NDLI: An inverse analysis method for design optimization with both statistical and fuzzy uncertainties

Content Provider	Springer Nature Link
Author	Du, Liu Choi, K. K.
Copyright Year	2008
Abstract	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.
Starting Page	107
Ending Page	119
Page Count	13
File Format	PDF
ISSN	1615147X
Journal	Structural and Multidisciplinary Optimization
Volume Number	37
Issue Number	2
e-ISSN	16151488
Language	English
Publisher	Springer-Verlag
Publisher Date	2008-02-13
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	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 α-cut Fuzzy variable Conditional possibility Engineering Design Computational Mathematics and Numerical Analysis Theoretical and Applied Mechanics
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Computer Graphics and Computer-Aided Design Control and Systems Engineering Computer Science Applications Software

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