Digital Generation of Non‐Gaussian Stochastic Fields

Abstract

A method by which sample fields of a multidimensional non‐Gaussian homogeneous stochastic field can be generated is developed. The method first generates Gaussian sample fields and then maps them into non‐Gaussian sample fields with the aid of an iterative procedure. Numerical examples indicate that the procedure is very efficient and generated sample fields satisfy the target spectral density and probability distribution function accurately. The proposed method has a wide range of applicability to engineering problems involving stochastic fields where the Gaussian assumption is not appropriate.