A probabilistic quantitative risk assessment model for fire in road tunnels with parameter uncertainty
Author(s) -
Qiang Meng,
Xiaobo Qu
Publication year - 2011
Publication title -
international journal of reliability and safety
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.146
H-Index - 19
eISSN - 1479-3903
pISSN - 1479-389X
DOI - 10.1504/ijrs.2011.041181
Subject(s) - probabilistic logic , risk assessment , probabilistic risk assessment , forensic engineering , environmental science , statistics , computer science , geology , mathematics , engineering , computer security
Fire in road tunnels can lead to catastrophic consequences in combination with tunnel safety provision failures, thus necessitating a need for a reliable and robust approach to assess tunnel risks caused by fire. In a quantitative risk assessment (QRA) model for road tunnels, uncertainty is an unavoidable component because input parameters of the model possess different levels of uncertainties which are inappropriate to be formulated by crisp numbers. In this paper, a Monte Carlo sampling-based QRA model is proposed to address parameter uncertainty of a QRA model. The tunnel risks are assessed in terms of percentile-based societal risk as well as expected number of fatalities (ENF) curve, which would facilitate tunnel managers to make decisions. A case study is carried out to demonstrate the approach.Full Tex
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom