Acoplamento SPIM-FEM adaptativo para modelos de degradação elástica

• Ano de defesa: 2022
• Autor(a) principal: Samir Silva Saliba
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; Brasil; ENG - DEPARTAMENTO DE ENGENHARIA ESTRUTURAS; Programa de Pós-Graduação em Engenharia de Estruturas; UFMG
• Palavras-chave em Português: Método dos elementos finitos; Método sem malha; Smoothed point interpolation method; Acoplamento; Meios parcialmente frágeis; Degradação elástica
• Link de acesso: http://hdl.handle.net/1843/51556

This thesis proposes a new approach to performing a physically nonlinear analysis of structures constituted by quasi-brittle material employing a coupling between the smoothed point interpolation method (SPIM) and the finite element method (FEM). This coupling is performed using different smoothing strategies: cell-based, edge-based, or node-based, without any restriction for the adoption of the point interpolation method (PIM) to build the shape function or for the support domain construction strategy. This approach aims to obtain, during a simulation, relevant advantages to each of the methods applied in the coupling and constitutive model. Then, with this purpose two strategies were proposed: in the first, the domain is discretized through the two methods, with the SPIM region being defined by the user; in the second, the domain starts discretized only by finite elements, and during the analysis, regions are converted to SPIM and refined automatically through parameters responsible for informing the system the location, size of the region and the moment in which this task should be performed. This work was implemented in the INSANE system (INteractive Structural Analysis Environment), which is an open-source software developed by the Structural Engineering Department of the Federal University of Minas Gerais. Numerical simulations present the resources of the implemented approaches and compare the results obtained with experimental and numerical results, widely discussed and evaluated in the academic environment, to demonstrate the ability to reproduce the expected results and validate the implementation.