Quantitative Testing of Fire Scenario Hypotheses: A Bayesian Inference Approach

Published

January 16, 2014

Author(s)

Kristopher J. Overholt, Ofodike A. Ezekoye

Abstract

Fire models are routinely used to evaluate life safety aspects of building design projects and are being used more often in fire and arson investigations as well as reconstructions of firefighter line-of-duty deaths and injuries. A fire within a compartment effectively leaves behind a record of fire activity and history (i.e., fire signatures). Fire and arson investigators can utilize these fire signatures in the determination of cause and origin during fire reconstruction exercises. Researchers conducting fire experiments can utilize this record of fire activity to better understand the underlying physics. In all of these applications, the heat release rate (HRR) and location of a fire are important parameters that govern the evolution of thermal conditions within a fire compartment. These input parameters can be a large source of uncertainty in fire models, especially in scenarios in which experimental data or detailed information on fire behavior are not available. Often, the confidence level or degree of uncertainty is required. To address issues related to the uncertainty of input parameters, an inversion framework was developed that has applications towards fire scene reconstructions. Rather than using point estimates of input parameters, a statistical inversion framework based on the Bayesian inference approach was used to determine probability distributions of input parameters. These probability distributions contain uncertainty information about the input parameters and can be propagated through fire models to obtain uncertainty information about predicted quantities of interest. The Bayesian inference approach was applied to various fire problems and coupled with algebraic, zone, and CFD fire models to extend the physical capability and accuracy of the inversion framework. Example applications include the estimation of both steady-state and transient fire sizes in a compartment as well as the location of a fire in a compartment.

Citation

Fire Technology

Pub Type

Journals

Download Paper

https://doi.org/10.1007/s10694-013-0384-z

Keywords

Fire investigation, Hypothesis testing, Bayesian inference, Uncertainty quantification

Citation

Overholt, K. and Ezekoye, O. (2014), Quantitative Testing of Fire Scenario Hypotheses: A Bayesian Inference Approach, Fire Technology, [online], https://doi.org/10.1007/s10694-013-0384-z (Accessed April 18, 2024)