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contributor authorYoojeong Noh
contributor authorKyung K. Choi
contributor authorIkjin Lee
contributor authorDavid Gorsich
contributor authorDavid Lamb
date accessioned2017-05-09T00:45:44Z
date available2017-05-09T00:45:44Z
date copyrightSeptember, 2011
date issued2011
identifier issn1050-0472
identifier otherJMDEDB-27952#091001_1.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/146995
description abstractFor reliability-based design optimization (RBDO), generating an input statistical model with confidence level has been recently proposed to offset inaccurate estimation of the input statistical model with Gaussian distributions. For this, the confidence intervals for the mean and standard deviation are calculated using Gaussian distributions of the input random variables. However, if the input random variables are non-Gaussian, use of Gaussian distributions of the input variables will provide inaccurate confidence intervals, and thus yield an undesirable confidence level of the reliability-based optimum design meeting the target reliability βt. In this paper, an RBDO method using a bootstrap method, which accurately calculates the confidence intervals for the input parameters for non-Gaussian distributions, is proposed to obtain a desirable confidence level of the output performance for non-Gaussian distributions. The proposed method is examined by testing a numerical example and M1A1 Abrams tank roadarm problem.
publisherThe American Society of Mechanical Engineers (ASME)
titleReliability-Based Design Optimization With Confidence Level for Non-Gaussian Distributions Using Bootstrap Method
typeJournal Paper
journal volume133
journal issue9
journal titleJournal of Mechanical Design
identifier doi10.1115/1.4004545
journal fristpage91001
identifier eissn1528-9001
keywordsEngineering standards
keywordsDesign
keywordsGaussian distribution
keywordsProbability
keywordsReliability-based optimization AND Reliability
treeJournal of Mechanical Design:;2011:;volume( 133 ):;issue: 009
contenttypeFulltext


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