نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشجوی دکترای تخصصی مهندسی عمران – سازههای هیدرولیکی، دانشکده فنی و مهندسی عمران، دانشگاه تبریز
2 دانشیار دانشکده عمران، دانشگاه تبریز، تبریز، ایران
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Concrete, as one of the most widely used building materials in various constructions, is essential in providing the security of structures, especially hydraulic channels, in terms of resistance against water and chemical penetration. In this research, effect of zinc oxide nanoparticles on permeability of concrete as well as its mechanical characteristics is investigated experimentally and in a laboratory. By performing unidirectional compressive tests, the compression and tensile strength of concrete containing values of 0%, 0.1%, 0.5%, 1.0% and 1.5% at the ages of 7 and 28 days have been determined. Also, permeability and water absorption rate were also checked. According to the test results, the mechanical resistance of concrete increases with the increase of nanoparticles to a certain extent. Also, in the best case, per 0.1% amount of zinc oxide nanoparticles, the permeability has decreased by 97% compared to the control sample. This is because nanomaterials improve mechanical resistance by creating a denser and less porous structure in the mixture of mortar and concrete. Analytical models were developed using the genetic algorithm to describe the time-dependent characteristics of concrete samples mixed with nanoparticles in different compressive and tensile states at different ages. Therefore, in this research, an attempt has been made to predict the mixing plan of concrete containing nanoparticles by using neural networks along with the genetic algorithm method. The purpose of this modeling is to show the accuracy of neural networks in predicting the compressive, tensile, and permeability resistance of concrete with different percentages of zinc oxide nanoparticles.
کلیدواژهها [English]
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