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Active-wake mixing in atmospheric boundary layers with one-turbine arrays

    Kenneth Brown | Sandia National Laboratories
    Lawrence Cheung | Sandia National Laboratories
    Gopal Yalla | Sandia National Laboratories
    Dan Houck | Sandia National Laboratories
    Nathaniel deVelder | Sandia National Laboratories
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Description

This dataset includes results of high fidelity simulations of a single, offshore wind turbine under a variety of atmospheric conditions. Of primary interest is the turbine performance and wake characteristics when different turbine control strategies are applied, including when wake steering or active wake control are used. The simulations were performed with the LES code AMR-Wind (https://github.com/Exawind/amr-wind/), coupled with OpenFAST (https://github.com/OpenFAST/openfast) and the ROSCO open-source turbine controller (https://github.com/NREL/ROSCO). The turbine used in the simulations is the IEA 15MW reference turbine model.

Funding Information

DOE Contract Number

DE-NA0003525

Originating Research Organization

Sandia National Laboratories (SNL)

Other Contributing Organizations

Oak Ridge National Laboratory (ORNL), National Renewable Energy Laboratory (NREL)

Sponsoring Organization

Office of Science (SC), Wind Energy Technologies Office (WETO)

Related Works

Details

Release Date

January 21, 2026

Subject

17 WIND ENERGY

Keywords

wind turbines, exawind, openfast, ROSCO

Dataset

Dataset Type

AS Animations/Simulations

Software

Python

Cite This Dataset:

Brown, K., Cheung, L., Yalla, G., Houck, D., deVelder, N. (2026). Active-wake mixing in atmospheric boundary layers with one-turbine arrays. Oak Ridge National Laboratory. https://doi.org/10.13139/OLCF/3000779.

Acknowledgements

This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Advanced Scientific Computing Research programs in the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.