A framework for reliability assessment of ship hull damage under ship bow impact
Ship collision analysis outcomes are generally used in computational models to derive damage distributions. However, damage is usually assessed after the collision energy has been fully absorbed by structural members rather than at the onset of outer hull fracture. Furthermore, the deformation behav...
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| Vydáno v: | Ships and offshore structures Ročník 11; číslo 7; s. 700 - 719 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Cambridge
Taylor & Francis
02.10.2016
Taylor & Francis Ltd |
| Témata: | |
| ISSN: | 1744-5302, 1754-212X |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Ship collision analysis outcomes are generally used in computational models to derive damage distributions. However, damage is usually assessed after the collision energy has been fully absorbed by structural members rather than at the onset of outer hull fracture. Furthermore, the deformation behaviour of ship structural members under load depends on uncertainty modelling through material, geometric, and structural considerations, captured in an appropriate reliability framework. To consider these significant missed opportunities in understanding the probability of ship structures meeting their performance targets during collisions, a novel stochastic framework is proposed in this paper. For efficient reliability computations, a plate resistance model is developed for hull damage assessment at the onset of failure. Stochastic modelling capabilities of Python scripting are interfaced with Abaqus
®
to compute the stochastic response. The reliability computations show that the probability of hull fracture increases as the hull deformation progresses, with maximum values occurring at the onset of outer hull fracture. The framework outcomes are useful in determining optimal ship structural design capabilities. |
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| Bibliografie: | SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 1744-5302 1754-212X |
| DOI: | 10.1080/17445302.2015.1051281 |