Genetic programming based formulation for compressive and flexural strength of cement mortar containing nano and micro silica after freeze and thaw cycles

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@Article{EMAMIAN:2020:CBM,

• author = "Seyed Ali Emamian and Hamid Eskandari-Naddaf",
• title = "Genetic programming based formulation for compressive and flexural strength of cement mortar containing nano and micro silica after freeze and thaw cycles",
• journal = "Construction and Building Materials",
• volume = "241",
• pages = "118027",
• year = "2020",
• ISSN = "0950-0618",
• DOI = "doi:10.1016/j.conbuildmat.2020.118027",
• URL = "http://www.sciencedirect.com/science/article/pii/S0950061820300325",
• keywords = "genetic algorithms, genetic programming, Genetic expression programming, Cement mortar, Micro and nano silica, Freeze-thaw cycles, Porosity, Compressive and flexural strength, Sensitivity analysis",
• abstract = "Replacing cement with supplementary cementitious materials such as nano and micro-silica would improve the mechanical properties including compressive strength (Fc) and flexural strength (Ff). Also, the frost resistance of the cement mortar as adding micro and nano-silica reduces its porosity. The purpose of this investigation is to evaluating the capability of Genetic Expression Programming (GEP) to predict and formulate the hardened characteristics of cement mortar with the simultaneous addition of nano and micro-silica by considering the freeze-thaw (F-T) cycles based on experimental data. 32 mix designs were prepared with 0.4 and 0.5 water/binder ratios, 990-1200 gr of cement content, 2.667-3.222 of sand/cement ratio, to 0.051 of nano-silica/cement ratio, and 0-0.157 of micro-silica/cement ratio. The parameters modeled by GEP were porosity, Fc, and Ff by considering the F-T cycles. The results obtained from the experimental program of this study were used as input dataset for the proposed GEP models. The correlation between GEP and the experimental results was evaluated and a small dispersion was observed. The results showed the power and robustness of the GEP tool for modeling the hardened characteristics of the cement mortar comprising nano and micro-silica. It also produced a formulation to predict these properties as a function of the mixture components. Finally, a sensitivity analysis was performed and the contribution of the predictor variables on the variation of the Fc and Ff was evaluated",

}

Genetic Programming entries for Seyed Ali Emamian Hamid Eskandari-Naddaf

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