Abstract
A method to carry out reliability-based optimization of uncertain structural systems under stochastic excitation is presented. The approach is based on a nonlinear interior point algorithm and a line search strategy. The associated reliability problems to be solved during the optimization process are high dimensional (thousands or more random variables). An advanced Monte Carlo simulation is adopted for the purpose of estimating the corresponding failure probabilities and their sensitivities (gradients). Numerical results show that only a small number of reliability estimates has to be performed during the entire design process. An example problem that consider a nonlinear eleven-story building model under earthquake excitation is presented to illustrate the effectiveness of the approach reported herein.
| Original language | English |
|---|---|
| Title of host publication | 2nd International Conference on Engineering Optimization |
| Number of pages | 9 |
| Publication date | Sept 2010 |
| Publication status | Published - Sept 2010 |
| Externally published | Yes |
Keywords
- : First order scheme
- Reliability analysis
- Sensitivity analysis
- Simulation procedures