Open Collections

Simulation of strongly non-Gaussian non-stationary stochastic processes utilizing Karhunen-Loeve expansion

International Conference on Applications of Statistics and Probability (12th : 2015 : Vancouver, B.C.)

The simulation of non-stationary and non-Gaussian stochastic processes is a challenging problem of considerable practical interest. Recently, Shields et al. have developed a class of conceptually simple and efficient methods for simulation of non-Gaussian processes using translation process theory (collectively referred to as the Iterative Translation Approximation Method - ITAM) that iteratively upgrades the underlying Gaussian power spectral density function for simulation using the spectral representation method. However, the currently existing ITAM method for generation of non-stationary and non-Gaussian processes requires additional approximations in the estimation of the evolutionary spectrum. An extension of the ITAM is proposed that utilizes the K-L expansion. The developed method iteratively upgrades the covariance function directly and, in so doing, avoids the complex and non-unique inverse problem of estimating the evolutionary spectrum from the non-stationary autocorrelation. The application of the method for a strongly non-Gaussian and non-stationary process with a prescribed target non-Gaussian correlation function is demonstrated.

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This collection contains the proceedings of ICASP12, the 12th International Conference on Applications of Statistics and Probability in Civil Engineering held in Vancouver, Canada on July 12-15, 2015. Abstracts were peer-reviewed and authors of accepted abstracts were invited to submit full papers. Also full papers were peer reviewed. The editor for this collection is Professor Terje Haukaas, Department of Civil Engineering, UBC Vancouver.

Vancouver : University of British Columbia Library

10.14288/1.0076040

Non UBC

Unreviewed

http://creativecommons.org/licenses/by-nc-nd/2.5/ca/