Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
An EPANET compatible python package to simulate and analyze water distribution networks under disaster scenarios.
| Date | Stars |
|---|---|
| 2026-07-25 | 456 |
| 2026-07-28 | 456 |
| 2026-07-30 | 456 |
| 2026-08-06 | 456 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
<h1> <img src="https://raw.githubusercontent.com/usepa/wntr/main/documentation/_static/logo.jpg" width="375"> </h1><br> [](https://github.com/USEPA/WNTR/actions/workflows/test_repository.yml) [](https://coveralls.io/github/USEPA/WNTR?branch=main) [](https://github.com/usepa/wntr/actions/workflows/build_deploy_pages.yml) [](https://github.com/USEPA/WNTR/graphs/contributors) The Water Network Tool for Resilience (WNTR) is a Python package designed to simulate and analyze resilience of water distribution networks. The software includes capability to: * Generate water network models * Modify network structure and operations * Add disruptive events including pipe leaks * Add response/repair strategies * Simulate pressure dependent demand and demand-driven hydraulics * Simulate water quality * Evaluate resilience * Visualize results For more information, see the WNTR documentation at https://usepa.github.io/WNTR DeepWiki AI-generated documentation, which includes code architecture diagrams and a chatbot, are available at https://deepwiki.com/USEPA/WNTR Installation -------------- The latest release of WNTR can be installed from PyPI or Anaconda using one of the following commands in a command line or PowerShell prompt. * PyPI [](https://pypi.org/project/wntr/) [](https://pepy.tech/project/wntr) ``pip install wntr`` * Anaconda [](https://anaconda.org/conda-forge/wntr) [](https://anaconda.org/conda-forge/wntr) ``conda install -c conda-forge wntr`` See [installation instructions](https://usepa.github.io/WNTR/installation.html) for more details. Citing WNTR ----------------- To cite WNTR, use one of the following references: * Klise, K., D. Hart, M. Bynum, J. Hogge, Terranna Haxton, R. Murray, AND J. Burkhardt. (2023). Water Network Tool for Resilience (WNTR) User Manual Version 1.0. U.S. Environmental Protection Agency, Washington, DC, EPA/600/B-23/098 * Klise, K.A., Murray, R., Haxton, T. (2018). An overview of the Water Network Tool for Resilience (WNTR), In Proceedings of the 1st International WDSA/CCWI Joint Conference, Kingston, Ontario, Canada, July 23-25, 075, 8p. * Klise, K.A., Bynum, M., Moriarty, D., Murray, R. (2017). A software framework for assessing the resilience of drinking water systems to disasters with an example earthquake case study, Environmental Modelling and Software, 95, 420-431, doi: 10.1016/j.envsoft.2017.06.022 License ------------ WNTR is released under the Revised BSD license. See [LICENSE.md](https://github.com/USEPA/WNTR/blob/main/LICENSE.md) for more details. Organization ------------ Directories * wntr - Python package * documentation - User manual * examples - Examples and network files Contact -------- * Katherine Klise, Sandia National Laboratories, [email protected] * Terra Haxton, US Environmental Protection Agency, [email protected] EPA Disclaimer ----------------- The United States Environmental Protection Agency (EPA) GitHub project code is provided on an "as is" basis and the user assumes responsibility for its use. EPA has relinquished control of the information and no longer has responsibility to protect the integrity , confidentiality, or availability of the information. Any reference to specific commercial products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply their endor
Excerpt of 4,572 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:10427573b9464667, topic:simulation