Extreme Value Metamodeling for System Reliability with Time-Dependent Functions

Abstract

The reliability of a system is usually measured by the probability that the system performs its intended function in a given period of time. Estimating such reliability is a challenging task when the probability of failure is rare and the responses are nonlinear and time variant. The evaluation of the system reliability defined in a period of time requires the extreme values of the responses in the predefined period of time during which the system is supposed to function. This work builds surrogate models for the extreme values of responses with the Kriging method. For the sake of computational efficiency, the method creates Kriging models with high accuracy only in the region that has high contributions to the system failure; training points of random variables and time are sampled simultaneously so that their interactions could be considered automatically. The example of a mechanism system shows the effectiveness of the proposed method.

Meeting Name

ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (2015: Aug. 2-5, Boston, MA)

Department(s)

Mechanical and Aerospace Engineering

Keywords and Phrases

Computational efficiency; Computer aided design; Design; Interpolation; Systems engineering; Kriging methods; Mechanism systems; Probability of failure; Surrogate model; System failures; System reliability; Time-dependent functions; Training points; Reliability

International Standard Book Number (ISBN)

978-0791857083

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2015 American Society of Mechanical Engineers (ASME), All rights reserved.

Publication Date

01 Aug 2015

Link to Full Text

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