/fsri-compartments-2018

Repository contains data from compartment fire experiments that were conducted for the project supported by Award No. 2017-DN-BX-O163, awarded by the National Institute of Justice, Office of Justice Programs, U.S. Department of Justice. The opinions, findings, and conclusions or recommendations expressed in this publication/program/exhibition are those of the author(s) and do not necessarily reflect those of the Department of Justice.

Primary LanguagePythonMIT LicenseMIT

fsri-compartments-2018

DOI

This repository contains data from compartment fire experiments that were conducted as part of a project that examined the use of fire dynamics analysis techniques with furniture-fueled fires. Information about the experiments and a Python script that generates charts of the experimental data are also included in this repository.

This project was supported by Award No. 2017-DN-BX-O163, awarded by the National Institute of Justice, Office of Justice Programs, U.S. Department of Justice. The opinions, findings, and conclusions or recommendations expressed in this publication/program/exhibition are those of the author(s) and do not necessarily reflect those of the Department of Justice.

01_Data

The data directory includes data files from the 120 compartment fire experiments. More information about the file structures and the corresponding experiments can be found here: Data Structure

02_Info

The info directory contains a plaintext .csv channel list that is referenced by the plotting script to properly map data channels to their respective sensor groups, add labels to the chart legends, and assign file names to the charts that are generated. Additional information about the instrumentation including a dimensioned floor plan of sensor locations can be found here: Experimental Information

03_Scripts

A single Python script, plot.py, is included in the scripts directory. When executed, the script generates .pdf graphs that contain data plots from each sensor group for every experiment. In conjunction with Matplotlib, Seaborn is used to style the graph. If Seaborn is not already installed, it can be added by the following:

pip install seaborn

If you are using the Anaconda distribution of Python, it can alternatively be installed by:

conda install seaborn

04_Charts

The charts directory is produced upon execution of plot.py. The charts produced by the Python script are saved in subdirectories that correspond to each compartment fire experiment. Because the graphs can be produced from files included in this repository, the graphs themselves are not files that are under version control.

Additional Information

For more information about this project and other FSRI fire investigation projects, visit the FSRI Fire Investigation webpage. Contact Us to request any additional information about this project.