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Artificial Intelligence techniques have been implemented in all applications of engineering. In optimum design, nature-inspired metaheuristic algorithms are suitable for solving nonlinear optimization problems. In this study, the optimum design of reinforced concrete (RC) T-beams was investigated via a music-inspired metaheuristic algorithm called harmony search. The optimization problem was discrete variables that are also related to practical production in construction yards. ACI 318- Building Code Requirements for Structural Concrete rules were considered in the optimization process and the effect of the concrete class was investigated for three cases having C25/30, C30/37 and C35/45 type concrete classes. Additionally, the optimization was investigated for increasing flexural moments. For the evaluation of optimum results, dimension limits for the design variables were also investigated for several cases.

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Metaheuristic-Based Detailed Optimization of Reinforced Concrete T-Beams and Evaluation of the Effect of Concrete Class

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  • 发表日期：

    2026年

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  • Sinan Melih Nigdeli,
  • Gebrail Bekdaş

摘要

Artificial Intelligence techniques have been implemented in all applications of engineering. In optimum design, nature-inspired metaheuristic algorithms are suitable for solving nonlinear optimization problems. In this study, the optimum design of reinforced concrete (RC) T-beams was investigated via a music-inspired metaheuristic algorithm called harmony search. The optimization problem was discrete variables that are also related to practical production in construction yards. ACI 318- Building Code Requirements for Structural Concrete rules were considered in the optimization process and the effect of the concrete class was investigated for three cases having C25/30, C30/37 and C35/45 type concrete classes. Additionally, the optimization was investigated for increasing flexural moments. For the evaluation of optimum results, dimension limits for the design variables were also investigated for several cases.