Time variant reliability model updating in instrumented dynamical systems based on Girsanov's transformation

Sundar, VS and Manohar, CS (2013) Time variant reliability model updating in instrumented dynamical systems based on Girsanov's transformation. In: International Journal of Non-Linear Mechanics, 52 . pp. 32-40.

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Abstract

The problem of updating the reliability of instrumented structures based on measured response under random dynamic loading is considered. A solution strategy within the framework of Monte Carlo simulation based dynamic state estimation method and Girsanov's transformation for variance reduction is developed. For linear Gaussian state space models, the solution is developed based on continuous version of the Kalman filter, while, for non-linear and (or) non-Gaussian state space models, bootstrap particle filters are adopted. The controls to implement the Girsanov transformation are developed by solving a constrained non-linear optimization problem. Numerical illustrations include studies on a multi degree of freedom linear system and non-linear systems with geometric and (or) hereditary non-linearities and non-stationary random excitations.

Item Type:	Journal Article
Publication:	International Journal of Non-Linear Mechanics
Publisher:	Elsevier Science
Additional Information:	Copyright of this article belongs to Elsevier Science.
Keywords:	Existing Structures; Reliability Model Updating; Girsanov's Transformation; Monte Carlo Method; Random Processes
Department/Centre:	Division of Mechanical Sciences > Civil Engineering
Date Deposited:	11 Jun 2013 07:57
Last Modified:	11 Jun 2013 07:57
URI:	http://eprints.iisc.ac.in/id/eprint/46629

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