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Approximation methods for reliability‐based design optimization problems
Author(s) -
Kaymaz Irfan
Publication year - 2007
Publication title -
gamm‐mitteilungen
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.239
H-Index - 18
eISSN - 1522-2608
pISSN - 0936-7195
DOI - 10.1002/gamm.200790017
Subject(s) - probabilistic logic , reliability (semiconductor) , constraint (computer aided design) , mathematical optimization , reliability engineering , probabilistic design , computer science , function (biology) , probabilistic analysis of algorithms , optimal design , engineering design process , engineering , mathematics , machine learning , mechanical engineering , power (physics) , physics , quantum mechanics , artificial intelligence , evolutionary biology , biology
Deterministic optimum designs are obtained without considering of uncertainties related to the problem parameters such as material parameters (yield stress, allowable stresses, moment capacities, etc.), external loadings, manufacturing errors, tolerances, cost functions, which could lead to unreliable designs, therefore several methods have been developed to treat uncertainties in engineering analysis and, more recently, to carry out design optimization with the additional requirement of reliability, which referred to as reliability‐based design optimization. In this paper, two most common approaches for reliability‐based design optimization are reviewed, one of which is reliability‐index based approach and the other performancemeasure approach. Although both approaches can be used to evaluate the probabilistic constraint, their use can be prohibitive when the associated function evaluation required by the probabilistic constraint is expensive, especially for real engineering problems. Therefore, an adaptive response surface method is proposed by which the probabilistic constraint is replaced with a simple polynomial function, thus the computational time can be reduced significantly as presented in the example given in this paper. (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)