Maritime Transportation Risk Assessment of Tianjin Port with Bayesian Belief Networks

This article proposes a maritime transportation risk analysis that uses a Bayesian belief network model to conduct a risk assessment of the Tianjin port, a large sea-port in northern China. The authors first conduct a statistical analysis of historical crash data at this port from 2008 to 2013. The Bayesian belief network model is then used to explore the dependencies between the indicator variables and accident consequences. Crash scenarios that occurred over the years are compared in terms of probability as well as consequences. The authors identified several variables that have influence on the consequences, such as navigational area, ship type, and time of day. They conclude that their model is useful for providing a full picture of maritime risk in both the probability and consequence of crashes in the approaches to the Tianjin port. They also offer some specific suggestions for the port, including improve the traffic management in a section of the approach found to be the most risky segment, enhance the performance of search and rescue (SAR) operations, and pay special attention to traffic management during the night hours.


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  • Accession Number: 01618092
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jun 30 2016 11:30AM