Markov chain splitting methods in structural reliability integral estimation

Kanjilal, Oindrila and Manohar, CS (2015) Markov chain splitting methods in structural reliability integral estimation. In: PROBABILISTIC ENGINEERING MECHANICS, 40 . pp. 42-51.

PDF Pro_Eng_Mech-40-42-2015.pdf - Published Version Restricted to Registered users only Download (1MB) | Request a copy

Abstract

Monte Carlo simulation methods involving splitting of Markov chains have been used in evaluation of multi-fold integrals in different application areas. We examine in this paper the performance of these methods in the context of evaluation of reliability integrals from the point of view of characterizing the sampling fluctuations. The methods discussed include the Au-Beck subset simulation, Holmes-Diaconis-Ross method, and generalized splitting algorithm. A few improvisations based on first order reliability method are suggested to select algorithmic parameters of the latter two methods. The bias and sampling variance of the alternative estimators are discussed. Also, an approximation to the sampling distribution of some of these estimators is obtained. Illustrative examples involving component and series system reliability analyses are presented with a view to bring out the relative merits of alternative methods. (C) 2015 Elsevier Ltd. All rights reserved.

Item Type:	Journal Article
Publication:	PROBABILISTIC ENGINEERING MECHANICS
Publisher:	ELSEVIER SCI LTD
Additional Information:	Copy right for this article belongs to the ELSEVIER SCI LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND
Keywords:	Markov chain Monte Carlo; Reliability integral; Particle splitting; Variance reduction
Department/Centre:	Division of Mechanical Sciences > Chemical Engineering
Date Deposited:	16 Jun 2015 05:27
Last Modified:	16 Jun 2015 05:27
URI:	http://eprints.iisc.ac.in/id/eprint/51704

Actions (login required)

View Item