PyroPython – Parameter estimation for FDS pyrolysis models written in python

Pyropython is a python library and set of command-line tools. The motivation for creating this tool has been to support the Fire Modeling efforts at VTT Technical Research Centre of Finland. These tools are best suited for identification of pyrolysis parameters for the Fire Dynamics Simulator (FDS).

Despite this background, the python library and commandline tools can be used to identify parameters for any simulator that outputs data in csv format with text headers.

Pyropython is a wrapper around existing optimizatioon libraries and is written in a fashion that allows easy addition of new algorithms. Currently supported algorithms are:

1. Random sampling
2. Nelder-Mead simplex (from scipy)
3. Differential evolution (also from scipy)
4. Bayesian Optimization (using scikit-optimize)

The PyroPython tool is released as open source software and is available from https://github.com/PyroId/PyroPython. The documentation can be found at http://pyroid.github.io/ .

Development of PyroPython was financed by state nuclear waste fund in the SAFIR2018 programme and NKS

Contents:

• Installation
• Usage
• Configuration files
  • Preliminaries
  • Configuration file structure
  • Configuration file keywords
• Template files
• Optimizers
  • Initial design
  • Random sampling
  • Multistart
  • Differential Evolution
• Plotting
• Filters
• Examples

Indices and tables

• Index
• Module Index
• Search Page