PyRC is a package to create and simulate resistance-capacity networks.

Installation

pip install pyrc

Notes:

• PyRC started as research software, built from scientists for scientists. It was initiated at the IGTE at the University of Stuttgart by Joel Kimmich and Tim Jourdan.
• PyRC becomes software in research.
• PyRC was initiated at the IGTE at the University of Stuttgart from Joel Kimmich and Tim Jourdan. Its first application was to simulate a dynamic thermal system with a constant mass flow under boundary conditions resulting from weather conditions (sun radiation and ambient temperatures) over a whole year. Parameter studies were also
  conducted as part of this work. PyRC has therefore been tested in this regard. Additional functionality was added subsequently, and its performance was tested in individual cases. Nevertheless, more extensive testing is absolutely necessary.
• PyRC brings the simplicity of Python. Some people may miss the speed of C code but appreciate the user-friendliness of Python. Python is widely spread across the scientific community and the automation of geometric thermal problems build in PyRC makes it a great tool to easily combine existing Python scripts with the accuracy of physics based dynamic models that can be represented in ODEs and solved efficiently by numeric algorithms.

When to use PyRC

• When you have any thermal multidimensional dynamic problem
• When modeling systems where time scales span nanoseconds to decades
• When avoiding the complexity of CFD mesh generation
• When the thermal network has an unstructured topology
• When extending or customizing solvers directly in Python
• When parameterizing large-scale RC-networks with up to thousands of elements are required
• When parameterizing small-scale RC-networks with only a few elements
• When working with time-dependent system matrices or boundary conditions
• When creating networks to solve partial differential equations via lumped-parameter models
• When creating geometric networks with visual aid of VPython
• ...

Fun Facts

• In principle, PyRC works not only for thermal problems but also for electrical ones. However, this has not yet been tested, and an Induction class modeling the behavior of an electrical coil is still missing. Contributions are welcome!
• Even when not interested in solving the ODE you can use PyRC as tool to get the state-space system of even complex system with hundreds and thousands of capacities and resistors.

Publications

First publication:

Kimmich, J. & Jourdan, T.: "Python Package for Generating Dynamic Systems and Simulating Resistance-Capacitance Networks (PyRC)", DaRUS, 2026. https://dx.doi.org/10.18419/darus-5765

Poster presented at the 1st Stuttgart Research Software Day, 2026:

Kimmich, J. & Jourdan, T.: "PyRC", Zenodo, 2026. https://doi.org/10.5281/zenodo.18832971

Further publications are in progress.

Experiences with PyRC:

• Network with weather data as boundary conditions and 280 radiation source terms; simulating one year with a maximum time step of 0.4 s on a single core at 3.2 GHz:
  • 3'302 capacities, 10'717 resistances
  • Pre-simulation to initialize: 2.5 hours (~7 simulated days)
  • Total simulation time: ~6.5 days
• Smaller systems (~400 nodes) run 1'000 times faster than simulated time.

Contributing

See CONTRIBUTING.rst for how to contribute to PyRC.

License

See LICENSE.txt for the license.

Funding

Funded by the Federal Ministry for Economic Affairs and Energy (Bundesministerium für Wirtschaft und Energie), Germany.