume: 18 Issue: 3, 100 - 106, 30.09.2023

Michael Toryila Tiza , Samson Imoni Mogbo Onyebuchi Ebenezer Ogırıma Akande Victoria Hassana Jiya Collins Onuzulike

Abstract

This study investigates the compressive strength of cement kiln replacement mixtures using a mechanistic modeling approach. The objective is to establish a mathematical model that predicts the compressive strength based on the percentage of cement kiln replacement. The study analyzed data from various replacement percentages ranging from 10% to 35% and their corresponding compressive strength values. A linear regression model was developed to capture the relationship between the replacement percentage and compressive strength. The model exhibited a good fit to the data, with a mean squared error of approximately 0.0254. Confidence intervals were calculated to provide a range of predicted compressive strength values at different replacement percentages. The findings of this study contribute to understanding the mechanical behavior of cement kiln replacement mixtures and offer insights for optimizing mixture designs. The developed mathematical model can serve as a valuable tool for engineers and researchers in the construction industry, aiding in the estimation of compressive strength for various cement kiln replacement scenarios.

Keywords

Cement kiln Replacement, Compressive Strength, Mechanistic Modeling, Mathematical model, linear regression.

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