Dynamic Inherently Safer Modifications: Metric development and its validation for fire and explosion prevention
Document Type
Article
Publication Date
7-1-2021
Abstract
Of the numerous inherent safety assessment tools, a dynamic metric capable of investigating and incorporating the temporal risk evolution when conducting Inherently Safer Modifications (ISMs) is yet to be established. To this end, this work developed a Dynamic Inherent Safety Metric (DISM) and validated its functionality and viability through a case study. Firstly, the Information-Flow-based Accident-causing Model (IFAM) was adapted to construct the topology of Bayesian Networks (BN). Then, Bayesian deductive reasoning was executed to do crucial risk identification by ranking posterior probabilities. Finally, risk-based ISMs were performed to address the relatively contributing risk factors. The case study results show that the fire and explosion risk decreased by approximately a third after implementing ISMs, thus demonstrating that the modified processing scenario could be inherently safer than the original processing scenario. The newly developed inherent safety metric (i.e., DISM) can assist in temporal risk identification and assessment, and it is expected to function as a novel assessment tool for measuring and comparing the inherent safeness before and after implementing ISMs with simultaneous considerations on the time-varying risk factors.
Keywords
Inherent safety, Risk assessment, Dynamic bayesian networks, Risk-based safeguard, Fire and explosion prevention
Divisions
fac_eng
Publication Title
Journal of Loss Prevention in the Process Industries
Volume
71
Publisher
Elsevier
Publisher Location
THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND