Estimation of time-variant system reliability of nonlinear randomly excited systems based on the Girsanov transformation with state-dependent controls

Kanjilal, Oindrila and Manohar, CS (2019) Estimation of time-variant system reliability of nonlinear randomly excited systems based on the Girsanov transformation with state-dependent controls. In: NONLINEAR DYNAMICS, 95 (2). pp. 1693-1711.

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Abstract

The problem of time-variant system reliability analysis of nonlinear dynamical systems subjected to random excitations is considered. The governing equations are formulated as a set of Ito's stochastic differential equations. Subsequently, a Monte Carlo simulation strategy, which incorporates Girsanov's transformation- based variance reduction step, is developed. The novel element of the work lies in the formulation of state-dependent Girsanov's control forces for estimating the system reliability. The study considers failure modes arranged in series, parallel, or composite configurations. Illustrative examples include studies on a 5-dof Duffing's system and an inelastic frame subjected to multi-support, non-stationary, Gaussian excitations. The numerical results demonstrate significant variance reduction achieved in estimating low probabilities of failure.

Item Type:	Journal Article
Publication:	NONLINEAR DYNAMICS
Publisher:	SPRINGER
Additional Information:	Copyright of this article belongs to SPRINGER
Keywords:	Time-variant system reliability; Monte Carlo simulation; Importance sampling; Girsanov's transformation
Department/Centre:	Division of Mechanical Sciences > Civil Engineering
Date Deposited:	15 May 2019 11:08
Last Modified:	15 May 2019 11:08
URI:	http://eprints.iisc.ac.in/id/eprint/62347

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