|Table of Contents|

 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]
Click and Copy

Epistemic-Based Investigation of the Probability of Hazard Scenarios Using Bayesian Network for the Lifting Operation of Floating Objects


Epistemic-Based Investigation of the Probability of Hazard Scenarios Using Bayesian Network for the Lifting Operation of Floating Objects
Ahmad Bahoo Toroody1 Mohammad Mahdi Abaiee2 Reza Gholamnia3 Mohammad Javad Ketabdari2
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
epistemic estimationBayesian theorylight-weight liftingsuccess likelihood index method (SLIM)event tree (ET)Bayesian network
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.


Abbassi R, Khan F, Garaniya V, Chai S, Chin C, Hossain KA, 2015. An integrated method for human error probabilityassessment during the maintenance of offshore facilities. Proccess Safety And Environmental Protection, 94, 172-179. DOI: 10.1016/j.psep.2015.01.010
Abimbola M, Khan F, Khakzad N, Butt S, 2015. Safety and risk analysis of managed pressure drilling operation using bayesian network. Safety Science, 76, 133-144. DOI: 10.1016/j.ssci.2015.01.010
Basra G, Kirwan B, 1998. Collection of offshore human error probability data. Reliability Engineering and System Safety, 61(1-2), 77-93. DOI: 10.1016/S0951-8320(97)00064-1
Bouhamed H, Masmoudi A, Lecroq T, Rebaï A, 2015. Structure space of Bayesian networks is dramatically reduced by subdividing it in sub-networks. Journal of Computational and Applied Mathematics, 287, 48-62. DOI: 10.1016/j.cam.2015.02.055
Chen TT, Leu SS, 2014. Fall risk assessment of cantilever bridge projects using Bayesian network. Safety Science, 70, 161-171. DOI: 10.1016/j.ssci.2014.05.011
Comer MK, Seaver DA, Stillwell WG, Gaddy X, 1984. Generating human reliability estimates using expert judgement. Vol. 1. NUREG/CR-3688 (SAND 84-7115).
Embrey D, 2000. Task analysis techniques.PhD managing director. human reliability associates ltd.
Ferdous R, Khan F, Sadiq R, Amyotte P, Veitch B, 2009. Handling data uncertainties in event tree analysis. Process Safety and Environmental Protection, 87(5), 283-292. DOI: 10.1016/j.psep.2009.07.003
Groth K, 2009. A data-informed model of performance shaping factors for use in human reliability analysis. PhD thesis, University of Maryland, College Park, MD, USA.
Helton JC, Oberkampf WL, 2004. Alternative representation of epistemic uncertainty. Reliability Engineering and System Safety (RESS), 85(1-3), 1-10. DOI: 10.1016/j.ress.2004.03.001
Kappes MS, Keiler M, von Elverfeldt K, Glade T, 2012. Challenges of analyzing multi-hazard risk: a review. Natural Hazards, 64(2), 1925-1958. DOI: 10.1007/s11069-012-0294-2
Khan FI, Amyotte PR, DiMattia DG, 2006. HEPI: A new tool for human error probability calculation for offshore operation. Safety Science, 44(4), 313-334. DOI: 10.1016/j.ssci.2005.10.008
Khakzad N, Khan F, Amyotte P, 2011. Safety analysis in process facilities: Comparison of fault tree and Bayesian network approaches. Reliability Engineering And System Safety, 96(8), 925-932. DOI: 10.1016/j.ress.2011.03.012
Kirwan B, 1988. A comparative evaluation of five human reliability assessment techniques. In human factors and decision making (ed. B. A. Sayers). Elsevier, 87-109.
Kirwan B, 1994. A Guide to practical human reliability assessment. Taylor & Francis, London.
Kirwan B, Kennedy R, Taylor-Adams S, A Validation A, 1995. Study of three human reliability quantification techniques. European Safety and Reliability Conference (ESREL’95), London, 641- 661.
Li LF, Wang JF, Leung H, Jiang CS, 2010. Assessment of catastrophic risk using bayesian network constructed from domain knowledge and spatial data. Risk Analysis, 30(7), 1157-1175. DOI: 10.1111/j.1539-6924.2010.01429.x
Marzocchi W, Garcia-Aristizabal A, Gasparini P, Mastellone ML, Di Ruocco A, 2012. Basic principles of multi risk assessment. A case study in Italy. Natural Hazards, 62, 551-573. DOI: 10.1007/s11069-012-0092-x
MontewkaJ, EhlersS, Goerlandt F, Hinz T, Tabri K, Kujala P, 2014. A framework for risk assessment for maritime transportation systems—A case study for open sea collisions involving RoPax vessels. Reliability Engineering and System Saftey, 124, 142-157. DOI: 10.1016/j.ress.2013.11.014
Musharraf M, Hassan J, Khan F, Veitch B, MacKinnon S, Imtiaz S, 2013. Human reliability assessment during offshore emergency conditions. Safety Sience, 59, 19-27. DOI: 10.1016/j.ssci.2013.04.001
Nadim F, Liu ZQ, 2013. Quantitative risk assessment for earthquake-triggered landslides using Bayesian network. Proceedings of the 18th International Conference on Soil Mechanics and Geotechnical Engineering, Paris.
Oberkampf WL, DeLand, SM, Rutherford BM, Diegert KV, Alvin KF, 2000. Estimation of totaluncertainty in modeling and simulation. Albuquerque, NM, SAND 2000-0824, Sandia National Laboratories.
Rausand M, 2011. Risk assessment. John Wiley & Sons, New Jersey.
Robinson RW, 1977. Counting unlabeled acyclic digraphs. Comb. Math., 622, 28-43. DOI: 10.1007/BFb0069178
Sentz K, Ferson S, 2002. Combination of evidence in Dempster-Shafer theory. Albuquerque, NM: SAND 2002-0835, Sandia National Laboratories.
Swain AD, Guttmann HE, 1983. Human reliability analysis with emphasis on nuclear power plant applications. NUREG/CR-1278, USNRC, Washington, DC.
Urbina A, Mahadevan S, 2011. Quantification of aleatoric and epistemic uncertainty in computational models of complex systems. Structural Dynamic, 3, 519-535. DOI: 10.1007/978-1-4419-9834-7_47
Williams JC, 1986. A proposed method for assessing and reducing human error. Proceedings of the 9th Advance in Reliability Technology Symposium, University of Bradford, B3/R/1-B3/R/13.


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