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Genetic prediction of cement mortar mechanical properties with different cement strength class after freezing and thawing cycles

机译:冻融循环后不同水泥强度等级水泥砂浆力学性能的遗传预测

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摘要

This study predicts the mechanical properties of cement mortars. It focuses specifically on cement strength classes of 32.5, 42.5, and 52.5 MPa, respectively. To this end, a total of 270 specimens using 54 mix designs were constructed and subjected to freezing and thawing cycles (FTCs) at -18 and 18 degrees C. Then, mechanical properties such as compressive and flexural strength and porosity of the specimens after 0, 50, 100, 150, and 200cycles were obtained. Afterward, genetic expression programming (GEP) was used to predict the obtained results and to represent nonlinear relationships between the mechanical properties, freezing and thawing cycle, and cement strength class. The experimental data was used for training and testing of two GEP approach models. The results show that the strength of mortar reduces with increase in FTC. On other hand, a close correlation was observed between the predicted and experimental values when cement strength class and number of cycle were considered as independent input parameters. This fact indicates the significance of the aforementioned parameters along with the other parameters such as water to cement ratio, sand to cement ratio, and weight of cement on the accuracy of the prediction.
机译:这项研究预测了水泥砂浆的力学性能。它专门针对32.5、42.5和52.5 MPa的水泥强度等级。为此,使用54种混合设计构造了总共270个样品,并在-18和18摄氏度下进行了冻融循环(FTC)。然后,在0之后样品的力学性能(例如抗压强度,弯曲强度和孔隙率)获得了50、100、150和200个循环。之后,使用基因表达程序(GEP)来预测获得的结果,并表示机械性能,冻融循环以及水泥强度等级之间的非线性关系。实验数据用于训练和测试两种GEP方法模型。结果表明,砂浆的强度随FTC的增加而降低。另一方面,当将水泥强度等级和循环次数作为独立的输入参数时,在预测值和实验值之间观察到密切相关。这一事实表明上述参数以及其他参数(例如水与水泥的比例,沙与水泥的比例以及水泥的重量)对预测准确性的重要性。

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