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Residual strength of corroded ring-stiffened cylinder structures under external hydrostatic pressure

Corrosion damage to submarine pressure hulls is a crucial consideration during the structural design phase because it diminishes the structural strength of a submarine, reducing its operational depth and posing a severe risk to the life of the crew. This necessitates using a validated analytical met...

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Bibliographic Details
Published in:International journal of naval architecture and ocean engineering 2024, 15(0), , pp.1-9
Main Authors: Park, Sang-Hyun, Lee, Su-Min, Yu, Youngjae, Cho, Sang-Rai
Format: Article
Language:English
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Summary:Corrosion damage to submarine pressure hulls is a crucial consideration during the structural design phase because it diminishes the structural strength of a submarine, reducing its operational depth and posing a severe risk to the life of the crew. This necessitates using a validated analytical method to estimate the residual strength and assess the safety of corrosion-affected pressure hulls. This paper presents an experimental and numerical investigation of the residual strength of corroded ring-stiffened cylinders, which are typical components of submarine pressure hulls, the main legs of semi-submersibles, and Floating Offshore Wind Turbine (FOWT) foundations. Four steel ring-stiffened cylinder models were fabricated: two remained intact, whereas the other two were artificially corroded by machining. Hydrostatic collapse tests were conducted in a pressure chamber. To evaluate the effect of initial shape imperfections caused by welding fabrication on the strength of the structure, the initial shape imperfections were measured using a three-dimensional coordinate measuring machine. The experimental results illustrate a significant reduction in the residual strengths of the two damaged models compared with those of the intact models. The collapse processes simulated using the Abaqus software package are presented, demonstrating a close agreement between the experimental results and numerical predictions.
ISSN:2092-6782
2092-6790
DOI:10.1016/j.ijnaoe.2024.100590