Generating high fidelity wind fields from the wind speed correlation tensor

Abstract

In this publication a new method to generate stochastic representations of homogeneous and isotropic wind fields is presented. In contrast to the typically employed algorithm, the new approach is based on the wind speed correlation tensor. This allows simulating a homogeneous and isotropic turbulent wind field with very high accuracy. In this publication, a deviation of the obtained dataset's structure function from the theoretical one of at least one order of magnitude lower than the commonly used method is achieved. Furthermore, a compensation method to decrease this error even further is proposed. Moreover, being a generic method, it can be used to simulate other Gaussian phenomena (e.g., temperature or index of refraction fluctuations) on various spatial domains and grid shapes.