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Title
Risk analysis of maritime accidents in an estuary: a case study of Shenzhen Waters

ISSN printed: 1733-8670, ISSN on-line: 2392-0378
Chen, Pengfei1; Mou, Junmin2; Li, Yajun3
URI: https://repository.am.szczecin.pl/handle/123456789/760
2015-06-10
Due to the unique geographic location, complex navigation environment and intense vessel traffic, a considerable number of maritime accidents occurred in estuarine waters during recent years which caused serious loss of life, property and environmental contamination. Based on the historical data of maritime accidents from 2003 to 2012, which is collected from Shenzhen Maritime Safety Administration, this paper conducted a risk analysis of maritime accidents by applying Bayesian network and fault tree analysis. First a Bayesian network model was introduced to describe the consequence of accidents based on the accident investigation report. Then fault tree analysis was applied to estimate the probability on the basis of accident statistics and ship traffic flow. Finally the risk of maritime accidents in Shenzhen Waters was depicted through the consequence multiplied by the probability of an accident.
  1. CELIK, M. & CEBI, S. (2009) Analytical, HFACS for investigating human errors in shipping accidents. Accident Analysis & Prevention. 41(1). pp. 66–75.,
  2. CHAUVIN, C., LARDJANE, S., MOREL, G. et al. (2013) Human and organizational factors in maritime accidents: analysis of collisions at sea using the HFACS. Accident Analysis & Prevention. 59. pp. 26–37.,
  3. CHEN, P., MOU, J. et al. (2014) Mining of Accident Data for Vessels Collided in Estuary. Proceedings of the 3rd international workshop on next generation of nautical traffic model (IWNTM 2014).,
  4. GOERLANDT, F. & MONTEWKA, J. (2014) A probabilistic model for accidental cargo oil outflow from product tankers in a ship–ship collision. Marine Pollution Bulletin. 79(1–2). pp. 130–144.,
  5. GUO, Q. et al. (2007) Analysis of maritime vessel accident based on fusion of case study and fault tree analysis.,
  6. HÄNNINEN, M. (2014) Bayesian networks for maritime traffic accident prevention: Benefits and challenges. Accident Analysis & Prevention. 73. pp. 305–312.,
  7. HU, S., FANG, Q., ZHANG, J. & CAI, C. (2010) Risk Assessment of Marine Traffic Safety in Coastal Water Area. Navigation of China. 33(1). pp. 50–55.,
  8. KAPLAN, S. (1997) The words of risk analysis. Risk Anal. 17. pp. 407–17.,
  9. LI, H. (2012) Marine Traffic Accident Characteristics and Cause Analysis Research in the Changshantou Water area. Wuhan University of Technology.,
  10. LI, S. (2010) Petri net based vessel collision accident causation analysis. Journal of Dalian Maritime University. 36 (4). pp. 5–7.,
  11. MAZAHERI, A., MONTEWKA, J., NISULA, J. & KUJALA P. (2015) Usability of accident and incident reports for evidence- based risk modeling. A case study on ship grounding reports. Safety Science. 76. pp. 202–214.,
  12. MONTEWKA, J. et al. (2014) A framework for risk assessment for maritime transportation systems. A case study for open sea collisions involving RoPax vessels. Reliability Engineering & System Safety. 124. pp. 142–157.,
  13. MOU, J., GAN, L. & XU H. (2008) Study on Safety criteria in port area based on risk theory.,
  14. QU, X., MENG, Q. & SUYI, L. (2011) Ship collision risk assessment for the Singapore Strait. Accident Analysis & Prevention. 43(6). pp. 2030–2036.,
  15. UNG, S. (2014) A novel maritime risk assessment model incorporating a fuzzy rule-based approach. Expert System. 31. pp. 398–408.,
  16. ZHANG, D. et al. (2013) Incorporation of formal safety assessment and Bayesian network in navigational risk estimation of the Yangtze River. Reliability Engineering & System Safety. 118. pp. 93–105.,

Title

Risk analysis of maritime accidents in an estuary: a case study of Shenzhen Waters

Pages

54-62

Figures

10

Tables

6

ISSN printed

1733-8670

ISSN on-line

2392-0378

DOI

10.17402/020

Type

Original scientific article

Journal

42 Scientific Journals of the Maritime University of Szczecin, no. 42 / 2015

Publisher

Scientific Journals Maritime University of Szczecin, Zeszyty Naukowe Akademia Morska w Szczecinie

Copyright Holder

Scientific Journals Maritime University of Szczecin, Zeszyty Naukowe Akademia Morska w Szczecinie

Published

2015-06-10

Recieved

2015-04-10

Accepted

2015-05-09

Funding

The work presented in this paper is financially supported by self-determined and innovative research funds of Wuhan University of Technology (Grant No.2015-zy-109).

Keywords

risk analysis, maritime accident, Bayesian network, fault tree analysis, estuarine waters, maritime safety

URI:

https://repository.am.szczecin.pl/handle/123456789/760

Language

English

Authors

Chen, Pengfei1; Mou, Junmin2; Li, Yajun3

Affiliation

1 Wuhan University of Technology, School of Navigation Hubei Key Laboratory of Inland Shipping Technology, Wuhan, China, pfchenly@outlook.com
2 Wuhan University of Technology, School of Navigation Hubei Key Laboratory of Inland Shipping Technology, Wuhan, China, moujm@whut.edu.cn
3 Department of Jiangsu Transportation Institute, Nanjing, China,

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