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Research Article | Open Access

Shear crack control for a reinforced concrete T-beam using coupled stochastic-multi-objective optimization methods

Department of Mathematics, College of Science, Sulaimani University, KRG
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Abstract

We use multi-objective optimization and numerical simulations to optimize the shear strength of a reinforced concrete T-beam. The optimization process involves four factors that are related to the Young's modulus of elasticity and density of both the steel reinforcement and the concrete. The factors, which have a limited range, are utilized in the construction of the regression equation that forecasts the reinforced concrete T-beam's ductility and elastic shear strain. Using ABAQUS finite element programs, 27 models were prepared for numerical analysis and simulation using the well-known sampling technique Box-Behnken design. To find the coefficients that correspond to the regression equations, MATLAB codes are utilized to solve complex matrices using the least squares method. Checking the regression equation's reliability to compare the outcomes of the numerical simulations and the regression equations, a reliability check for the regression equation has been implemented. Due to the simultaneous R2 values of 1 and 1 for ductility and elastic shear strain, the reliability check was 100%. The optimization of the reinforced concrete T-beam's shear strength capacity can be easily determined, according to multi-objective optimization results, and the design of this structural system is highly controllable.

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AIMS Materials Science
Pages 1077-1089

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Cite this article:
Ramadan A. Shear crack control for a reinforced concrete T-beam using coupled stochastic-multi-objective optimization methods. AIMS Materials Science, 2023, 10(6): 1077-1089. https://doi.org/10.3934/matersci.2023057

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Received: 21 August 2023
Revised: 27 October 2023
Accepted: 30 October 2023
Published: 15 December 2023
©2023 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)