Journal
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
Volume 37, Issue 2, Pages 107-119Publisher
SPRINGER
DOI: 10.1007/s00158-007-0225-0
Keywords
Mixed-variable design optimization (MVDO); Maximal failure search (MFS); Possibility-based design optimization (PBDO); Maximal possibility search (MPS); Performance measure approach (PMA); Inverse analysis for MVDO; alpha-cut; Fuzzy variable; Conditional possibility
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Funding
- Automotive Research Center
- US Army Tank and Automotive Research, Development and Engineering Center
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If the statistical data for the input uncertainties are sufficient to construct the distribution function, the input uncertainties can be treated as random variables to use the reliability-based design optimization (RBDO) method; otherwise, the input uncertainties can be treated as fuzzy variables to use the possibility-based design optimization (PBDO) method. However, many structural design problems include both input uncertainties with sufficient and insufficient data. This paper proposes a new mixed-variable design optimization (MVDO) method using the performance measure approach (PMA) for such design problems. For the inverse analysis, this paper proposes a new most probable/possible point (MPPP) search method called maximal failure search (MFS), which is an integration of the enhanced hybrid mean value method (HMV+) and maximal possibility search (MPS) method. This paper also improves the HMV+ method using an angle-based interpolation. Mathematical and physical examples are used to demonstrate the proposed inverse analysis method and MVDO method.
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