A method for the direct assessment of ship collision damage and flooding risk in real conditions

Mingyang Zhang, Fabien Conti, Hervé Le Sourne, Dracos Vassalos, Pentti Kujala, Daniel Lindroth, Spyros Hirdaris

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Collision accidents may lead to significant asset damage and human casualties. This paper introduces a direct analysis methodology that makes use of Automatic Identification System (AIS) data to estimate collision probability and generate scenarios for use in ship damage stability assessment. Potential collision scenarios are detected from AIS data by an avoidance behaviour-based collision detection model (ABCD-M) and the probability of collision is estimated in various routes pertaining to a specific area of operation. Damage extents are idealised by the Super – Element (SE) method accounting for the influence of surrounding water in way of contact. Results are presented for a Ro - Pax ship operating from 2018 to 2019 in the Gulf of Finland. It is confirmed that collision probability is extremely diverse among voyages and the damages obtained correlate well with those adopted by the UN IMO Regulatory Instrument SOLAS (2020). It is concluded that the method is by nature sensitive to traffic features in the selected case study area. Yet, it is useful for the evaluation of flooding risk for ships operating in real hydro-meteorological conditions.

Original languageEnglish
Article number109605
Number of pages20
JournalOcean Engineering
Volume237
Early online date7 Aug 2021
DOIs
Publication statusPublished - 1 Oct 2021

Keywords

  • big-data analytics
  • collisions
  • damage stability
  • flooding risk
  • passenger ships
  • super-element method

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