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PUBLICATIONS

Fire Data Generator (FD-Gen) v1.0.0

Published

Author(s)

Hongqiang Fang, Wai Cheong Tam

Abstract

This document serves as the documentation for the Fire Data Generator (FD-Gen), an automated tool designed to streamline the creation of multiple Fire Dynamics Simulator (FDS) input files. By employing Monte Carlo methods to sample relevant fire parameters, FD-Gen creates diverse fire scenarios and seamlessly integrates them into FDS case input files. This tool is designed to efficiently produce large volumes of synthetic fire data, supporting the development and training of machine learning models for smart fire detection and forecasting applications. Additionally, FD-Gen may offer practical benefits for applications such as fire risk assessment and fire investigation, broadening its impact across fire safety and research domains.
Citation
Technical Note (NIST TN) - 2332
Report Number
2332
NIST Pub Series
Technical Note (NIST TN)
Pub Type
NIST Pubs

Download Paper

https://doi.org/10.6028/NIST.TN.2332
Local Download

Keywords

Fire scenarios, Fire simulation, FDS input files, Monte Carlo, Data sampling, Automated tool
Public safety, Machine learning, Fire modeling, Fire fighting, Fire dynamics and science and Fire

Citation

FANG, H. and Tam, W. (2025), Fire Data Generator (FD-Gen) v1.0.0, Technical Note (NIST TN), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://doi.org/10.6028/NIST.TN.2332, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=959283 (Accessed October 13, 2025)

Issues

If you have any questions about this publication or are having problems accessing it, please contact [email protected].

Created March 6, 2025
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