DOI QR코드

DOI QR Code

Development of Quantitative Risk Assessment Methodology for the Maritime Transportation Accident of Merchant Ship

상선 운항 사고의 양적 위기평가기법 개발

  • Yim, Jeong-Bin (Division of Maritime Transportation System, Mokpo Maritime University)
  • 임정빈 (목포해양대학교 해상운송시스템학부)
  • Published : 2009.03.01

Abstract

This paper describes empirical approach methodology for the quantitative risk assessment of maritime transportation accident (MTA) of a merchant ship. The principal aim of this project is to estimate the risk of MTA that could degrade the ship safety by analyzing the underlying factors contributing to MTA based on the IMO's Formal Safety Assessment techniques and, by assessing the probabilistic risk level of MTA based on the quantitative risk assessment methodology. The probabilistic risk level of MTA to Risk Index (RI) composed with Probability Index (PI) and Severity Index (SI) can be estimated from proposed Maritime Transportation Accident Model (MTAM) based on Bayesian Network with Bayesian theorem Then the applicability of the proposed MTAM can be evaluated using the scenario group with 355 core damaged accident history. As evaluation results, the correction rate of estimated PI, $r_{Acc}$ is shown as 82.8%, the over ranged rate of PI variable sensitivity with $S_p{\gg}1.0$ and $S_p{\ll}1.0$ is shown within 10%, the averaged error of estimated SI, $\bar{d_{SI}}$ is shown as 0.0195 and, the correction rate of estimated RI, $r_{Acc}$(%), is shown as 91.8%. These results clearly shown that the proposed accident model and methodology can be use in the practical maritime transportation field.

본 논문에서는 상선의 운항 사고에 관한 양적 위기평가에 관한 실험적인 접근방법들을 기술했다. 이 연구의 목적은 국제해사기구의 공식 안전성 평가(FSA)를 기반으로 운항 사고에 크게 기여하는 요소들을 분석하고, 양적 위기평가기법에 기반을 둔 운항 사고의 확률적인 위기수준을 평가한 후, 선박 안전을 저해할 수 있는 운항 사고 위기를 예측하는 것이다. 확률지수(PI)와 심각성지수(SI) 구성된 위기지수(RI)에 대한 운항 사고의 확률적인 위기수준은 베이지안 이론을 적용한 베이지안 네트워크를 기반으로 본 연구에서 제안한 운항사고 위기 모델을 이용해서 예측했다. 그리고 355건의 핵심 손상 사고기록으로 구성된 시나리오 그룹을 이용하여 제안한 모델의 적용 가능성을 평가하였다. 평가결과, 예측한 PI의 정답률 $r_{Acc}$은 82.8%로 나타났고, $S_p{\gg}1.0$$S_p{\ll}1.0$에 포함되는 PI 변수들의 민감도 초과비율은 10% 이내로 나타났으며, 예측한 SI의 평균 오차 $\bar{d_{SI}}$는 0.0195로 나타났고, 예측한 RI의 정답률은 91.8%로 나타났다. 이러한 결과는 제안한 모델과 방법이 실제 해상운송 현장에 적용 가능함을 나타낸다.

Keywords

References

  1. 구자영,임정빈 (2001), "해상안전용 위기관리 시스템 구축을 위한 기초 연구" 2001 년 춘계해양관련학회 공동 학술발표회 논문집,한국항해학회,pp.80-86
  2. 엄정빈,구자영 (2000) , "해양경찰청의 위기상황 가시화 시스템 구축" 한국항해학회 추계학술발표회 논문집,pp.45-49
  3. 임정빈 (2003a) ,"해양사고 예보 시스템 개발(1) : 해양사고수량화 D/B 구축과 분석" 한국항해항만학회지, 제 27권 4호, pp.359-364 https://doi.org/10.5394/KINPR.2003.27.4.359
  4. 임정빈(2003b) , "해양사고 예보 시스템 개발(II) : 해양사고 예측모텔 구현" 한국항해항만학회지, 제 27권 5호,pp.487-492 https://doi.org/10.5394/KINPR.2003.27.5.487
  5. 임정빈 (2003c), "해양사고 예보 시스템 개발(Ill) : 3차원통계 가시화 시스템 구축" 한국항해항만학회지,제 28 권 1호,pp.17-29
  6. 임정빈,김대회,장진민 (2007) ,"선박관리회사의 운항사고 예측 시스템 기초설계" 2007년도 한국항해항만학회 춘계 학술대회(제1권),제31권 제1호, pp.301-308
  7. ABS(2000), "Guidance Notes on Risk Assessment Appliιution for the Marine Oil and Industries", Arnerican Bureau of Shipping, pp.1-144
  8. Eleye-Datubo, A. G., Wall,A., Saajedi,A., and Wang, J. (2006), "Enabling a Powerful Marine and Offshore Decision-Support Solution Through Bayesian Network Technique," Risk Analysis, Vol. 26, No. 3, pp.223-237 https://doi.org/10.1111/j.1539-6924.2006.00708.x
  9. Andrew, G., John, B. C., Hal,S. S., and Donald, B. R(2004), "Bayesian Data Analysis, Second Edition", Chapman & Hall/CRC, pp.1-137
  10. Christos, A. K. (2005), "Formal Safety Assessment: a critical review and Future Role", Diploma Thesis, National Technical University of Athens, pp.1-138
  11. Curtis, L. S.(1998), "Calculating Conditional Core Damage Probabilities for Nuclear Power Plant Operation," Reliability Engineering and System Safety, VoL 59, pp.299-307 https://doi.org/10.1016/S0951-8320(97)00152-X
  12. DNV(2002), "Marine Risk Assessment", Offshore Technology Report 2001/063, Det Norske Veritas, pp.1-72
  13. Harvard, J. T., Eirik, S., and Tim, F.(2001), "A Method for Assessing the Risk qf Sea Transportation : Numeriml Examples for the Oslofford", Det Norske Veritas, pp.1-8
  14. IMO(2002), "Guidelines for Formal Sqfety Assessment(FSA) for Use in the IMO Rule-Making Process", MSC/Circ. 1023, MEPC/Circ. 392
  15. IMO(2006) , "Amendments to the Guidance on the Use qf Human Element Analysing Process (HEAP) and Formal Safety Assessment (FSA) in the Rule-Making Process of IMO (MSC/Cir.l022-MEPC/Circ.391)", MSC-MEPC.2/ Circ.6
  16. Isabelle, A, Emmanuel, G., Jean-Baptiste, D., and Judith, R(2008), "Quantitative Risk Assessment from Farm to Folk and Beyond: A Global Bayesian ApproachConcerning Food-Borne Diseases," Risk Analysis, Vol.28, No.2, pp.557-571 https://doi.org/10.1111/j.1539-6924.2008.01000.x
  17. Jason, R W., Menick, J Rene, V. D., Jack, H, Thomas, M., John, E. S., and Martha, G.(2000), "A Systems Approach to Managing Oil Transportation Risk in Prince William Sound," System Engineering, 3:3, pp.128-142 https://doi.org/10.1002/1520-6858(200033)3:3<128::AID-SYS2>3.0.CO;2-R
  18. Jason, R W. M., and Rene, V. D.(2006), "Speaking the Truth in Maritime Risk Assessment," Risk Analysis, Vol. 26, No.1, pp.223-237 https://doi.org/10.1111/j.1539-6924.2006.00708.x
  19. Joseph, F., and Donald, B. R(1982), "Probabilistic Models for Risk Assessment," Risk Analysis, VoL 2, No.1, pp.1-8 https://doi.org/10.1111/j.1539-6924.1982.tb01397.x
  20. Judea, P.(2008), "GAUSALITY: Models, Reasoning, and Inference", Sth Printing, Cambridge University Press, pp.9-24
  21. Kevin, P. M.(2002), "Dynamic Bayesian Networks: Representation, Inference and Learning", Ph. D. Thesis, Computer Science in the Graduate Division of the University of California, Berkeley, pp.1-212
  22. Kelvin, P. M.(2007), "Bayes Net Toolbox for Matlab", http://www.cs.ubc.ca
  23. Kelvin, P. M.(2007), "Bayes Net Toolbox for Matlab", http://www.cs.ubc.ca
  24. Louis, A. C., Jr. Djangir, B., and William, H.(2005), "Some Limitation of Qualitative Risk Rating Systems," Risk Analysis, Vol. 25, No.3, pp.651-662 https://doi.org/10.1111/j.1539-6924.2005.00615.x
  25. Marcus, A (2002), "Uncertainty in Quantitative Risk Analysis Characterisation and Methods of Treatment", Department of Fire Safety Engineering,Lund University, Sweden, Report 1024
  26. Martha, G., Jason, M., John, R H, Tom, M., and Rene, V. D.(2000), "Risk Modeling in Distributed, Large-Scale Systems," Revised for IEEE Systems, Man & Cybernetics: A, pp.1-37
  27. Maxine, E. D., John, E. T., M, J S., and Kevin, P. B. (1996) , "Risk-Based Environmental Remediation: Bayesian Monte Carlo Analysis and the Expected Value of Sample Information," Risk Analysis, Vol. 16, No.1, pp.67-79 https://doi.org/10.1111/j.1539-6924.1996.tb01437.x
  28. MCA(2005), "Formal Safety Assessment & Research Projects on Domestic Passenger Vessel Standards - A Synopsis", Maritime and Coastguard Agency, U.K., pp.1-48
  29. Michael, D. A, Alan, B., and Michael, G.(1997), "A Probabilistic Analysis Of Tanker Groundings," 7th International Offshore and Polar Engineering Conference, Honolulu, Hawaii, pp.1-19
  30. Stanley, K., and Garrick, B. J(1981), "On The Quantitative Definition of Risk," Risk Analysis, Vol.1, No.1, pp.11-27 https://doi.org/10.1111/j.1539-6924.1981.tb01350.x
  31. Timothy, A w., Kishore, G., and Stephen, B.(1997),"Development of Risk-Based Ranking Measures of Effectiveness for the United States Coast Guard'sVessel Inspection Program," Risk Analysis, Vol. 17, No. 3, pp.333-340 https://doi.org/10.1111/j.1539-6924.1997.tb00871.x
  32. Timothy, G. F. and Eirik, S.(2000), "Modeling Ship Transportation Risk," Risk Analysis, Vol. 20, No.2, pp.225-244 https://doi.org/10.1111/0272-4332.202022
  33. USCG(2007), "Risk-Based Decision-Making Guidelines", http:;/www.uscg.mil
  34. Yuanhua, Q.(2006), "Quantitative Transportation Risk Analysis Based on Available Data/Dam Base: Decision Support Tools for Hazardous materials Transportation", Ph. D. Thesis, Graduate Studies of Texas A&M University, pp.1-174

Cited by

  1. Development of Quantitative Risk Assessment Methodology for the Maritime Transportation Accident of Merchant Ship vol.33, pp.1, 2009, https://doi.org/10.5394/KINPR.2009.33.1.009