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Grounding Probability in Narrow Waterways

Published online by Cambridge University Press:  02 July 2019

Şirin Özlem ,
Yiğit Can Altan ,
Emre N. Otay  and
İlhan Or
Şirin Özlem*
Affiliation:
(Department of Industrial Engineering, MEF University, Istanbul, Turkey)
Yiğit Can Altan
Affiliation:
(Department of Civil Engineering, Bahcesehir University, Istanbul, Turkey)
Emre N. Otay
Affiliation:
(Department of Civil Engineering, Bogazici University, Istanbul, Turkey)
İlhan Or
Affiliation:
(Department of Industrial Engineering, Bogazici University, Istanbul, Turkey)
*
(E-mail: [email protected])
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Abstract

The Strait of Istanbul is one of the world's busiest, narrowest and most winding waterways. As such, there is a high grounding probability for vessels. Although a number of grounding probability models exist, they have been deemed unsuitable by local maritime experts, due to their insufficient stopping distance criteria for narrow waterways. Thus, there is a need for a new model. This paper proposes a two-component grounding probability model that multiplies the geometric grounding probability (calculated with a kinematic-based model) with the causation probability (calculated with a specially designed Bayesian network). The geometric probability model is improved in terms of stopping distance parameters and the Bayesian network is crafted for narrow waterways. The model is then deployed with pre-determined parameters within the Strait of Istanbul to run risk analysis scenarios. The results, validated with actual grounding records, show that the causation probability is the key component for quantifying the probability of grounding in narrow waterways. If navigated without frequent evasive manoeuvres, grounding would be almost inevitable. Although this study focuses on the Strait of Istanbul, the proposed approach can be applied to research into grounding probability of vessels navigating through other waterways.

Keywords

Human FactorModellingRiskStraits
Type
Research Article
Information
The Journal of Navigation , Volume 73 , Issue 2 , March 2020 , pp. 267 - 281
Copyright
Copyright © The Royal Institute of Navigation 2019

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References

REFERENCES

Akten, N. (2004). Analysis of shipping casualties in the Bosphorus. The Journal of Navigation, 57(3), 345–356. doi:10.1017/S0373463304002826.CrossRefGoogle Scholar
Altan, Y. C. and Otay, E. N. (2017). Maritime traffic analysis of the Strait of Istanbul based on AIS data. The Journal of Navigation, 70(6), 1367–1382. doi:10.1017/S0373463317000431.CrossRefGoogle Scholar
Altan, Y. C. and Otay, E. N. (2018). Spatial mapping of encounter probability in congested waterways using AIS. Ocean Engineering, 164, 263–271. doi:10.1016/J.OCEANENG.2018.06.049.CrossRefGoogle Scholar
ANNEX II: Risk Assessment-Large Passengr Ships-Navigation. (2019). Available at: http://research.dnv.com/skj/FSALPS/ANNEXII.pdf (Accessed: 25 January 2019).Google Scholar
Candanoglu, O. (2013). Scheduling Transit Vessels in the Istanbul Strait. Bogazici University.Google Scholar
Fujii, Y., Oshima, R., Yamanouchi, H. and Mizuki, N. (1974). Some factors affecting the frequency of accidents in marine traffic: I-the diameter of evasion for crossing encounters, II-the probability of stranding, III-the effect of darkness of the probability of collision and stranding. The Journal of Navigation, 27, 239–247.10.1017/S0373463300025960CrossRefGoogle Scholar
Hänninen, M. (2014). Bayesian networks for maritime traffic accident prevention: Benefits and challenges. Accident Analysis & Prevention, 73, 305–312. doi:10.1016/J.AAP.2014.09.017.CrossRefGoogle ScholarPubMed
Hänninen, M. and Kujala, P. (2012). Influences of variables on ship collision probability in a Bayesian belief network model. Reliability Engineering & System Safety, 102, 27–40. doi:10.1016/J.RESS.2012.02.008.CrossRefGoogle Scholar
Ince, A. N. and Topuz, E. (2004). Modelling and simulation for safe and efficient navigation in narrow waterways. The Journal of Navigation, 57(1), 53–71. doi:10.1017/S0373463303002510.CrossRefGoogle Scholar
Kristiansen, S. (2005). Maritime Transportation:Safety Management and Risk Analysis. London: Routledge.Google Scholar
Macduff, T. (1974). The Probability of Vessel Collisions. Ocean Industry, 9(9), 144–148.Google Scholar
Marmaray – Maritime Pilot. (2019). Available at: http://www.vda.org.tr/duyuru/marmaray--kilavuz-kaptan/1115 (Accessed: 29 January 2019).Google Scholar
Mazaheri, A. (2009). Probabilistic Modeling of Ship Grounding. Helsinki University of Technology, 48–56.Google Scholar
Or, I. and Kahraman, I. (2002). A simulation study of the accident risk in the Istanbul Channel. International Journal of Emergency Management, 1(2), 110–124. doi:10.1504/IJEM.2002.000514.CrossRefGoogle Scholar
Özlem, Ş. (2018). Risk Analysis and Modeling of the Maritime Traffic in the Strait of Istanbul. Bogazici University.Google Scholar
TSMS. (2018), Long-term weather data recorded at the Kumköy Meteorology Station, Istanbul Regional Directorate, Turkish State Meteorological Services.Google Scholar
Turkish Ministry of Transport, Maritime and Communications. (2018). Official records of maritime accidents in Turkish waters. Accessible at: http://atlantis.udhb.gov.tr/denizkaza/yayin/aakb_bolsonuc.asp?BOLGE=ISTANBUL&Submit=ARA (Accessed: 24 September 2018).Google Scholar
The Navigator. (2014). Bridge Resource Management:Working as a Cohesive Team. The Nautical Institute. Available at: https://www.nautinst.org/uploads/assets/uploaded/9035e6d8-7886-49f1-994501926c5f5e6d.pdfGoogle Scholar
Turkish Straits Maritime Traffic Regulations. (TSMTR). (1998). Official Gazette: 23515 Repeat Published.Google Scholar
Turkish Straits Sea Traffic Scheme. (2018). Implementation Instructions of Sea Traffic Regulations in Turkish Straits. English version published in the website of the Maritime Association of Ship Owners and Agents on 20 July 2018. Accessible at: http://www.vda.org.tr/upload/duyuru/20.07.2018-UYGULAMATALIMATI_ENG.pdf (Accessed: 4 February 2019).Google Scholar
Wiegerinck, W., Burgers, W. and Kappen, B. (2013). Bayesian Networks, Introduction and Practical Applications. Springer, Berlin, Heidelberg, 401–431. doi:10.1007/978-3-642-36657-4_12.Google Scholar