Simulation of non-stationary and non-Gaussian random processes by 3rd-order Spectral Representation Method: Theory and POD implementation
Statistics Theory
2022-06-01 v1 Statistics Theory
Abstract
This paper introduces the -order Spectral Representation Method for simulation of non-stationary and non-Gaussian stochastic processes. The proposed method extends the classical -order Spectral Representation Method to expand the stochastic process from an evolutionary bispectrum and an evolutionary power spectrum, thus matching the process completely up to third-order. A Proper Orthogonal Decomposition (POD) approach is further proposed to enable an efficient FFT-based implementation that reduces computational cost significantly. Two examples are presented, including the simulation of a fully non-stationary seismic ground motion process, highlighting the accuracy and efficacy of the proposed method.
Keywords
Cite
@article{arxiv.2109.13689,
title = {Simulation of non-stationary and non-Gaussian random processes by 3rd-order Spectral Representation Method: Theory and POD implementation},
author = {Lohit Vandanapu and Michael D. Shields},
journal= {arXiv preprint arXiv:2109.13689},
year = {2022}
}
Comments
38 pages, 9 figures, 2 tables