Wind Energy Science
Wind Energy Science
WES
Articles | Volume 10, issue 7
Articles | Volume 10, issue 7
https://doi.org/10.5194/wes-10-1403-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/wes-10-1403-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 10, issue 7
Research article
 | 
18 Jul 2025
Research article |  | 18 Jul 2025

Modeling the effects of active wake mixing on wake behavior through large-scale coherent structures

Lawrence Cheung, Gopal Yalla, Prakash Mohan, Alan Hsieh, Kenneth Brown, Nathaniel deVelder, Daniel Houck, Marc T. Henry de Frahan, Marc Day, and Michael Sprague

Viewed

Total article views: 2,197 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,483 596 118 2,197 40 90 148
  • HTML: 1,483
  • PDF: 596
  • XML: 118
  • Total: 2,197
  • Supplement: 40
  • BibTeX: 90
  • EndNote: 148
Views and downloads (calculated since 09 Dec 2024)
Cumulative views and downloads (calculated since 09 Dec 2024)

Viewed (geographical distribution)

Total article views: 2,197 (including HTML, PDF, and XML) Thereof 2,102 with geography defined and 95 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 11 Apr 2026
Download
Short summary
Mitigating turbine wakes is an important aspect to maximizing wind farm energy production but is a challenge to model. We demonstrate a new approach to modeling active wake mixing, which re-energizes turbine wake through periodic blade pitching. The new model divides the wake into separate steady, unsteady, and turbulent components and solves for each in a computationally efficient manner. Our results show that the model can reasonably predict the faster wake recovery due to mixing.
Read more
Share
Special issue
NAWEA/WindTech 2024
Altmetrics
Final-revised paper
Preprint