Communications

Bouglada M-salah, Noui A, Belagraa L. Statistical Modelling of the Compressive Strength of Mortar Based on Cement Blended with Mineral Additions by the Method of Experimental Design. The Eurasia Proceedings of Science, Technology, Engineering & Mathematics (EPSTEM) [Internet]. 2021. Publisher's VersionAbstract

This experimental study aims to study the mechanical behaviour of a mortar based on cement blended with mineral additions (pozzolana, limestone and slag), knowing that the mechanical strength of a mortar is closely related to its composition. The use of the three mineral additions simultaneously, presents a high number of factors affecting the mechanical resistance and requires a very large number of experiments and the obtained data analysis becomes much more complex. In order to optimise the number of tests and to achieve a such satisfactory analysis, a statistical approach known as an "experimental design" was used. The experimental methodology has been established to assess the compressive strength of mortars at 2, 7, 28 and 60 days, by the elaboration of an experimental design for a set of cement mixtures, the level of the three additions (factors), slag, limestone and pozzolana at rates varying from 0% to 35%, provided that a fixed dosage of 35% is maintained for all combinations to form a binary, ternary and quaternary cement in accordance with cement standard requirements CEM II/B. This statistical approach allowed us to evaluate by a numerical analysis the effect of each addition alone as well the meaning of the double or triple interaction resulting from the association of two or three additions at a time. In addition, it has enabled us to establish a representative model that permitted to estimate and predict the mechanical behaviour of any composition in the experimental program with tolerable errors. The obtained results lead to a satisfactory numerical modeling of the compressive strengths, in particular at the age of 28 days, with a trend curve of a an acceptable determined coefficient of R 2 equal to 0.87.

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