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A risk‐based approach for predicting domino effects due to fires combining exceedance curves with dynamic thermal stress analysis
Author(s) -
Dunjó Denti Jordi,
AmorósMartí Marcel,
Prophet Neil,
Gorski Gene
Publication year - 2018
Publication title -
process safety progress
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.378
H-Index - 40
eISSN - 1547-5913
pISSN - 1066-8527
DOI - 10.1002/prs.11937
Subject(s) - overpressure , domino effect , process (computing) , reliability engineering , engineering , heat flux , domino , structural engineering , thermal , nuclear engineering , heat transfer , mechanical engineering , computer science , mechanics , physics , meteorology , nuclear physics , thermodynamics , operating system , biochemistry , chemistry , catalysis
This article proposes a risk‐based method for domino effect characterization and potential escalation for process equipment affected by thermal radiation (i.e., fires). This methodology intends to answer two key questions: (1) which process equipment is impacted by a heat flux capable of resulting in escalation due to equipment failure; and (2) what is the associated time to the process equipment failure; that is, Time to Failure (TTF). The first phase consists of developing dedicated heat flux exceedance curves for a given location of interest. The second phase involves a dynamic simulation for the prediction of the TTF due to fires impacting the equipment identified in phase one. A two‐step approach is proposed for ensuring accurate results: (1) vessel wall segmentation to determine how the Ultimate Tensile Strength (UTS) of the material decreases as a function of temperature, and (2) the UTS is then compared with the Hoop stress by considering the equipment internal pressure combined with the installed overpressure protection performance. This article defines step‐by‐step how to conduct a risk‐based assessment and determine the TTF using a case study. It demonstrates the applicability and accuracy of this approach, which helps the decision‐making process on how potential mitigation measures can be implemented. © 2017 American Institute of Chemical Engineers Process Saf Prog 37: 176–185, 2018