TY - JOUR ID - 171458 TI - Optimization of Compressive Strength of Lime-Cement Concrete using Scheffe’s Regression Theory JO - Advance Researches in Civil Engineering JA - ARCE LA - en SN - AU - Awodiji, Chioma Temitope Gloria AU - Sule, Samuel AD - Senior Lecturer, Department of Civil and Environmental Engineering, University of Port Harcourt, Rivers State, Nigeria Choba Rivers State AD - Senior Lecturer, Department of Civil and Environmental Engineering, University of Port Harcourt, Rivers State, Nigeria Y1 - 2022 PY - 2022 VL - 4 IS - 4 SP - 38 EP - 54 KW - Scheffe’s regression theory KW - Compressive strength KW - Lime-cement concrete KW - Mix ratios DO - 10.30469/arce.2022.171458 N2 - In this paper, a regression model is formed to make the fore-telling of the compressive strengths and their compactible mix ratios for a lime-cement concrete as effective and perfect as possible using the Scheffe’s regression theory. Twenty four selected mix ratios were studied experimentally for their compressive strengths at 28 days after curing in water at room temperature. Compressive strengths obtained stretched from 15.12N/mm2 to 24.58N/mm2. Fifteen of the readings obtained were used to develop the regression model while nine mix proportions were adopted for validation of the developed model. The model was tested for reliability at 95 % level of confidence using the F-statistic test and found to be adequate as the calculated F-value (1.918) was less than the critical F-value (3.438). A MATLAB based computer program was written based on the regression model using visual basic 6.0 software to optimize the compressive strength of the lime cement concrete and also speed up the process of selecting the corresponding mix ratios. The peak value of compressive strength predictable by the model is 24.460336 N/mm2 and the corresponding mix ratio is 0.586:0.841:0.159:2.42:4.84 (water: cement: lime: sand: granite chippings). MATLAB program developed is interactive, quick and is suitable for application in optimum concrete mixture proportioning. UR - https://www.arce.ir/article_171458.html L1 - https://www.arce.ir/article_171458_c6323350de0505a3fae0a267ee32dac2.pdf ER -