Probabilistic risk assessment of fire occurrence in residential buildings: Application to the Grenfell Tower

Abstract

Fire occurrence is one of the most devastating events in residential buildings, among other civil engineered structures. The importance of providing mathematical tools that support fire risk assessments is imperative to improve fire containment measurements as well as accident prevention. In this paper, a novel probabilistic method based on credal networks is proposed to assess the impact on the expected risk of the variables involved in the cause and prevention of fire events. This approach can capture the epistemic uncertainty associated with data available in the form of the probability intervals. This helps to avoid hard assumptions based on the use of crisp probabilities that may lead to unrealistic results. A general model is proposed and then adapted to the Grenfell Tower fire by introducing as evidence the specific conditions of the case study. Different fire scenarios are created to study the effects of the components involved in the accident. The probabilistic outcomes of those scenarios are used to compute the expected risk of unwanted factors, e.g., fatalities and fire costs as part of the fire risk assessment. Different data sources and experts have been consulted to enhance the accuracy and quality of the report.