Optimization of reinforced concrete structures using population-based metaheuristic algorithms

Authors

DOI:

https://doi.org/10.5902/2179460X74927

Keywords:

Constrained Optimization, Evolutionary algorithms, Reinforced concrete

Abstract

For many industrial activities, ideal projects are achieved by comparing the solution of alternative projects with those already executed. The feasibility of solutions plays an important role in these activities. For example, the underlying objective (cost, profit, etc.) estimated for each project solution is calculated and the best solution is adopted. This is the usual procedure followed by many constructors due to time and resource limitations. However, in many cases, this method is followed simply by a lack of knowledge of existing optimization procedures. In this context, a comparative study of population-based metaheuristic algorithms applied to a case study of a reinforced concrete beam design reinforced with a polymer matrix with carbon fibers will be presented. Evolutionary algorithms have the ability to determine the optimal values of the design variables without disregarding the restrictions on ACI-318 and ACI-440 standards while minimizing the reinforcement area for each beam (cost). The comparative study shows that not all presented algorithms violated design constraints. In addition, it can be said that the values found for the design variables present a low dispersion around the mean value of the objective function.

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Author Biographies

Rodrigo Reis Amaral, Federal University of Rio Grande do Sul

Possui Graduação em Engenharia Civil pela Universidade Católica de Pelotas, Mestrado em Modelagem Computacional pela Universidade Federal do Rio Grande. Atualmente é Doutorando em Engenharia pelo Programa de Pós-Graduação em Engenharia Mecânica da Universidade Federal do Rio Grande do Sul. Seu principal interesse está na análise de estruturas de concreto armado, otimização topológica, confiabilidade estrutural e mecânica computacional. Tem experiência na área de Engenharia Civil, com ênfase em Mecânica das Estruturas.

Lamartini Fontana Barazzutti, Federal University of Rio Grande do Sul

Possui graduação em Engenharia Mecânica pela Universidade do Vale do Rio dos Sinos. Atualmente é mestrando de Engenharia Mecânica na Universidade Federal do Rio Grande do Sul. Tem experiência na área de Engenharia Mecânica, com ênfase em cálculo estrutural utilizando software de elementos finitos, atuando principalmente nos seguintes temas: CAE, simulação computacional, otimização estrutural, identificação de modelo, detecção de dano, manufatura aditiva.

Herbert Martins Gomes, Federal University of Rio Grande do Sul

Possui graduação em Engenharia Civil pela UFPB, Mestrado em Eng. Civil pela UFRGS e Doutorado em Eng. Civil pela UFRGS. Realizou estágio no Laboratório de Mecânica Experimental e Novos Materiais na UP, Portugal. Realizou Pós Doutorado na Universidade de Liverpool no Institute for Risk and Uncertainty do Dep. Eng. Mecânica (Inglaterra). Atualmente é Professor Titular da UFRGS. Tem experiência na área de Engenharia Mecânica/Civil, com ênfase em Mecânica dos Sólidos/Estruturas, tendo atuado e atuando principalmente nos seguintes temas: Elementos Finitos, Confiabilidade Estrutural, Algoritmos Heurísticos em Engenharia, Medições e Instrumentação Mecânica e Concreto Armado.

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Published

2023-12-01

How to Cite

Amaral, R. R., Barazzutti, L. F., & Gomes, H. M. (2023). Optimization of reinforced concrete structures using population-based metaheuristic algorithms. Ciência E Natura, 45(esp. 3), e74927. https://doi.org/10.5902/2179460X74927

Issue

Vol. 45 No. esp. 3 (2023): ENMC/ECTM/MCSul/SEMENGO

Section

Special Edition

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