NDLI: Design Sensitivity Method for Sampling-Based RBDO With Fixed COV

Content Provider	The American Society of Mechanical Engineers (ASME) Digital Collection
Author	Cho, Hyunkyoo Choi, K. K. Lee, Ikjin Lamb, David
Copyright Year	2015
Abstract	Conventional reliability-based design optimization (RBDO) uses the means of input random variables as its design variables; and the standard deviations (STDEVs) of the random variables are fixed constants. However, the fixed STDEVs may not correctly represent certain RBDO problems well, especially when a specified tolerance of the input random variable is presented as a percentage of the mean value. For this kind of design problem, the coefficients of variations (COVs) of the input random variables should be fixed, which means STDEVs are not fixed. In this paper, a method to calculate the design sensitivity of probability of failure for RBDO with fixed COV is developed. For sampling-based RBDO, which uses Monte Carlo simulation for reliability analysis, the design sensitivity of the probability of failure is derived using a first-order score function. The score function contains the effect of the change in the STDEV in addition to the change in the mean. As copulas are used for the design sensitivity, correlated input random variables also can be used for RBDO with fixed COV. Moreover, the design sensitivity can be calculated efficiently during the evaluation of the probability of failure. Using a mathematical example, the accuracy and efficiency of the developed method are verified. The RBDO result for mathematical and physical problems indicates that the developed method provides accurate design sensitivity in the optimization process.
Sponsorship	Design Engineering Division Computers and Information in Engineering Division
File Format	PDF
ISBN	9780791857083
DOI	10.1115/DETC2015-47359
Volume Number	Volume 2B: 41st Design Automation Conference
Conference Proceedings	ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
Language	English
Publisher Date	2015-08-02
Publisher Place	Boston, Massachusetts, USA
Access Restriction	Subscribed
Subject Keyword	Design Reliability-based optimization Simulation Probability Event history analysis Failure Optimization
Content Type	Text
Resource Type	Article

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