A model to simulate multidimensional nonstationary and non-Gaussian fields based on S-transform

In many cases, the probabilistic assessment of structure and infrastructure systems requires the modeling and simulation of nonstationary or nonhomogeneous and non-Gaussian random fields. In the present study, we propose an iterative algorithm to simulate multidimensional nonstationary and non-Gaussian random fields. It uses the S-transform that has the advantage of providing good time (or space) localized high frequency resolu-tion and good low frequency resolution. The algorithm iteratively adjusts time-frequency (or space-wavenumber) dependent power spectral density function of the nonstationary random field and the amplitude of the random field according to the marginal probability distribution of the field. The algorithm is efficient and usually converges within less than ten iterations for practical problems. The application of the proposed algorithm is shown by three numerical examples of practical interest. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

An iterative algorithm is proposed in this study to simulate multidimensional nonstationary and non-Gaussian random fields, which is efficient and converges quickly. The application of the algorithm is demonstrated through three numerical examples of practical interest.