Fractional Spectral Moments for Digital Simulation of Multivariate Wind Velocity Fields

TL;DR

This paper introduces a novel method using fractional spectral moments and generalized Taylor expansion to digitally simulate multivariate wind velocity fields, enabling more accurate modeling of complex wind behaviors.

Contribution

It presents a new simulation technique based on fractional spectral moments and extends it to multivariate processes, improving wind field modeling accuracy.

Findings

Effective simulation of wind velocity fields demonstrated.

Method extends to multivariate processes.

Practical implementation issues addressed.

Abstract

In this paper, a method for the digital simulation of wind velocity fields by Fractional Spectral Moment function is proposed. It is shown that by constructing a digital filter whose coefficients are the fractional spectral moments, it is possible to simulate samples of the target process as superposition of Riesz fractional derivatives of a Gaussian white noise processes. The key of this simulation technique is the generalized Taylor expansion proposed by the authors. The method is extended to multivariate processes and practical issues on the implementation of the method are reported.