Determinação do modelo elasto-plástico através de método de otimização
From the need to develop shaped parts with more complex geometries, the need to use the finite element method arises. In order to obtain precise results in the simulations, it is essential that the elastic and plastic properties of the materials are known, so it is of great importance that they can...
| Autor principal: | Aguiar, Marcos Vinícius de |
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| Formato: | Trabalho de Conclusão de Curso (Graduação) |
| Idioma: | Português |
| Publicado em: |
Universidade Tecnológica Federal do Paraná
2021
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| Assuntos: | |
| Acesso em linha: |
http://repositorio.utfpr.edu.br/jspui/handle/1/24938 |
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| Resumo: |
From the need to develop shaped parts with more complex geometries, the need to use the finite element method arises. In order to obtain precise results in the simulations, it is essential that the elastic and plastic properties of the materials are known, so it is of great importance that they can determine such properties with precision. One of these strategies is the parameter identification methodology, which combines numerical and experimental techniques, using optimization techniques. Therefore, the objective of this work is to determine the elastic-plastic parameters, considering the constitutive model of nonlinear isotropic hardening. For this purpose, an inverse model adjustment technique was used, where a finite element model (FEM) was created to represent the tensile test of steel A-533, Grade B, Class 1. From the experimental data of a tensile test of this material, the parameters of the elasto-plastic model, implemented in the finite element model (FEM), were determined by means of optimization techniques. At the end, the experimental curve and the number of the tensile test were compared, obtaining the difference of 1.6% between them. The yield curve found compared with other references shows a difference of 3.4%. The methodology developed in the study can be used for different metallic materials. The procedure is also customizable, allowing it to be adapted to more than one parameter identification problem. |
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