High temporal frequency data from a four turbine, blade-resolved wind farm simulation with ExaWind
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Marc T. Henry de Frahan | National Renewable Energy Laboratory
Lawrence Cheung | Sandia National Laboratories
Michael A. Sprague | National Renewable Energy Laboratory
Description
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).
Funding Information
DOE Contract Number
DE-AC36-08GO28308; DE-NA0003525Originating Research Organization
National Renewable Energy LaboratoryOther Contributing Organizations
Sandia National Laboratories, Oak Ridge National LaboratorySponsoring Organization
Office of Science (SC)Details
Release Date
November 6, 2025Subject
17 WIND ENERGYKeywords
wind energy, amr-wind, openfast, wind farm, wind turbines, computational fluid dynamics, exawind, nalu-wind, tiogaDataset
Dataset Type
AS Animations/SimulationsSoftware
python, VisIt, or ParaviewCite This Dataset:
Henry de Frahan, M., Cheung, L., Sprague, M. (2025). High temporal frequency data from a four turbine, blade-resolved wind farm simulation with ExaWind. Oak Ridge National Laboratory. https://doi.org/10.13139/OLCF/3000073.
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.