ulfsri / fsri_materials_database

Repository of materials and products properties and fire test data to improve fire modeling and fire investigation.
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Materials and Products Database

Repository of materials and products properties and fire test data to improve fire modeling and fire investigation.

This project was supported in part by Award No. 2019-DU-BX-0018, 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.



Cite this database: "McKinnon, M., Weinschenk, C., Dow, N., DiDomizio, M., and Madrzykowski, D. Materials and Products Database (Version 1.0.0), Fire Safety Research Institute, UL Research Institutes. Columbia, MD 21045, 2023."

Cite the Technical Reference Guide: "McKinnon, M., Weinschenk, C., and Madrzykowski, D. Materials and Products Database - Technical Reference Guide, Fire Safety Research Institute, UL Research Institutes. Columbia, MD 21045, 2023."

Cite the User Guide: "McKinnon, M., and Weinschenk, C. Materials and Products Database - User Guide, Fire Safety Research Institute, UL Research Institutes. Columbia, MD 21045, 2023."



Database Structure

01_Data/

Raw data generated from each apparatus are included here in plain-text format. The data is organized first by material, next by the short name of test apparatus used, and where applicable additional filtering by test settings.

Test Apparatus and Data File Structure

Additional Data Files

02_Scripts/

Python processing scripts exist for analyzing the experimental data to generate derived quantities and to plot the experimental data. The scripts are apparatus specific and cycle through all materials upon execution. Each apparatus has a pair of scripts: data.py and __data_html.py__.

To successfully execute the Python scripts in this repository, several additional packages (outside of base Python) will need to be installed. One way to do this is through pip with following commands:

pip install pandas              #used for data wrangling/processing
pip install numpy               #used for math analysis
pip install scipy               #used for stats analysis
pip install matplotlib          #used for plot styling and pdf plots
pip install plotly              #used for interactive html plots
pip install GitPython           #used for add repo hash to plots
pip install pybaselines         #used for melting analysis in STA

03_Charts

The material sub directories get generated upon executing of the plotting scripts. The sub directories are broken down by material and further by test apparatus.