Proceedings ArticleDOI
Experience with Approximate Reliability-Based Optimization Methods
Ren-Jye Yang,Lei Gu +1 more
TLDR
In this paper, several approximate RBDO methods are coded, discussed, and tested against a double loop algorithm through four design problems, and they are compared to a single loop algorithm.Abstract:
Traditional reliability-based design optimization (RBDO) requires a double loop iteration process. The inner optimization loop is to find the most probable point (MPP) and the outer is the regular optimization loop to optimize the RBDO problem with reliability objectives or constraints. It is well known that the computation can be prohibitive when the associated function evaluation is expensive. As a result, many approximate RBDO methods, which convert the double loop to a single loop, have been developed. In this work, several approximate RBDO methods are coded, discussed, and tested against a double loop algorithm through four design problems.read more
Citations
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Journal ArticleDOI
A survey on approaches for reliability-based optimization
TL;DR: This contribution provides a survey on approaches for performing Reliability-based Optimization, with emphasis on the theoretical foundations and the main assumptions involved.
Journal ArticleDOI
Reliability-Based Optimization Using Evolutionary Algorithms
TL;DR: In this paper, the authors demonstrate how classical reliability-based concepts can be borrowed and modified and, with integrated single and multiobjective evolutionary algorithms, used to enhance their scope in handling uncertainties involved among decision variables and problem parameters.
Journal ArticleDOI
Reliability Estimation and Design with Insufficient Data Based on Possibility Theory
Zissimos P. Mourelatos,Jun Zhou +1 more
TL;DR: In this work, the possibility theory is used to assess design reliability with incomplete information, and a possibility-based design optimization method is proposed where all design constraints are expressed in a possibilistic way.
Journal ArticleDOI
MDO: assessment and direction for advancement— an opinion of one international group
Jeremy S. Agte,Olivier de Weck,Jaroslaw Sobieszczanski-Sobieski,Paul Arendsen,Alan Morris,Martin Spieck +5 more
TL;DR: The 2006 European-U.S. Multidiscipli-nary Optimization (MDO) Colloquium in Goettingen, Germany, was attended by nearly seventy professionals from academia, industry, and government as discussed by the authors.
Journal ArticleDOI
Component and system reliability-based topology optimization using a single-loop method
TL;DR: In this article, reliability-based topology optimization by combining reliability analysis and material distribution topology design methods to design linear elastic structures subject to random inputs, such as random loadings, is considered.
References
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Journal ArticleDOI
Sequential Optimization and Reliability Assessment Method for Efficient Probabilistic Design
Xiaoping Du,Wei Chen +1 more
TL;DR: The sequential optimization and reliability assessment (SORA) as mentioned in this paper method employs a single-loop strategy, where a serial of cycles of optimization and assessment is employed, and the reliability assessment is decoupled from each other.
Journal ArticleDOI
Hybrid Analysis Method for Reliability-Based Design Optimization
TL;DR: It is shown that PMA with a spherical equality constraint is easier to solve than RIA with a complicated equality constraint in estimating the probabilistic constraint in the RBDO process.
Proceedings ArticleDOI
Reliability based structural design optimization for practical applications
TL;DR: A new method for reliabilitybased optimization which requires only a modest increase in computational cost over that of deterministic design optimization, and appears to be robust in terms of convergence from arbitrarily selected initial design points to the solutions determined by existing methods.
Journal ArticleDOI
Optimization and robustness for crashworthiness of side impact
TL;DR: In this paper, a nonlinear response surface-based safety optimization and robustness process is presented, where stepwise regression and optimal Latin hyper cube sampling methods are employed to construct the "efficient-to-compute" surrogate model.