Statistical analyses for the ECO-Cement Research Project

Eco-Cement is a new proposed material for the construction industry that uses waste products of multiple industries in its manufacture. It is a composite material of bacteria, urea, calcium carbonate, cement kiln dust, a hydraulic agent, and sand. Through numerical simulations, we achieved the qualitative and quantitative identification of the optimal ingredients. The end product utilizes wastes of the cement manufacturing industry, the dairy industry and the poultry growing industry achieving an environmentally friendly product. In particular, we correlated the values of the ingredients with the compressive strength in order to define an optimum value for each variable and thus an optimum recipe using the mechanical properties of the composed material as the objective function. A simultaneous variation modeling of the design variables (six ingredients) was assumed. The correlation with final strength was initially attempted using linear regression analysis, but because numerical tests were not satisfactory, an advanced model using artificial neural networks was implemented. Various parameters of the neural network training were investigated and the best possible one was finally used to formulate the optimum recipe.

Sensitivity analysis for Biomass importance apropos Compressive Strength

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