Simulation of non-Gaussian wind field as a $3^{rd}$-order stochastic wave

TL;DR

This paper introduces a third-order spectral method for efficiently simulating non-Gaussian wind fields as stochastic waves, capturing asymmetry and skewness, with applications to long-span bridge wind modeling.

Contribution

It extends the classical spectral representation to third-order, enabling realistic non-Gaussian wind field simulations with improved computational efficiency.

Findings

Efficient third-order spectral simulation method developed.

Successfully applied to wind field modeling along a bridge.

Significantly reduces computational time compared to traditional methods.

Abstract

This paper presents a methodology for the simulation of non-Gaussian wind field as a stochastic wave using the 3rd-order Spectral Representation Method. Traditionally, the wind field is modeled as a stochastic vector process at discrete locations in space. But the simulation of vector process is well-known to be computationally challenging and numerically unstable when modeling wind at a large number of discrete points in space. Recently, stochastic waves have been used to model the field as a continuous process indexed both in time and space. We extend the classical Spectral Representation Method for simulation of Gaussian stochastic waves to a third-order representation modeling asymmetrically skewed non-Gaussian stochastic waves from a prescribed power spectrum and bispectrum. We present an efficient implementation using the fast Fourier transform, which reduces the computational time dramatically. We then apply the method for simulation of a non-Gaussian wind velocity field along a long-span bridge.