Determination of Risk Factors Caused By Ships in Port Planning

Year 2019, Volume: 6 Issue: 3, 254 - 263, 08.12.2019

Mehmet Ersin Yücel , Cemil Yurtören

https://doi.org/10.30897/ijegeo.641434

Cited By: 3

Abstract

World Economy has been globalizing faster then ever as a
result of the technological evolution. Increase of global trade brings the need
of higher transportation capacity as bigger ships and port facilities. Port
construction and expansion investments can be said to be supply to meet demand.
Maritime safety is one of the factors affecting the zoning plan approval
process in the port construction and extension investments. These factors
mostly caused by the ship maneuver. One of the most widely used models is the
Environmental Stress (ES) Model in risk assessment of navigation and ship
maneuver.

ES Model measures the risk occurring around the ship
during the berthing / unberthing maneuvers performed in the simulation
environment with the ports and ships that are modeled similar to the port
project. But, it is not certain which parameter of the port project will be
revised such as ship tonnageand length of the ship, port form and size etc. The
main benefit of this study is taking precaution with measuring risk by
specifying the risk factors and their weights using both ES Model and fuzzy
logic method. Thus, the development plan and project evaluation process, which
is under the duty and responsibility of the Turkish Ministry of Transport, will
be carried out in terms of safety with the method proposed in this study.
Another important contribution of this study is its originalty in terms of
clarification of raw outputs of ES model reports by using fuzzy logic method in
scientific literature.

So, the revised port project will be realized by
providing maritime safety. While port projects are approved by the Ministry of
Transport within the scope of the legislation that determines the port planning
process in question, the evaluation of Modeling Reports with fuzzy logic method
will contribute to both fast and safe project design process.

Keywords

ES (Environmental Stress) model, fuzzy logic, risk assessment, port planning

References

• Başbuğ, A. (1994). “Fuzzy Technology”, Byte, February, 147-152.
• Dco.uscg.mil. (2019). Ports and Waterways Safety Assessment (PAWSA). [online] Available at: https://www.dco.uscg.mil/PAWSA/ [Accessed 23 Oct. 2019]
• Ford, D. Sterman, J. D. (1998). Expert knowledge elicitation to improve mental and formal models. System Dynamics Review, 14(4), 309-340
• Friis-Hansen, P.(2008) Basic Modelling Principles For Prediction of Collision and Grounding Frequencies Working Document
• Gucma, L., & Pietrzykowski, Z. (2006). Ship Manoeuvring in Restricted Areas: An Attempt to Quantify Dangerous Situations Using a Probabilistic-Fuzzy Method. Journal Of Navigation, 59(2), 251-262.
• Hsu, H. M. Chen, T. C. (1994). Aggregation of fuzzy opinion under group decision making. Fuzzy Sets and Systems, 79(3), 279, 285
• Hu, S., Fang, Q., Xia, H., Xi, Y. (2007). Formal safety assessment based on relative risks model in ship navigation. Reliability Engineering & System Safety. 92. 369-377.
• Imo.org. (2019). Formal Safety Assessment. [online] Available at: http://www.imo.org/en/OurWork/Safety/SafetyTopics/Pages/FormalSafetyAssessment.aspx [Accessed 23 Oct. 2019].
• Inoue, K., Masuda, K., Sera, W. (1998). Guidelines to Assess the Safety of Marine Traffic-I : Evaluation of Shiphandling Difficulty based on the Environmental Stress Model. The Journal of Japan Institute of Navigation. 98. 225-234. 10.9749/jin.98.225.
• Kahraman, C., & Kaya, I. (2010). A fuzzy multicriteria methodology for selection among energy alternatives. Expert Syst. Appl. 37, 6270-6281.
• Kim, K. I., Jeong J.S., Park G.K. (2012). A Study on the Quantitative Risk Assessment of Mokpo Entrance Waterway by IWRAP, Proceedings of 2012 KOSOMES Spring Conference, pp. 253-256.
• Korta, J. P., Lee, M. P., Einsberg, N., Dewispelare, A. (1996). Branch technical position on the use of expert elicitation in the high-level radioactive waste program. 1st Ed. U.S. Nuclear Regulatory Comission.
• Ministry of Environment and Urbanization (2011), Notification Regarding Planning and Implementation Process in Coastal Structures and Facilities, Ankara, Turkey
• Ministry of Transport (2005), Transportation Master Plan Strategy Project, Ankara, Turkey
• Ministry of Transport (2010), Coastal Structures Master Plan, Ankara, Turkey
• Navcen.uscg.gov. (2019). Ports and Waterways Safety Assessment. [online] Available at: https://www.navcen.uscg.gov/?pageName=pawsaMain [Accessed 23 Oct. 2019].
• Park, Y.S., Jae-Yong, J., Inoue K. (2002). A Study on Assessment of Vessel Traffic Safety Management by Marine Traffic Flow Simulation. Journal of the Korea Society for Simulation. 11.
• Senol Y.E.(2014), Fault Tree Analysis of Chemical Cargo Contamination By Fuzzy Approach (MSc thesis), Istanbul Technical University, Istanbul, Turkey
• Sii, H., Wang, J. and Ruxton, T. (2001). A Fuzzy-Logic-Based Approach to Subjective Safety Modelling for Maritime Products. Safety and Reliability, 21(2), pp.65-78.
• Son, N.S., Kim, S.Y., Gong, I.Y. (2009). Study on the Estimation of Collision Risk of Ship in Ship Handling Simulator using Fuzzy Algorithm and Environmental Stress Model. Journal of Korean navigation and port research.
• Wang, J.(2001).Current status of future aspects of formal safety assessment of ships. Safety Science, 38, 19–30.
• Yurtören C., Duru O., Satir T. The Environmental Effects of Projected Container Terminal to the Safely Manoeuvring Journal Vol. 2 No. 1 - March 2008
• Z. Wang, M. Zoghi, F. Hutter, D. Matheson, and N. de Freitas. (2013) Bayesian Optimization in a Billion Dimensions via Random Embeddings. ArXiv e-prints, January
• Zadeh, L.A.(1965) “Fuzzy Sets.” Information and Control, vol. 8, no. 3, June 1965, pp. 338–353, 10.1016/s0019-9958(65)90241-x. Accessed 20 May 2019.
• Zhao, R. Govind, R. (1991). Defuzzification of fuzzy intervals. Fuzzy Sets and Systems, 43(1), 45-55Sugeno in 1985 (Sugeno, 1999).