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Research on coupling mechanism of intelligent ship navigation risk factors based on N-K model

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Abstract

In order to provide theoretical and practical supports for the risk prevention and management of intelligent ship at sea, a N-K model is adopted to investigate the coupling mechanism of risk factors of intelligent ship. Firstly, the navigation risks of intelligent ships are divided into four aspects: navigation environment perception, remote control center, environment and emergency management, and then the risk factors affecting the safety are analyzed. The risk coupling is divided into single factor coupling, double factor coupling and multiple factor coupling. Secondly, the formation mechanism of coupling risk is analyzed based on the concept of comprehensive security threshold. Finally, a N-K model is used to describe the coupling relationship within the system quantitatively. For the first time, a case study of N-K model was carried out based on 299 maritime accident statistics data matching intelligent ships released by major maritime agencies from 2011 to 2021. The results show that the coupling risk factors are proportional to the coupling information interaction value, and the coupling information interaction value determines the occurrence probability of safety accidents; the factors of remote control center have the greatest influence on coupling information interaction value. In the construction and operation of intelligent ships in the future, managers should strengthen the construction and control of remote control center, avoid multi-factor coupling, pay more attention to the weak link of navigation risk, establish an anti-coupling mechanism, and improve the safety of intelligent ship production and operation.

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References

  1. Shi J (2012) “costa concorde” tragedy, China Ship Inspection (2): 22–24

  2. Kee D, Jun GT, Waterson P, Haslam R (2017) A systemic analysis of south korea sewol ferry accident-striking a balance between learning and accountability. Appl Ergon 59:504–516

    Article  Google Scholar 

  3. Kong X, Zhu J, Xue M (2018) Analysis of the causes and responsibilities of the collision accident between “sanji’’ and “changfeng crystal’’. World Shipping 41(6):1–8

    Google Scholar 

  4. Yin G, Sun Y, Yang D, Li S, Li Z (2021) Analysis and research of typical cases of ship safety accidents. Ship 32(04):1–14

    Google Scholar 

  5. Lu K (2020) Oil spill thousands of tons, “Mauri SOS” who can respond. China Petrol Petrochem Corp 16:44–47

    Google Scholar 

  6. Zhu J, Qiu W (2021) The influence of “Changi” super large container ship grounding accident and its enlightenment to the development of Chinese Marine industry. Integr Transp 43(04):95–100

    Google Scholar 

  7. Wang H, Liu Z (2021) Coupling analysis of marine traffic safety risk factors based on N-K model. J Safety Environ 21(01):56–61

    Google Scholar 

  8. Lin J, Li K, Zhang B (2011) Research on intrinsic safety management of aviation equipment based on risk coupling theory. China’s Saf Prod Sci Technol 7(9):75–79

    Google Scholar 

  9. Huang W, Shuai B, Sun Y (2019) Research on the formation mechanism of coupling risk in railway dangerous goods transportation system based on n-k model. Railway J 41(5):1–9

    Google Scholar 

  10. Hu X, Yan X (2015) Construction safety evaluation of construction projects based on risk coupling mechanism. Saf Environ Eng 22(6):134–138

    Google Scholar 

  11. Zhu J, Chen G, Meng X, Yang Y (2020) Coupling risk analysis of deepwater blowout accident based on n-k model

  12. Deng J, Liu S, Xie C, Liu K (2021) Risk coupling characteristics of maritime accidents in chinese inland and coastal waters based on nk model. J Marine Sci Eng 10(1):4

    Article  Google Scholar 

  13. Yousaf J, Shin J, Kim K, Youn J, Lee D, Hwang C, Nah W (2017) System level esd coupling analysis using coupling transfer impedance function. IEEE Trans Electromagn Compat 60(2):310–321

    Article  Google Scholar 

  14. Xiao C, Liu Y (2022) Electro-magnetic-thermal-mechanical coupling analysis of material damage under long-duration lightning current arc. Chin Soc Electr Eng 42(22):8382–8390

    Google Scholar 

  15. Wang J, Zheng T, Liu X, Zhang Q, Zhao C (2021) Research on the safety risk coupling of fruit and vegetable cold chain logistics based on n-k model. Transp Res 7(2):11–19

    Google Scholar 

  16. Zhang W, Zhang Y, Zhang C (2022) Navigation risk identification and screening of intelligent ships based on hhm-rfrm theory. J Safety Environ 1–10

  17. Yan X, Wang S, Ma F (2021) Research status and development thinking of intelligent freight ships. Chin Ship Res 16(1):1–6

    Google Scholar 

  18. Ding Z, Zhang X, Wang C, Li Q, An L (2021) Intelligent decision-making method for collision avoidance of unmanned ships based on driving practice. Chin Ship Res 16(1):96–104

    Google Scholar 

  19. Zou Z (2019) Risk assessment algorithm for unmanned ship navigation under complex navigation conditions, Master’s thesis, Dalian Maritime University

  20. Yao H (2019) Research on navigation risk identification and accident cause analysis of autonomous cargo shipping vessels, Ph.D. thesis, Wuhan: Wuhan University of Technology

  21. Zhou X (2020) Research on hazard analysis method for autonomous ships, Ph.D. thesis, Dalian Maritime University

  22. Yuan X, Zhang D, Zhang J, Zhang M, Soares CG (2021) A novel real-time collision risk awareness method based on velocity obstacle considering uncertainties in ship dynamics. Ocean Eng 220:108436

    Article  Google Scholar 

  23. Chang C-H, Kontovas C, Yu Q, Yang Z (2021) Risk assessment of the operations of maritime autonomous surface ships. Reliab Eng Syst Saf 207:107324

    Article  Google Scholar 

  24. Ventikos NP, Chmurski A, Louzis K (2020) A systems-based application for autonomous vessels safety: hazard identification as a function of increasing autonomy levels. Saf Sci 131:104919

    Article  Google Scholar 

  25. Utne IB, Rokseth B, Sørensen AJ, Vinnem JE (2020) Towards supervisory risk control of autonomous ships. Reliab Eng Syst Saf 196:106757

    Article  Google Scholar 

  26. Kim D-H (2020) Identification of collision risk factors perceived by ship operators in a vessel encounter situation. Ocean Eng 200:107060

    Article  Google Scholar 

  27. Bolbot V, Theotokatos G, Boulougouris E, Vassalos D (2020) A novel cyber-risk assessment method for ship systems. Saf Sci 131:104908

    Article  Google Scholar 

  28. Im N, Luong TN (2019) Potential risk ship domain as a danger criterion for real-time ship collision risk evaluation. Ocean Eng 194:106610

    Article  Google Scholar 

  29. Wróbel K, Montewka J, Kujala P (2018) Towards the development of a system-theoretic model for safety assessment of autonomous merchant vessels. Reliab Eng Syst Saf 178:209–224

    Article  Google Scholar 

  30. Clarke L. J, Macfarlane G. J, Penesis I, Duffy J. T, Matsubara S, Ballantyne R. J (2017) A risk assessment of a novel bulk cargo ship-to-ship transfer operation using the functional resonance analysis method, in: International Conference on Offshore Mechanics and Arctic Engineering, Vol. 57663, American Society of Mechanical Engineers, p. V03BT02A019

  31. Akyuz E, Celik E (2018) The role of human factor in maritime environment risk assessment: a practical application on ballast water treatment (bwt) system in ship. Human Ecol Risk Assess 24(3):653–666

    Article  Google Scholar 

  32. Chou C-C, Wang C-N, Hsu H-P (2022) A novel quantitative and qualitative model for forecasting the navigational risks of maritime autonomous surface ships. Ocean Eng 248:110852

    Article  Google Scholar 

  33. Liu C, Chu X, Wu W, Li S, He Z, Zheng M, Zhou H, Li Z (2022) Human-machine cooperation research for navigation of maritime autonomous surface ships: a review and consideration. Ocean Eng 246:110555

    Article  Google Scholar 

  34. Sheng R (2019) Systems engineering for aerospace: a practical approach. Academic Press, New York

    Google Scholar 

  35. Wang H, Liu Q (2016) Causation mechanism of human factors in water vessel traffic accidents. China Navig 39(3):41–44

    Google Scholar 

  36. Meng Q (2016) Navigation safety management countermeasures in the bay of biscay in bad weather, Master’s thesis, Dalian Maritime University

  37. Jiang N (2011) Research on traffic safety emergency management system based on risk coupling, Ph.D. thesis, Wuhan University of Technology

  38. Liu T, Luo F (2012) Analysis of air traffic safety risk composition and coupling relationship. J Wuhan Univ Tech Inf Manag Eng Edition 34(1):93–97

    Google Scholar 

  39. Guo D (2020) Analysis and thinking of milano bridge wheel collision accident. J Qingdao Ocean Shipping Vocational College 41(4):30–34

    Google Scholar 

  40. Wright S et al (1932) The roles of mutation, inbreeding, crossbreeding, and selection in evolution. In: Proceedings of the sixth international congress of genetics, Ithaca, New York

  41. Kauffman SA et al (1993) The origins of order: self-organization and selection in evolution. Oxford University Press, Oxford

    Google Scholar 

  42. Li B, Lv J, Li J (2020) Evaluation of emergency support capability of key nodes in maritime transportation based on improved copula. Transp Syst Eng Inf 20(2):20–25

    Google Scholar 

  43. Huang W, Shuai B, Sun Y, Li M, Pang L (2018) Entropy-topsis coupling coordination method to evaluate the risk of railway dangerous goods transportation system. Chin J Saf Sci 28(2):134–138

    Google Scholar 

  44. Pan W, Liu S, Xu Y (2022) Urban waterlogging simulation and risk assessment based on multi-dimensional coupling model, Shaanxi Water Conservancy (10) 19–22

  45. Zhou Q (2022) Study on coupled early-warning method of tower crane operation risk based on finite element analysis. Eng Technol Res 7(13):106–108

    Google Scholar 

  46. Yan W, Men X, Yang F (2019) Risk assessment of subway construction based on interaction matrix. J Wuhan University (Engineering Science) 52(09):796–801

    Google Scholar 

  47. Huang W, Yin D, Xu Y, Zhang R, Xu M (2022) Using n-k model to quantitatively calculate the variability in functional resonance analysis method. Reliab Eng Syst Saf 217:108058

    Article  Google Scholar 

  48. Chen Y, Song F, Zhou C (2018) Study on coupling risk of civil aviation maintenance personnel error events based on n-k model. J Civil Aviation Flight College of China 29(04):72–75+80

  49. Yang T, Shuai B, Huang W (2019) Coupling risk analysis of road dangerous goods transport system based on n-k model. Chin J Saf Sci 29(9):132

    Google Scholar 

  50. Fu B, Jiang H, Xu T, Yao A (2018) Coupling analysis of possible failure factors of urban gas pipeline based on n-k model. China Saf Prod Sci Techno 14(2):145–149

    Google Scholar 

Download references

Acknowledgements

This research was funded by the LiaoNing Revitalization Talents Program (Grand number XLYC1902071).

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  1. Navigation College, Dalian Maritime University, Dalian, 116026, PR China

    Wenjun Zhang & Yingjun Zhang

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  1. Wenjun Zhang
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  2. Yingjun Zhang
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Correspondence to Wenjun Zhang or Yingjun Zhang.

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Zhang, W., Zhang, Y. Research on coupling mechanism of intelligent ship navigation risk factors based on N-K model. J Mar Sci Technol 28, 195–207 (2023). https://doi.org/10.1007/s00773-022-00919-0

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