A Re-Analysis Methodology for System RBDO Using a Trust Region Approach with Local Metamodels 2010-01-0645
A simulation-based, system reliability-based design optimization (RBDO) method is presented that can handle problems with multiple failure regions and correlated random variables. Copulas are used to represent the correlation. The method uses a Probabilistic Re-Analysis (PRRA) approach in conjunction with a trust-region optimization approach and local metamodels covering each trust region. PRRA calculates very efficiently the system reliability of a design by performing a single Monte Carlo (MC) simulation per trust region. Although PRRA is based on MC simulation, it calculates “smooth” sensitivity derivatives, allowing therefore, the use of a gradient-based optimizer. The PRRA method is based on importance sampling. It provides accurate results, if the support of the sampling PDF contains the support of the joint PDF of the input random variables. The sequential, trust-region optimization approach satisfies this requirement. Local metamodels are constructed sequentially for each trust region taking advantage of the potential overlap of the trust regions. The metamodels are used to determine the value of the indicator function in MC simulation. An example with correlated input random variables demonstrates the accuracy and efficiency of the proposed RBDO method.
Ramon Kuczera, Zissimos Mourelatos, Efstratios Nikolaidis
Oakland Univ., Univ. of Toledo
SAE 2010 World Congress & Exhibition
SAE International Journal of Materials and Manufacturing-V119-5, Reliability and Robust Design in Automotive Engineering, 2010-SP-2272, SAE International Journal of Materials and Manufacturing-V119-5EJ
Simulation and modeling
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