Otimização de pilares de concreto armado com seções retangulares e circulares submetidos à flexão composta oblíqua

• Autor(a) principal: Grossmann, Daniel Dal Agnol
• Data de Publicação: 2019
• Tipo de documento: Trabalho de conclusão de curso
• Idioma: por
• Título da fonte: Repositório Institucional da UTFPR (da Universidade Tecnológica Federal do Paraná (RIUT))
• Texto Completo: http://repositorio.utfpr.edu.br/jspui/handle/1/11737
• topic: Vigas de concreto; Algorítmos computacionais; Construção civil; Concrete beams; Computer algorithms; Building; CNPQ::ENGENHARIAS

This work presents a computational algorithm, called “PFOC”, for optimization of reinforced concrete columns of rectangular and circular cross sections subjected to axial forces and biaxial bending. Columns with a slenderness coefficient λ ≤ 90 with reinforcement distributed in a symmetric form on section, without transverse loads and with discrete optimization for the steel area (bar arrangement) were studied, so that the solution obtained is executable. Aspects such as commercial gauges to the bars, design recommendations of the NBR 6118 (ABNT, 2014), possibility of additional reinforcement, dimensions for the cross section that facilitate the execution and fck up to 90 MPa are also considered. The program performs the optimization of columns through five independent steps, which include the delimitation of possible solutions, cost calculation, calculation of the resulting efforts and Ultimate Limit States (ULE) verification of the evaluated combinations, with the adoption of a methodology, adapted from the literature to consider the nonlinearity of concrete stresses. Examples of validation of the subroutines for circular and rectangular cross sections checks are presented, and comparisons between the results of the discrete optimization used in the implemented algorithm, and those of continuous optimization. "PFOC" was developed in the Python programming language, the use and modification of the program is free, its source code is available at https://github.com/DanielDgrossmann/PFOC.