High temporal frequency data from a four turbine, blade-resolved wind farm simulation with ExaWind

Henry de Frahan, Marc T.; Cheung, Lawrence; Sprague, Michael A.

doi:10.13139/OLCF/3000073

Title: High temporal frequency data from a four turbine, blade-resolved wind farm simulation with ExaWind

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Abstract

The data was generated with ExaWind (https://github.com/Exawind) which couples AMR-Wind (https://github.com/Exawind/amr-wind/), Nalu-Wind (https://github.com/Exawind/nalu-wind), TIOGA (https://github.com/Exawind/tioga), and OpenFAST (https://github.com/OpenFAST/openfast). This is a large-scale simulation of a blade-resolved wind farm using the ExaWind software stack. ExaWind couples together a background flow solver, AMR-Wind, and a near-body solver, Nalu-Wind, through an overset technique from the TIOGA application. Another application, OpenFAST, handles the structural dynamics of the turbine blades and towers, which informs the fluid-structure interaction of the wind turbines with the flow solvers. This particular simulation includes four blade-resolved wind turbines operating in a turbulent atmospheric boundary layer. The AMR-Wind solver uses 500 million cells and is being solved on 256 AMD GPUs of the Oakridge Leadership Computing Facility Frontier supercomputer. Each turbine is assigned its own Nalu-Wind solver with over 13 million elements per turbine and solved using 448 CPU cores, for a total of 1792 CPU cores. For each node, 56 cores contain Nalu-Wind, while 8 cores correspond to AMR-Wind operations on the GPUs. Consequently, ExaWind is entirely utilizing the CPUs and the GPUs of the nodes concurrently. The data used in the visualization is full flow field data output from the simulation. It is lossy-compressed to a specific accuracy usingmore »« less

Authors:

Henry de Frahan, Marc T.; Cheung, Lawrence; Sprague, Michael A.

National Renewable Energy Laboratory
Sandia National Laboratories

Publication Date:: Thu Nov 06 04:00:00 UTC 2025

DOE Contract Number:: AC36-08GO28308; NA0003525

Research Org.:: National Renewable Energy Laboratory

Sponsoring Org.:: Office of Science (SC)

Subject:: 17 WIND ENERGY; amr-wind; computational fluid dynamics; exawind; nalu-wind; openfast; tioga; wind energy; wind farm; wind turbines

OSTI Identifier:: 3000073

DOI:: https://doi.org/10.13139/OLCF/3000073

Citation Formats


                    Henry de Frahan, Marc T., Cheung, Lawrence, and Sprague, Michael A. High temporal frequency data from a four turbine, blade-resolved wind farm simulation with ExaWind.  United States: N. p., 2025. 
        Web.  doi:10.13139/OLCF/3000073.

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                    Henry de Frahan, Marc T., Cheung, Lawrence, & Sprague, Michael A. High temporal frequency data from a four turbine, blade-resolved wind farm simulation with ExaWind.  United States.  doi:https://doi.org/10.13139/OLCF/3000073

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                    Henry de Frahan, Marc T., Cheung, Lawrence, and Sprague, Michael A. 2025.  
"High temporal frequency data from a four turbine, blade-resolved wind farm simulation with ExaWind".  United States.  doi:https://doi.org/10.13139/OLCF/3000073.  https://www.osti.gov/servlets/purl/3000073. Pub date:Thu Nov 06 04:00:00 UTC 2025

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@article{osti_3000073,

  title        = {High temporal frequency data from a four turbine, blade-resolved wind farm simulation with ExaWind},

  author       = {Henry de Frahan, Marc T. and Cheung, Lawrence and Sprague, Michael A.},

  abstractNote = {The data was generated with ExaWind (https://github.com/Exawind) which couples AMR-Wind (https://github.com/Exawind/amr-wind/), Nalu-Wind (https://github.com/Exawind/nalu-wind), TIOGA (https://github.com/Exawind/tioga), and OpenFAST (https://github.com/OpenFAST/openfast). This is a large-scale simulation of a blade-resolved wind farm using the ExaWind software stack. ExaWind couples together a background flow solver, AMR-Wind, and a near-body solver, Nalu-Wind, through an overset technique from the TIOGA application. Another application, OpenFAST, handles the structural dynamics of the turbine blades and towers, which informs the fluid-structure interaction of the wind turbines with the flow solvers. This particular simulation includes four blade-resolved wind turbines operating in a turbulent atmospheric boundary layer. The AMR-Wind solver uses 500 million cells and is being solved on 256 AMD GPUs of the Oakridge Leadership Computing Facility Frontier supercomputer. Each turbine is assigned its own Nalu-Wind solver with over 13 million elements per turbine and solved using 448 CPU cores, for a total of 1792 CPU cores. For each node, 56 cores contain Nalu-Wind, while 8 cores correspond to AMR-Wind operations on the GPUs. Consequently, ExaWind is entirely utilizing the CPUs and the GPUs of the nodes concurrently. The data used in the visualization is full flow field data output from the simulation. It is lossy-compressed to a specific accuracy using ZFP and written to disk every 16 time-steps to enable real-time flow visualization. The flow fields are sampled at a high temporal frequency to enable real-time, 24fps visualization. The flow fields are sampled every 12 simulation time steps (every 0.04132s).},

  doi          = {10.13139/OLCF/3000073},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Thu Nov 06 04:00:00 UTC 2025},

  month        = {Thu Nov 06 04:00:00 UTC 2025}

}

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DOI: https://doi.org/10.13139/OLCF/3000073

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