Study on Parameter Optimization of a Nonlinear Material Model of Structural Steel
| Autor: | Ming-Yao Chang, 張明堯 |
|---|---|
| Rok vydání: | 2019 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 107 Because of the high cost of structural experiments, researchers usually use real experimental data to build numerical models to simulate the reactions. To build a reliable numerical model, researchers will use the nonlinear material model to make the simulation as much as possible to be real. It will spend a lot of time to find the most suitable parameters of the nonlinear material model by trial and error. In this study, the optimization methods are used to estimate the parameters of the combined hardening nonlinear material model in order to reduce the time it takes for researchers. This study used two methods of optimization, Particle Swarm Optimization (PSO) and Symbiotic Organisms Search (SOS), to find the most suitable parameters of the combined hardening model in Abaqus by MATLAB as the programming platform, and to verify the feasibility by the real experiments. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
| Externí odkaz: |
|