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Modelling turbulence in axisymmetric wakes: an application to wind turbine wakes

Bastankhah, Majid, Zunder, Jenna K., Hydon, Peter E., Deebank, Charles, Placidi, Marco (2024) Modelling turbulence in axisymmetric wakes: an application to wind turbine wakes. Journal of Fluid Mechanics, 1000 . Article Number A2. ISSN 0022-1120. (doi:10.1017/jfm.2024.664) (KAR id:107925)

Abstract

A novel fast-running model is developed to predict the three-dimensional (3-D) distribution of turbulent kinetic energy (TKE) in axisymmetric wake flows. This is achieved by mathematically solving the partial differential equation of the TKE transport using the Green's function method. The developed solution reduces to a double integral that can be computed numerically for a wake prescribed by any arbitrary velocity profile. It is shown that the solution can be further simplified to a single integral for wakes with Gaussian-like velocity-deficit profiles. Wind tunnel experiments were performed to compare model results against detailed 3-D laser Doppler anemometry data measured within the wake flow of a porous disk subject to a uniform free-stream flow. Furthermore, the new model is used to estimate the TKE distribution at the hub-height level of the rotating non-axisymmetric wake of a model wind turbine immersed in a rough-wall boundary layer. Our results show the important impact of operating conditions on TKE generation in wake flows, an effect not fully captured by existing empirical models. The wind-tunnel data also provide insights into the evolution of important turbulent flow quantities such as turbulent viscosity, mixing length and the TKE dissipation rate in wake flows. Both mixing length and turbulent viscosity are found to increase with the streamwise distance. The turbulent viscosity, however, reaches a plateau in the far-wake region. Consistent with the non-equilibrium theory, it is also observed that the normalised energy dissipation rate is not constant, and it increases with the streamwise distance.

Item Type: Article
DOI/Identification number: 10.1017/jfm.2024.664
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Funders: Engineering and Physical Sciences Research Council (https://ror.org/0439y7842)
Depositing User: Peter Hydon
Date Deposited: 25 Nov 2024 10:22 UTC
Last Modified: 26 Nov 2024 14:31 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/107925 (The current URI for this page, for reference purposes)

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