Incorporation of technical, human and organizational risks in a dynamic probabilistic fire risk model for high‐rise residential buildings. (18th June 2020)

• Record Type: Journal Article
• Authors: Tan, Samson; Weinert, Darryl; Joseph, Paul; Moinuddin, Khalid A. M.
• Other Names: Klippel Andrea guestEditor.; Meacham Brian guestEditor.; Wang Yi guestEditor.
• Is Part Of: Fire and materials. Volume 45:Number 6(2021)
• Page Start: 779
• Page End: 810
• Publication Date: 2020-06-18
• Subjects: Bayesian network -- high‐rise residential buildings -- human and organizational errors -- human and organizational risks -- probabilistic risk assessment -- system dynamics -- technical risks; Fire-testing -- Periodicals; Fire -- Periodicals; Materials -- Periodicals; 620.11217
• DOI: 10.1002/fam.2872
• Languages: English
• ISSNs: 0308-0501

Abstract

Summary: While probabilistic risk assessment (PRA) is an explicit methodology for complying with the performance requirements of the Building Code of Australia (BCA) or similar codes, it traditionally focuses only on technical risks of fire safety systems in a building. There are growing concerns that performance‐based fire engineering designs underestimate safety risk levels in high‐rise residential buildings. Existing fire risk models account for failures of technical systems but ignore human and organizational errors (HOEs) and the complex interactions among these variables. Probabilistic models in other applications, such as offshore platforms and nuclear plants, demonstrate the importance of HOE inclusion in risk models and the resulting impacts on overall risk. This paper proposes a comprehensive technical‐human‐organizational risk (T‐H‐O‐Risk) methodology to enhance the PRA approach by quantifying human and organizational risks in a probabilistic model using Bayesian Network (BN) analysis of HOEs and System Dynamics (SD) modelling for dynamic characterization of risk variations over time. While risk modelling itself is not novel, the current research develops unique and specific enhancements to existing risk approaches by integrating HOE risks with technical risks in a comprehensive dynamic and probabilistic model for high‐rise residential buildings. Three case studies are conducted to demonstrate the application of this comprehensive approach to the designs of various high‐rise residential buildings ranging from 18 to 24 storeys. Societal risks are represented in F‐N curves. Results show that in general, fire safety designs that do not consider HOEs underestimate overall risks generally by~20%—and can reach up to 42% in an extreme case. Furthermore, risks over time due to HOEs vary by as much as 30% over a 10‐year period. A sensitivity analysis indicates that deficient training, poor safety culture and ineffective emergency plans have significant impact on overall risk.