Efficient stationary multivariate non-Gaussian simulation based on a Hermite PDF model. (October 2015)

• Record Type: Journal Article
• Authors: Yang, Luping; Gurley, Kurtis R.
• Is Part Of: Probabilistic engineering mechanics. Volume 42(2015:Oct.)
• Page Start: 31
• Page End: 41
• Publication Date: 2015-10
• Subjects: Monte Carlo simulation -- Non-Gaussian -- Hermite polynomials -- Translation processes -- Correlation distortion; Engineering -- Statistical methods -- Periodicals; Mechanics, Applied -- Statistical methods -- Periodicals; Probabilities -- Periodicals; Ingénierie -- Méthodes statistiques -- Périodiques; Mécanique appliquée -- Méthodes statistiques -- Périodiques; Probabilités -- Périodiques; 620.100727
• DOI: 10.1016/j.probengmech.2015.09.006
• Languages: English
• ISSNs: 0266-8920

Abstract

Abstract: An efficient stationary multivariate non-Gaussian simulation method is developed using spectral representation and third order Hermite polynomial translation. An approximate closed form relationship is employed to identify the Hermite translation parameters based on target skewness and kurtosis. This preserves a high degree of accuracy over the entire admissible range of the Hermite translation, and eliminates the need for iterative solution of the translation parameters. The Hermite PDF model is suitable for a wide range of strongly non-Gaussian stochastic process. In addition, an explicit bidirectional relationship between the target non-Gaussian and Gaussian correlation is developed to eliminate the need for iteration or numerical integration to identify the underlying Gaussian correlation. Examples apply the simulation method to both theoretical targets and experimental wind pressure data.