An RBDO Method for Multiple Failure Region Problems using Probabilistic Reanalysis and Approximate Metamodels
Date Published: 2009-04-20
Paper Number:2009-01-0204
DOI: 10.4271/2009-01-0204
Citation:
Kuczera, R., Mourelatos, Z., Latcha, M., and Nikolaidis, E., "An RBDO Method for Multiple Failure Region Problems using Probabilistic Reanalysis and Approximate Metamodels," SAE Int. J. Mater. Manuf. 2(1):108-120, 2009, doi:10.4271/2009-01-0204.
A Reliability-Based Design Optimization (RBDO) method for multiple failure regions is presented. The method uses a Probabilistic Re-Analysis (PRRA) approach in conjunction with an approximate global metamodel with local refinements. The latter serves as an indicator to determine the failure and safe regions. PRRA calculates very efficiently the system reliability of a design by performing a single Monte Carlo (MC) simulation. Although PRRA is based on MC simulation, it calculates “smooth” sensitivity derivatives, allowing therefore, the use of a gradient-based optimizer. An “accurate-on-demand” metamodel is used in the PRRA that allows us to handle problems with multiple disjoint failure regions and potentially multiple most-probable points (MPP). The multiple failure regions are identified by using a clustering technique. A maximin “space-filling” sampling technique is used to construct the metamodel. A vibration absorber example highlights the potential of the proposed method.
See papers presented at SAE World Congress & Exhibition, April 2009, Detroit, MI, USA, Session: Reliability and Robust Design in Automotive Engineering: Reliability-Based Design Optimization and Robustness
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