Performance characterisation for risk assessment of striking ship impacts based on struck ship damaged volume

Abayomi Obisesan, Srinivas Sriramula (Corresponding Author)

Research output: Contribution to journalArticle

4 Citations (Scopus)
7 Downloads (Pure)

Abstract

Ship collision accidents are rare events but pose huge threat to human lives, assets, and the environment. Many researchers have sought for effective models that compute ship stochastic response during collisions by considering the variability of ship collision scenario parameters. However, the existing models were limited by the capability of the collision computational models and did not completely capture collision scenario, and material and geometric uncertainties. In this paper, a novel framework to performance characterisation of ships in collision involving a variety of striking ships is developed, by characterising the structural consequences with efficient response models. A double-hull oil carrier is chosen as the struck ship to demonstrate the applicability of the proposed framework. Response surface techniques are employed to generate the most probable input design sets which are used to sample an automated finite element tool to compute the chosen structural consequences. The resulting predictor-response relationships are fitted with suitable surrogate models to probabilistically characterise the struck ship damage under collisions. As demonstrated in this paper, such models are extremely useful to reduce the computational complexity in obtaining probabilistic design measures for ship structures. The proposed probabilistic approach is also combined with available collision frequency models from literature to demonstrate the risk tolerance computations.
Original languageEnglish
Pages (from-to)111-128
Number of pages18
JournalJournal of Marine Science and Application
Volume16
Issue number2
Early online date7 Apr 2017
DOIs
Publication statusPublished - Jun 2017

Keywords

  • ship collision
  • hull damage
  • numerical simulation
  • structural reliability
  • risk assessment

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