A comparison of geometric imperfection models for collapse analysis of ship-type stiffened plated grillages

Shen Li, Dimitris G. Georgiadis, Do Kyun Kim, Manolis S. Samuelides

Research output: Contribution to journalArticlepeer-review

Abstract

The assessment of the buckling and ultimate collapse strength is a mandatory step in the ultimate limit state design of ship structures. The collapse analysis of ship-type stiffened panels under longitudinal compression is highly affected by initial geometric imperfection. Several geometric imperfection models are available in the literature. Broadly speaking, they can be categorised into deterministic and probabilistic approaches. The deterministic approach describes the initial deflection field with a presumed geometric shape and a characteristic maximum distortion magnitude. Several geometric deflection shapes are commonly adopted, including hungry-horse (HH) mode, Admiralty Research Establishment (ARE) mode and critical buckling (CM) mode. Each of these deflection mode shapes is used in conjunction with a characteristic maximum distortion magnitude. Except otherwise specified, an average-level magnitude is usually applied. By contrast, the probabilistic approach evaluates the initial geometric imperfection as a random field, generated based on the prescribed statistics. A comparative study is presented in this study in the light of analysing the uncertainty in ultimate compressive strength of stiffened plated grillages induced by different modelling of geometric imperfection. In addition, the influence of relative deflection in the adjacent panels is analysed. Recommendations for choosing an imperfection model for buckling analysis of ship-type stiffened plated structures are reported.
Original languageEnglish
Article number113480
Number of pages44
JournalEngineering Structures
Volume250
Early online date5 Nov 2021
DOIs
Publication statusE-pub ahead of print - 5 Nov 2021

Keywords

  • geometric imprefection
  • buckling
  • ultimate strength
  • stiffened panel
  • random field

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