Synthesis of realistic non-homogeneous non-Gaussian turbulent wind fields

Abstract

This paper presents a sequential method for generating synthetic non-homogeneous non-Gaussian turbulent wind fields with a prescribed time-space covariance structure. The proposed methodology is based on the optimisation of restricted multivariate autoregressive (VAR) models, and the quantile-to-quantile transform between statistical distributions. The considered case study is a non-homogeneous non-Gaussian turbulent wind field over the roof of a high rise building simulated with LES. Results show a notably good matching in terms of the reproduced wind statistical distributions, Covariance Matrix Function (CMF) and Cross Power Spectral Density Matrix (CPSDM). In addition, the synthetic wind field reproduced accurately the recirculation bubble close to the roof. The main advantages of the proposed method are that, once the VAR model is computed, the synthesis of several realisations is computationally very cheap, which is useful for performing several aeroelastic simulations of the same analysis case, as suggested by the standards. The critical point is that, to characterise the statistical features for a specific case study (such as wind turbine wakes or turbulence due to obstacles), an LES simulation of the wind field is required as input. The software employed in this work is open source and it is available on GitHub.