Skip to content

kafakiran/WNTR

 
 

Repository files navigation

WNTR: Water Network Tool for Resilience

TravisCI Coverage Status Documentation Status

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 driven demand and demand driven hydraulics
  • Simulate water quality
  • Evaluate resilience
  • Visualize results

For more information, go to http://wntr.readthedocs.io

License

WNTR is released under the Revised BSD license. See the LICENSE.txt file.

Organization

Directories

  • wntr - The root directory for WNTR source code
  • documentation - user manual
  • examples - examples and network files

Contact

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 endorsement, recommendation or favoring by EPA. The EPA seal and logo shall not be used in any manner to imply endorsement of any commercial product or activity by EPA or the United States Government.

Sandia Funding Statement

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA-0003525.

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Python 96.8%
  • Pascal 1.5%
  • Visual Basic .NET 1.3%
  • PowerShell 0.4%