AMR‐Wind: A Performance‐Portable, High‐Fidelity Flow Solver for Wind Farm Simulations
ABSTRACT We present AMR‐Wind, a verified and validated high‐fidelity computational‐fluid‐dynamics code for wind farm flows. AMR‐Wind is a block‐structured, adaptive‐mesh, incompressible‐flow solver that enables predictive simulations of the atmospheric boundary layer and wind plants. It is a highly scalable code designed for parallel high‐performance computing with a specific focus on performance portability for current and future computing architectures, including graphical processing units (GPUs). In this paper, we detail the governing equations, the numerical methods, and the turbine models. Establishing a foundation for the correctness of the code, we present the results of formal verification and validation. The verification studies, which include a novel actuator line test case, indicate that AMR‐Wind is spatially and temporally second‐order accurate. The validation studies demonstrate that the key physics capabilities implemented in the code, including actuator disk models, actuator line models, turbulence models, and large eddy simulation (LES) models for atmospheric boundary layers, perform well in comparison to reference data from established computational tools and theory. We conclude with a demonstration simulation of a 12‐turbine wind farm operating in a turbulent atmospheric boundary layer, detailing computational performance and realistic wake interactions.
Authors
- Michael Sprague (ORCID: https://orcid.org/0000-0003-0519-0379)
- Ann Almgren (ORCID: https://orcid.org/0000-0003-2103-312X)
- Michael Kühn (ORCID: https://orcid.org/0000-0002-5506-7777)
- Marc Henry de Frahan (ORCID: https://orcid.org/0000-0001-7742-1565)
- Luis A. Martínez‐Tossas (ORCID: https://orcid.org/0000-0003-2353-4999)
- Regis Thedin (ORCID: https://orcid.org/0000-0001-5336-7875)
- Ashesh Sharma (ORCID: https://orcid.org/0000-0003-3337-9160)
- Georgios Deskos (ORCID: https://orcid.org/0000-0001-7592-7191)
- Shreyas Ananthan (ORCID: https://orcid.org/0000-0003-3966-4595)
- Michael Brazell (ORCID: https://orcid.org/0000-0001-9610-6624)
- Weiqun Zhang (ORCID: https://orcid.org/0000-0001-8092-1974)
- Jon Rood
- Lawrence C.C. Cheung (ORCID: https://orcid.org/0000-0002-7697-4739)
- Ganesh Vijayakumar (ORCID: https://orcid.org/0000-0001-5228-2511)
- Matthew Churchfield (ORCID: https://orcid.org/0000-0001-9906-7288)
- Philip Sakievich (ORCID: https://orcid.org/0000-0002-7251-8496)
- Prakash Mohan (ORCID: https://orcid.org/0000-0003-3889-5957)
Institutions
- National Laboratory of the Rockies (US)
- Lawrence Berkeley National Laboratory (US)
- Sandia National Laboratories California (US)
- Sandia National Laboratories (US)
Publication Details
- Journal
- Wind Energy
- Published
- 2025-03-24
- DOI
- https://doi.org/10.1002/we.70010
- Citations
- 7
- Primary Topic
- Wind Energy Research and Development
- Type
- article
- Field-Weighted Citation Impact
- 29.96
Funders
- U.S. Department of Energy
- Office of Science
- Office of Energy Efficiency and Renewable Energy
- National Nuclear Security Administration
- Advanced Scientific Computing Research
- Biological and Environmental Research
- Wind Energy Technologies Office
- Office of Energy Efficiency
- Sandia National Laboratories