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Author Kalantarnia, M.en_US
Author Khan, F.en_US
Author Hawboldt, K.en_US
Available date 2009-12-27T07:06:00Zen_US
Publication Date 2009-04-15en_US
Publication Name Journal of Loss Prevention in the Process Industries
Citation Maryam Kalantarnia, Faisal Khan, Kelly Hawboldt, Dynamic risk assessment using failure assessment and Bayesian theory, Journal of Loss Prevention in the Process Industries, Volume 22, Issue 5, September 2009, Pages 600-606en_US
Abstract To ensure the safety of a process system, engineers use different methods to identify the potential hazards that may cause severe consequences. One of the most popular methods used is quantitative risk assessment (QRA) which quantifies the risk associated with a particular process activity. One of QRA's major disadvantages is its inability to update risk during the life of a process. As the process operates, abnormal events will result in incidents and near misses. These events are often called accident precursors. A conventional QRA process is unable to use the accident precursor information to revise the risk profile. To overcome this, a methodology has been proposed based on the work of Meel and Seider (2006). Similar to Meel and Seider (2006) work, this methodology uses Bayesian theory to update the likelihood of the event occurrence and also failure probability of the safety system. In this paper the proposed methodology is outlined and its application is demonstrated using a simple case study. First, potential accident scenarios are identified and represented in terms of an event tree, next, using the event tree and available failure data end-state probabilities are estimated. Subsequently, using the available accident precursor data, safety system failure likelihood and event tree end-state probabilities are revised. The methodology has been simulated using deterministic (point value) as well as probabilistic approach. This Methodology is applied to a case study demonstrating a storage tank containing highly hazardous chemicals. The comparison between conventional QRA and the results from dynamic failure assessment approach shows the significant deviation in system failure frequency throughout the life time of the process unit.en_US
Language enen_US
Publisher Elsevier Ltden_US
Subject Dynamic failure assessmenten_US
Subject Dynamic risk assessmenten_US
Subject Failure probabilityen_US
Subject Accident precursor dataen_US
Subject Bayesian theoryen_US
Title Dynamic risk assessment using failure assessment and Bayesian theoryen_US
Type Articleen_US

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