AMR‐Wind: A Performance‐Portable, High‐Fidelity Flow Solver for Wind Farm Simulations
Year: 2025
Type: article
Abstract: 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.
Source: Wind Energy
DOI: 10.1002/we.70010
Authors: Michael B. Kuhn, Marc T. Henry de Frahan, Prakash Mohan, Georgios Deskos, Matt Churchfield, Lawrence Cheung, Ashesh Sharma, Ann Almgren, Shreyas Ananthan, Michael J. Brazell, Luis A. Martínez‐Tossas, Regis Thedin, Jon Rood, Philip Sakievich, Ganesh Vijayakumar, Weiqun Zhang, Michael Sprague
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,730
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
Awards: G1071216263, G1122898986, G11630931, G1166951225, G1193633358, G121915436, G1286236842, G1337544421, G14908310, G1491959311, G1591330662, G1645119126, G1796307089, G1799333409, G203625172, G2135731044, G2164033304, G2214935549, G223002938, G2258721529, G2293800358, G2451833446, G2644915645, G2710243964, G280414146, G2900453181, G2988778103, G3083819904, G3121793570, G3383803043, G3886122786, G399272915, G413247060, G419881185, G42916606, G4370606643, G4501827968, G450780475, G472303462, G4903105778, G498139845, G5265720794, G5339743583, G56224450, G5692331544, G645873479, G6647760685, G7021897321, G7787287669, G816254390, G8269158468, G834333836, G855168022, G8794501934, G8906985441, G944719100, G969889393
OpenAlex ID: W4408858073
