nalu-wind

Solver for wind farm simulations targeting exascale computational platforms.
https://github.com/kynema/kynema-ugf

Category: Renewable Energy
Sub Category: Wind Energy

Keywords

cfd ecp exascale-computing les low-mach

Keywords from Contributors

exawind wind-energy snl-applications turbulence wind-turbines wind amrex amr snl-science-libs sandia-national-laboratories

Last synced: about 20 hours ago
JSON representation

Repository metadata

Unstructured grid fluid solver for the Kynema project

README.md

Kynema-UGF (formerly Nalu-Wind)

Documentation | Nightly test dashboard

Kynema-UGF (formerly Nalu-Wind), wherein UGF stands for unstructured-grid fluid dynamics, is a generalized, unstructured-grid, massively parallel, incompressible-flow solver. The codebase was initiated in 2018 from NaluCFD, which was developed by Sandia National Laboratories. Kynema-UGF is being actively
developed and maintained by a dedicated, multi-institutional team from National Laboratory of the Rockies and Sandia National Laboratories.

Kynema-UGF was originally called Nalu-Wind (as part of the ExaWind stack), but was renamed in 2026 in order to reflect its broader, general computational-fluid-dynamics (CFD) capabilities.

Kynema-UGF is developed as an open-source code with the following objectives:

  • an open, well-documented implementation of the state-of-the-art computational
    models for modeling flow physics relevant to energy systems that are
    backed by a comprehensive verification and validation (V&V) process;

  • be able to leverage the high-performance leadership-class computing
    facilities available at DOE national laboratories.

When disseminating technical work that includes Kynema-UGF simulations
please reference the following citations:

The following contains the introduction of Nalu-Wind as part of the ExaWind suite:

Sprague, M. A., Ananthan, S., Vijayakumar, G., Robinson, M., "ExaWind: A multifidelity 
modeling and simulation environment for wind energy", NAWEA/WindTech 2019 Conference, 
Amherst, MA, 2019. https://iopscience.iop.org/article/10.1088/1742-6596/1452/1/012071/pdf

The following contains details for Kynema-UGF (formerly Nalu-Wind):

Sharma, A., M.J. Brazell, M.J., G. Vijayakumar, S. Ananthan, L. Cheung, N. deVelder, 
M.T. Henry de Frahan, N. Matula, P. Mullowney, J. Rood, P. Sakievich, A. Almgren, P.S. 
Crozier, and M.A. Sprague, 2024, ExaWind: Open-source CFD for hybrid-RANS/LES 
geometry-resolved wind turbine simulations in atmospheric flows. Wind Energy, 27, 
225-257. https://onlinelibrary.wiley.com/doi/full/10.1002/we.2886.

Documentation

Documentation is available online at https://kynema.github.io/kynema-ugf/ and is
split into the following sections:

  • Theory manual:
    This section provides a detailed overview of the supported equation sets, the
    discretization and time-integration schemes, turbulence models available, etc.

  • Verification manual:
    This section documents the results from verification studies of the spatial
    and temporal schemes available in Kynema-UGF.

  • User manual:
    The user manual contains detailed instructions on building the code, along
    with the required third-party libraries (TPLs) and usage.

All documentation is maintained alongside the source code within the git
repository and automatically deployed to a github-hosted website upon new commits.

Compilation and usage

Kynema-UGF is primarily built upon the packages provided by the Trilinos
project
, which in turn depends on several third-party
libraries (MPI, HDF5, NetCDF, parallel NetCDF), and YAML-CPP. In addition, it
has the following optional dependencies: hypre, TIOGA, and OpenFAST. Detailed
build instructions are available in the user
manual
.
We recommend using the Spack package manager to install
Kynema-UGF on your system.

Testing and quality assurance

Kynema-UGF comes with a comprehensive unit test and regression test suite that
exercise almost all major components of the code. The main branch is
compiled and run through a regression test suite with different compilers
(GCC, LLVM/Clang, and
Intel) on Linux and MacOS
operating systems, against the latest versions of
Trilinos. Tests are performed both using
MPI on CPUs and GPU hardware configurations. The results of the nightly
testing are publicly available on CDash
dashboard
.

Contributing, reporting bugs, and requesting help

To report issues or bugs please create a new
issue
on GitHub.

We welcome contributions from the community in form of bug fixes, feature
enhancements, documentation updates, etc. All contributions are processed
through pull-requests on GitHub. Please follow our contributing
guidelines

when submitting pull-requests.

To pass the formatting check, use this with a new version of clang-format:

find kynema_ugf.C unit_tests.C ./include ./src ./unit_tests \( -name "*.cpp" -o -name "*.H" -o -name "*.h" -o -name "*.C" \) -exec clang-format -i {} +

License

Kynema-UGF is licensed under BSD 3-clause license. Please see the
LICENSE included in
the source code repository for more details.

Acknowledgements

Kynema-UGF was originally developed with funding from Department of Energy's
(DOE) Office of Science Exascale Computing Project
(ECP)
and Energy Efficiency and Renewable
Energy (EERE) Wind Energy Technology Office (WETO). It is currently supported by the
DOE Office of Critical Minerals and Energy Innovation (CMEI).

Please see authors
file
for a
list of contributors to Kynema-UGF, formerly Nalu-Wind.


Owner metadata


GitHub Events

Total
Last Year

Committers metadata

Last synced: 2 days ago

Total Commits: 2,406
Total Committers: 74
Avg Commits per committer: 32.514
Development Distribution Score (DDS): 0.822

Commits in past year: 41
Committers in past year: 11
Avg Commits per committer in past year: 3.727
Development Distribution Score (DDS) in past year: 0.732

Name Email Commits
Shreyas Ananthan s****s@u****u 429
Jon Rood j****d@n****v 404
Stefan P. Domino s****n@s****v 393
Alan Williams w****m@s****v 193
Robert C. Knaus r****s@s****v 159
psakievich p****v@s****v 136
James Overfelt j****f@s****v 133
Marc T. Henry de Frahan m****n@n****v 99
Ganesh Vijayakumar g****r@n****v 71
Nalu It n****t@N****l 54
Shreyas Ananthan s****n@n****v 39
PaulMullowney 6****y 37
ashesh2512 3****2 25
mbarone81 m****e@s****v 15
Michael B Kuhn 3****n 14
Timothy Smith 5****4 14
lawrenceccheung c****l@g****m 13
Tony Martinez t****e@g****m 11
Wyatt Horne 6****e 10
Luc Berger-Vergiat l****e@s****v 9
Jeremy Melvin j****n@g****m 9
Johnathan Vo j****o@s****v 8
Philip Sakievich p****v@s****v 7
ddement d****t@g****u 7
Tim Neumann n****m@f****e 6
Matt Churchfield m****d@n****v 6
djglaze 4****e 5
Mike Sprague m****e@g****m 5
Thomas J. Otahal t****a@s****v 5
Jonathan Hu j****u@s****v 5
and 44 more...

Committer domains:


Issue and Pull Request metadata

Last synced: 6 days ago

Total issues: 0
Total pull requests: 1
Average time to close issues: N/A
Average time to close pull requests: less than a minute
Total issue authors: 0
Total pull request authors: 1
Average comments per issue: 0
Average comments per pull request: 0.0
Merged pull request: 1
Bot issues: 0
Bot pull requests: 0

Past year issues: 0
Past year pull requests: 1
Past year average time to close issues: N/A
Past year average time to close pull requests: less than a minute
Past year issue authors: 0
Past year pull request authors: 1
Past year average comments per issue: 0
Past year average comments per pull request: 0.0
Past year merged pull request: 1
Past year bot issues: 0
Past year bot pull requests: 0

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/kynema/kynema-ugf

Top Issue Authors

Top Pull Request Authors

  • jrood-nrel (1)

Top Issue Labels

Top Pull Request Labels


Dependencies

.github/workflows/ci.yml actions
  • DoozyX/clang-format-lint-action v0.13 composite
  • actions/checkout v3 composite
  • styfle/cancel-workflow-action 0.6.0 composite
.github/workflows/stale.yml actions
  • actions/stale v8 composite
.github/workflows/docs.yml actions
  • JamesIves/github-pages-deploy-action releases/v3 composite
  • actions/checkout v4 composite
  • actions/setup-python v5 composite

Score: 9.391661428436553