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Computers and Concrete Volume 30, Number 2, August 2022 , pages 127-141 DOI: https://doi.org/10.12989/cac.2022.30.2.127 |
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Optimization of RC polygonal cross-sections under compression and biaxial bending with QPSO |
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Lucas C. de Oliveira, Felipe S. de Almeida and Herbert M. Gomes
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| Abstract | ||
| In this paper, a numerical procedure is proposed for achieving the minimum cost design of reinforced concrete polygonal column cross-sections under compression and biaxial bending. A methodology is developed to integrate the metaheuristic algorithm Quantum Particle Swarm Optimization (QPSO) with an algorithm for the evaluation of the strength of reinforced concrete cross-sections under combined axial load and biaxial bending, according to the design criteria of Brazilian Standard ABNT NBR 6118:2014. The objective function formulation takes into account the costs of concrete, reinforcement, and formwork. The cross-section dimensions, the number and diameter of rebar and the concrete strength are taken as discrete design variables. This methodology is applied to polygonal cross-sections, such as rectangular sections, rectangular hollow sections, and L-shaped cross-sections. To evaluate the efficiency of the methodology, the optimal solutions obtained were compared to results reported by other authors using conventional methods or alternative optimization techniques. An additional study investigates the effect on final costs for an alternative parametrization of rebar positioning on the cross-section. The proposed optimization method proved to be efficient in the search for optimal solutions, presenting consistent results that confirm the importance of using optimization techniques in the design of reinforced concrete structures. | ||
| Key Words | ||
| biaxial bending; cross-section; QPSO; reinforced concrete columns; structural optimization | ||
| Address | ||
| Lucas C. de Oliveira, Felipe S. de Almeida and Herbert M. Gomes: Department of Civil Engineering, Graduate Program in Civil Engineering, Av. Osvaldo Aranha, 99, 3o. Andar, Porto Alegre, RS, Brazil | ||