Otimização estrutural de edificações em concreto armado com o emprego dos softwares MATLAB e Robot

• Ano de defesa: 2021
• Autor(a) principal: Huppes, Fábio Augusto Henkes
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade de Passo Fundo; Faculdade de Engenharia e Arquitetura – FEAR; Brasil; UPF; Programa de Pós-Graduação em Engenharia Civil e Ambiental
• Palavras-chave em Português: Concreto armado; Otimização estrutural; Construção civil; Algoritmos genéticos; ENGENHARIAS::ENGENHARIA CIVIL
• Link de acesso: https://repositorio.upf.br/handle/123456789/2657

The construction industry make an important role in economic and social development, however it consumes large amounts of energy and is responsible for a meaningful global generation. In this sector, buildings are responsible for consuming a high amount of materials, including steel and concrete. For years, in engineering projects, we have been looking for lowcost solutions, but the structural design is usually performed based on the experience of the design engineer, which adopts a solution that is not always the best. Given this scenario, structural optimization can be employed. However, the development of specific software for optimization, analysis, dimensioning and structural detailing requires a great deal of effort, in addition to knowledge that is normally out of the designers' daily lives. In this sense, the objective of the work is to optimize reinforced concrete building structures, considering the economic and environmental cost through the integration of Matlab and Robot softwares, in order to obtain optimal design alternatives, with the shortest possible execution time structural design. For this purpose, a formulation for reinforced concrete beams and columns was implemented, in association with the method of genetic algorithms. For the analyzed examples, it was found that the results obtained were consistent with those found in the literature. It was also observed that the proposed methodology leads to a significant reduction in the costs and impacts generated.