Development of Probabilistic Fire Brigade Suppression Model in Assembly Occupancies Using Bayesian Method

Abstract

This study developed the probabilistic fire brigade suppression model for assembly occupancies whose risk is significant in terms of life and property damage due to unspecified majority of people and the high density in the space when fire occurs using Bayesian Markove Chain Monte Carlo method. As a result of deriving a fire brigade suppression probability model based on actual fire experience data over the past five years, 17 cities and provinces were able to be grouped into 3 for which, Log-normal or Gamma based probability models are developed. The probabilistic fire brigade suppression models for 3 groups drawn through this study are expected to contribute to secure the realism of quantitative fire risk assessment and to enhance reliability of the fire safety management measures through support of risk based decision by reflecting the real fire event experiences.