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

  • Brown, Kenneth | Sandia National Laboratories
  • Cheung, Lawrence | Sandia National Laboratories
  • Yalla, Gopal | Sandia National Laboratories
  • Houck, Dan | Sandia National Laboratories
  • deVelder, Nathaniel | Sandia National Laboratories
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Overview

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 Resources

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), DOE Wind Energy Technologies Office (WETO)

Project Identifier

CFD162

Related Resources

Details

DOI

10.13139/OLCF/3000779

Release Date

January 21, 2026

Dataset

Dataset Type

AS Animations/Simulations

Software

Python

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.

Category

  • 17 WIND ENERGY

Keywords

  • wind turbines,
  • exawind,
  • openfast,
  • ROSCO