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Research Papers: Design Automation

A Single-Loop Kriging Surrogate Modeling for Time-Dependent Reliability Analysis

[+] Author and Article Information
Zhen Hu

Department of Civil and Environmental
Engineering,
Vanderbilt University,
279 Jacobs Hall,
VU Mailbox: PMB 351831,
Nashville, TN 37235
e-mail: zhen.hu@vanderbilt.edu

Sankaran Mahadevan

Professor
Department of Civil and Environmental
Engineering,
Vanderbilt University,
272 Jacobs Hall,
VU Mailbox: PMB 351831,
Nashville, TN 37235
e-mail: sankaran.mahadevan@vanderbilt.edu

1Corresponding author.

Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received October 26, 2015; final manuscript received April 12, 2016; published online May 4, 2016. Assoc. Editor: Xiaoping Du.

J. Mech. Des 138(6), 061406 (May 04, 2016) (10 pages) Paper No: MD-15-1727; doi: 10.1115/1.4033428 History: Received October 26, 2015; Revised April 12, 2016

Current surrogate modeling methods for time-dependent reliability analysis implement a double-loop procedure, with the computation of extreme value response in the outer loop and optimization in the inner loop. The computational effort of the double-loop procedure is quite high even though improvements have been made to improve the efficiency of the inner loop. This paper proposes a single-loop Kriging (SILK) surrogate modeling method for time-dependent reliability analysis. The optimization loop used in current methods is completely removed in the proposed method. A single surrogate model is built for the purpose of time-dependent reliability assessment. Training points of random variables and over time are generated at the same level instead of at two separate levels. The surrogate model is refined adaptively based on a learning function modified from time-independent reliability analysis and a newly developed convergence criterion. Strategies for building the surrogate model are investigated for problems with and without stochastic processes. Results of three numerical examples show that the proposed single-loop procedure significantly increases the efficiency of time-dependent reliability analysis without sacrificing the accuracy.

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Figures

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Fig. 2

Illustration of crossing points

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Fig. 4

Effect of correlation threshold on clustering of training points: (a) without correlation threshold and (b) with correlation threshold

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Fig. 3

A four-bar function generator mechanism

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Fig. 5

Corroded beam subjected to stochastic load

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