Multivariate Extreme Value Distributions for Random Vibration Applications
Publication: Journal of Engineering Mechanics
Volume 131, Issue 7
Abstract
The problem of determining the joint probability distribution of extreme values associated with a vector of stationary Gaussian random processes is considered. A solution to this problem is developed by approximating the multivariate counting processes associated with the number of level crossings as a multivariate Poisson random process. This, in turn, leads to approximations to the multivariate probability distributions for the first passage times and extreme values over a given duration. It is shown that the multivariate extreme value distribution has Gumbel marginal and the first passage time has exponential marginal. The acceptability of the solutions developed is examined by performing simulation studies on bivariate Gaussian random processes. Illustrative examples include a discussion on the response analysis of a two span bridge subjected to spatially varying random earthquake support motions.
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Acknowledgment
The work reported in this paper forms a part of the research project entitled “Seismic probabilistic safety assessment of nuclear power plant structures,” funded by the Board of Research in Nuclear Sciences, Department of Atomic Energy, Government of India.
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© 2005 ASCE.
History
Received: Mar 2, 2004
Accepted: Oct 20, 2004
Published online: Jul 1, 2005
Published in print: Jul 2005
Notes
Note. Associate Editor: Gerhart I. Schueller
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