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Effects of Turbulence Modeling on the Simulation of Wind Flow over Typical Complex Terrains.

Authors :
Ma, Guolin
Tian, Linlin
Song, Yilei
Zhao, Ning
Source :
Applied Sciences (2076-3417); Dec2024, Vol. 14 Issue 23, p11438, 23p
Publication Year :
2024

Abstract

The correct prediction of the wind speed and turbulence levels over complex terrain is essential for accurately assessing wind turbine wake recovery, power production, safety, and wind farm design. In this paper, two modified RANS turbulence models are proposed, which are innovative variants of the conventional SST k-ω model and the linear Reynolds stress model (RSM) featuring optimized closure constants. Then, these two modified models and their origin models are applied to compare and analyze wind flows from a 3D hill wind tunnel experiment and two field measurements over typical complex terrain, including Askervein hill and Bolund island, with the aim of analyzing the sensitivity of wind flows to different RANS turbulence models. The study focuses on analyzing the effects of different turbulence models on the self-sustainability of wind speed and turbulent kinetic energy upstream of the computational domain and on the accuracy of wind flow prediction over complex terrain. The results show that our modified RSM model shows better agreement with the available experimental data on the upstream and leeward sides of all simulated hills. The wind speed on the leeward slope is particularly sensitive to the turbulence model, with a maximum difference in the relative root mean square error (RRMSE) that can reach 11% among the four models. The accuracy of the turbulent kinetic energy depends on the self-sustainability of the upstream turbulent kinetic energy and the predictive ability of the turbulence model for separated flows, and the maximum difference in the RRMSE of the four models can reach 47%. In addition, the advantages and disadvantages of the tested models are discussed to provide guidance for model selection during wind flow simulations in complex terrain. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763417
Volume :
14
Issue :
23
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
181655744
Full Text :
https://doi.org/10.3390/app142311438