Polynomial Chaos Decomposition for the Simulation of Non-Gaussian Nonstationary Stochastic Processes
- 1 February 2002
- journal article
- Published by American Society of Civil Engineers (ASCE) in Journal of Engineering Mechanics
- Vol. 128 (2) , 190-201
- https://doi.org/10.1061/(asce)0733-9399(2002)128:2(190)
Abstract
A method is developed for representing and synthesizing random processes that have been specified by their two-point correlation function and their nonstationary marginal probability density functions. The target process is represented as a polynomial transformation of an appropriate Gaussian process. The target correlation structure is decomposed according to the Karhunen–Loève expansion of the underlying Gaussian process. A sequence of polynomial transformations in this process is then used to match the one-point marginal probability density functions. The method results in a representation of a stochastic process that is particularly well suited for implementation with the spectral stochastic finite element method as well as for general purpose simulation of realizations of these processes.Keywords
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