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Citation:
　Ahmad Bahoo Toroody,Mohammad Mahdi Abaiee,Reza Gholamnia,et al.Epistemic-Based Investigation of the Probability of Hazard Scenarios Using Bayesian Network for the Lifting Operation of Floating Objects[J].Journal of Marine Science and Application,2016,(3):250-259.[doi:10.1007/s11804-016-1361-y]
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Epistemic-Based Investigation of the Probability of Hazard Scenarios Using Bayesian Network for the Lifting Operation of Floating Objects

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Title:
Epistemic-Based Investigation of the Probability of Hazard Scenarios Using Bayesian Network for the Lifting Operation of Floating Objects
Author(s):
Ahmad Bahoo Toroody1;  Mohammad Mahdi Abaiee2;  Reza Gholamnia3;  Mohammad Javad Ketabdari2
Affilations:
Author(s):
Ahmad Bahoo Toroody1;  Mohammad Mahdi Abaiee2;  Reza Gholamnia3;  Mohammad Javad Ketabdari2
1. Faculty of Engineering, Kar Higher Education Institute of Qazvin, Qazvin 3431849689, Iran;
2. Faculty of Marine Technology, Amirkabir University of Technology Tehran, Tehran 15875-4413, Iran;
3. Faculty of Health Safety and Environment, Shahid Beheshti University of Medical Science, Tehran 19395, Iran
Keywords:
epistemic estimation; Bayesian theory; light-weight lifting; success likelihood index method (SLIM); event tree (ET); Bayesian network
分类号:
-
DOI:
10.1007/s11804-016-1361-y
Abstract:
Owing to the increase in unprecedented accidents with new root causes in almost all operational areas, the importance of risk management has dramatically risen. Risk assessment, one of the most significant aspects of risk management, has a substantial impact on the system-safety level of organizations, industries, and operations. If the causes of all kinds of failure and the interactions between them are considered, effective risk assessment can be highly accurate. A combination of traditional risk assessment approaches and modern scientific probability methods can help in realizing better quantitative risk assessment methods. Most researchers face the problem of minimal field data with respect to the probability and frequency of each failure. Because of this limitation in the availability of epistemic knowledge, it is important to conduct epistemic estimations by applying the Bayesian theory for identifying plausible outcomes. In this paper, we propose an algorithm and demonstrate its application in a case study for a light-weight lifting operation in the Persian Gulf of Iran. First, we identify potential accident scenarios and present them in an event tree format. Next, excluding human error, we use the event tree to roughly estimate the prior probability of other hazard-promoting factors using a minimal amount of field data. We then use the Success Likelihood Index Method (SLIM) to calculate the probability of human error. On the basis of the proposed event tree, we use the Bayesian network of the provided scenarios to compensate for the lack of data. Finally, we determine the resulting probability of each event based on its evidence in the epistemic estimation format by building on two Bayesian network types: the probability of hazard promotion factors and the Bayesian theory. The study results indicate that despite the lack of available information on the operation of floating objects, a satisfactory result can be achieved using epistemic data.

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Memo

Memo:
Received date: 2015-10-14;Accepted date: 2016-2-29。
Corresponding author: Ahmad Bahoo Toroody,E-mail:ahmad.bahootoroody@gmail.com
Last Update: 2016-09-02