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Parallel Transient Simulation in Water Networks
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To get a local copy up and running follow these simple steps. PTSNET can be downloaded via pip

We highly encourage using a conda environment for the installation

• Install conda

  # Linux
  https://docs.conda.io/projects/conda/en/latest/user-guide/install/linux.html

  # Windows
  https://conda.io/projects/conda/en/latest/user-guide/install/windows.html

• Install the conda environment with all the necessary dependencies

  Download the environment recipe for Windows or Linux/Mac. Then cd to the location of the downloaded ptsnet.yml file. The parallel version of PTSNET can only run on Linux.

  # Open the shell and type
  conda env create -f ptsnet.yml
  conda activate ptsnet

Use this jupyter notebook to run useful examples of transient simulations using PTSNET. You can test the parallel version of PTSNET executing test_simulation.py as follows:

mpiexec -n 8 python test_simulation.py

For more examples, please refer to the Documentation

If PTSNET has been useful for your research and you are ready to publish your paper, please cite the paper below:

Distributed and Vectorized Method of Characteristics for Fast Transient Simulations in Water Distribution Systems

@article{riano2022distributed,
  title={Distributed and vectorized method of characteristics for fast transient simulations in water distribution systems},
  author={Ria{\~n}o-Brice{\~n}o, Gerardo and Sela, Lina and Hodges, Ben R},
  journal={Computer-Aided Civil and Infrastructure Engineering},
  year={2022},
  publisher={Wiley Online Library}
}

Distributed under the Unlicense License. See LICENSE for more information.

Gerardo Riano - [email protected]

Project Link: https://github.com/gandresr/PTSNET

This publication was developed under Cooperative Agreement No. 83595001 awarded by the U.S. Environmental Protection Agency to The University of Texas at Austin. It has not been formally reviewed by EPA. The views expressed in this document are solely those of the authors, and do not necessarily reflect those of the Agency. EPA does not endorse any products or commercial services mentioned in this publication. The authors acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing HPC resources that have contributed to the research results reported within this paper. URL: http://www.tacc.utexas.edu