Chapter 4 - A model for quantitative fire risk assessment integrating agent-based model with automatic event tree analysis

Abstract

Fire is one of the catastrophic accidents that affect people, environment, and properties. Therefore, different models are developed under qualitative, semiquantitative, and quantitative approaches for fire risk assessment. Quantitative approach is considered as the best because of its precision. However, uncertainty is still the main challenge to analyze fire accidents effectively. Consequently, this chapter comes out with new methodology to handle uncertainty of fire assessment and generate automatic event tree for quantitative analysis. The developed methodology is based on the following steps: (1) the Consolidated Model of Fire and Smoke Transport (CFAST) as a deterministic model to determine the state of the fire, (2) @RISK as a probabilistic model to predict a possible operational state for each agent using Monte Carlo simulation, and (3) an agent-based model (ABM) to coordinate interactions and determine the risk of all possible scenarios. The results of the developed methodology in this study are more precise and reliable than those of the classical models.