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

机译:基于遗传规划的冻融循环后含纳米和微硅的水泥砂浆抗压和抗折强度的配方

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Replacing cement with supplementary cementitious materials such as nano and micro-silica would improve the mechanical properties including compressive strength (F-c) and flexural strength (F-f). 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, 0 to 0.051 of nano-silica/cement ratio, and 0-0.157 of micro-silica/cement ratio. The parameters modeled by GEP were porosity, F-c, and F-f 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 F-c and F-f was evaluated. (C) 2020 Elsevier Ltd. All rights reserved.
机译:用诸如纳米和微二氧化硅的辅助胶结材料代替水泥将改善包括抗压强度(F-c)和抗弯强度(F-f)在内的机械性能。而且,当添加微米和纳米二氧化硅时,水泥砂浆的抗冻性降低了其孔隙率。这项研究的目的是通过考虑基于实验的冻融(FT)循环来评估遗传表达程序设计(GEP)预测并制定水泥砂浆的硬化特性(同时添加纳米和微硅)的能力。数据。制备了32种混合设计,水/粘结剂比为0.4和0.5,水泥含量为990-1200 gr,砂/水泥比为2.667-3.222,纳米二氧化硅/水泥比为0至0.051,微二氧化硅为0-0.157 /水泥比。考虑到F-T循环,GEP建模的参数是孔隙度,F-c和F-f。从这项研究的实验程序获得的结果用作拟议的GEP模型的输入数据集。评价了GEP与实验结果之间的相关性,并观察到小的分散。结果表明,GEP工具具有强大的功能和鲁棒性,可用于建模包含纳米和微二氧化硅的水泥砂浆的硬化特性。它还产生了一种配方,可根据混合物组分预测这些性能。最后,进行了敏感性分析,并评估了预测变量对F-c和F-f变化的贡献。 (C)2020 Elsevier Ltd.保留所有权利。

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