A New Regression Model for Optimizing Concrete Mixes
Journal Title: International Journal of Engineering Sciences & Research Technology - Year 30, Vol 2, Issue 7
Abstract
Scheffe’s and Osadebe’s models are the statistical methods of concrete mix design most frequently used in civil engineering. Although these methods are quite suitable for concrete mix optimization, they are greatly limited in that a predetermined number of experiments must be carried out in order to formulate them and they can only be applied for mix ratios that fall within the predetermined observation points. Ibearugbulem’s regression model has been formulated as a new model to take care of these inherent problems in Scheffe’s and Osadebe’s. The formulation started with the Osadebe’s procedure and Scheffe’s and Osadebe’s constraints were imposed on it. Some modifications were made to obtain the new model. This new model has been satisfactorily tested through laboratory experiments on concrete. 150mm x 150mm x 150mm concrete cubes were prepared using each of 21 mix ratios, cured for 28 days, and crushed to determine their compressive strengths. The Fisher f-test revealed that the values of compressive cube strength predicted by the new regression model are very close to those from the experiment, with f-value of 1.510 at 95% confidence level. Thus, within 95% confidence level, the compressive cube strength of concrete made with water, cement, sand, and granite can be predicted using this new model. Therefore, the new Ibearugbulem’s Regression Model is suitable for concrete mix optimization. It is therefore, recommended as a new regression model for use in concrete mix design, with merits over the existing Scheffe’s simplex and Osadebe’s alternative regression models.
Authors and Affiliations
O. M. Ibearugbulem
Keywords
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