Skip to content

Python-based (chemical kinetic) Model Automatic Reduction Software

License

Notifications You must be signed in to change notification settings

parkerclayton/pyMARS

 
 

Repository files navigation

pyMARS

Code of Conduct License

Python-based (chemical kinetic) Model Automatic Reduction Software (MARS), which consists of multiple techniques for reducing the size and complexity of detailed chemical kinetic models.

pyMARS currently consists of two stages:

  1. Directed relation graph with error propagation and sensitivity analysis (DRGEPSA)
  2. Unimportant reaction elimination

Additional reduction stages, including isomer lumping and CSP-based quasi-steady-state (QSS) species reduction, are currently under development and testing.

See the following publications for more detail:

  • KE Niemeyer, CJ Sung, and MP Raju. Skeletal mechanism generation for surrogate fuels using directed relation graph with error propagation and sensitivity analysis. Combust. Flame, 157(9):1760--1770, 2010. doi:10.1016/j.combustflflame.2009.12.022
  • KE Niemeyer and CJ Sung. On the importance of graph search algorithms for DRGEP-based mechanism reduction methods. Combust. Flame, 158(8):1439--1443, 2011. doi:10.1016/j.combustflflame.2010.12.010.
  • KE Niemeyer and CJ Sung. Mechanism reduction for multicomponent surrogates: A case study using toluene reference fuels. Combust. Flame, in press, 2014. doi:10.1016/j.combustflame.2014.05.001
  • TF Lu and CK Law. Combustion and Flame, 154:153--163, 2008. doi:10.1016/j.combustflame.2007.11.013

Usage

To install: python setup.py install

pyMARS is called from terminal via pyMARS --args

example: pyMARS --file=gri30.cti --run_drg --conditions=example_input.txt --thresholds=example_thresholds.txt

Options

License

pyMARS is released under the MIT license, see LICENSE for details.

If you use this package as part of a scholarly publication, please cite the following papers in addition to this resource:

  • KE Niemeyer, CJ Sung, and MP Raju. Skeletal mechanism generation for surrogate fuels using directed relation graph with error propagation and sensitivity analysis. Combust. Flame, 157(9):1760--1770, 2010. doi:10.1016/j.combustflflame.2009.12.022
  • KE Niemeyer and CJ Sung. On the importance of graph search algorithms for DRGEP-based mechanism reduction methods. Combust. Flame, 158(8):1439--1443, 2011. doi:10.1016/j.combustflflame.2010.12.010.
  • KE Niemeyer and CJ Sung. Mechanism reduction for multicomponent surrogates: A case study using toluene reference fuels. Combust. Flame, in press, 2014. doi:10.1016/j.combustflame.2014.05.001

Code of Conduct

In order to have a more open and welcoming community, pyMARS adheres to a code of conduct adapted from the Contributor Covenant code of conduct.

Please adhere to this code of conduct in any interactions you have in the pyMARS community. It is strictly enforced on all official PyKED repositories, websites, and resources. If you encounter someone violating these terms, please let the project lead (@kyleniemeyer) know via email at kyle.niemeyer@gmail.com) know and we will address it as soon as possible.

About

Python-based (chemical kinetic) Model Automatic Reduction Software

Resources

License

Code of conduct

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%