Compartment level progressive collapse strength as a method for analysing damaged steel box girders
Compartment level progressive collapse strength as a method for analysing damaged steel box girders
It is vital to be able to rapidly assess damaged ship structures. This ensures the safety of personnel and facilitation of the most effective repair or recovery. Interframe progressive collapse analysis has been used as a method for rapid assessment for vessels but its suitability for application to damaged vessels has been questioned, due to the limited failure modes assessed and modelling assumptions required when implementing the method. To reduce the cost and increase the effectiveness of the recovery of a damaged vessel, it will be important to more accurately assess the structure by determining the correct failure mode. This paper presents a study on the use of progressive collapse analysis to model damaged box girders which assesses the structure across multiple frame boundaries. The study shows that while progressive collapse analysis can be applied in the assessment of damaged box girders, implementing the newly proposed assessment allows greater accuracy in the calculation of the collapse strength through capture of the true mode of failure. This new method will allow the effects of the damage on surrounding structure to be captured which can influence the deflection shapes that will lead to collapse of the structure.
346-357
Underwood, James
5747071d-558b-467b-b60a-1389ca47b332
Sobey, Adam
e850606f-aa79-4c99-8682-2cfffda3cd28
Blake, James
6afa420d-0936-4acc-861b-36885406c891
Shenoi, Ajit
a37b4e0a-06f1-425f-966d-71e6fa299960
September 2016
Underwood, James
5747071d-558b-467b-b60a-1389ca47b332
Sobey, Adam
e850606f-aa79-4c99-8682-2cfffda3cd28
Blake, James
6afa420d-0936-4acc-861b-36885406c891
Shenoi, Ajit
a37b4e0a-06f1-425f-966d-71e6fa299960
Underwood, James, Sobey, Adam, Blake, James and Shenoi, Ajit
(2016)
Compartment level progressive collapse strength as a method for analysing damaged steel box girders.
Thin-Walled Structures, 106, .
(doi:10.1016/j.tws.2016.04.007).
Abstract
It is vital to be able to rapidly assess damaged ship structures. This ensures the safety of personnel and facilitation of the most effective repair or recovery. Interframe progressive collapse analysis has been used as a method for rapid assessment for vessels but its suitability for application to damaged vessels has been questioned, due to the limited failure modes assessed and modelling assumptions required when implementing the method. To reduce the cost and increase the effectiveness of the recovery of a damaged vessel, it will be important to more accurately assess the structure by determining the correct failure mode. This paper presents a study on the use of progressive collapse analysis to model damaged box girders which assesses the structure across multiple frame boundaries. The study shows that while progressive collapse analysis can be applied in the assessment of damaged box girders, implementing the newly proposed assessment allows greater accuracy in the calculation of the collapse strength through capture of the true mode of failure. This new method will allow the effects of the damage on surrounding structure to be captured which can influence the deflection shapes that will lead to collapse of the structure.
Text
Compartment Level Progressive Collapse Strength as a method for analysing Damaged Steel Box Girders .pdf
- Accepted Manuscript
More information
Accepted/In Press date: 6 April 2016
e-pub ahead of print date: 26 May 2016
Published date: September 2016
Organisations:
Fluid Structure Interactions Group
Identifiers
Local EPrints ID: 391229
URI: http://eprints.soton.ac.uk/id/eprint/391229
ISSN: 0263-8231
PURE UUID: ce6c7b89-2664-4a98-b583-51d0c4205570
Catalogue record
Date deposited: 08 Apr 2016 11:40
Last modified: 15 Mar 2024 05:28
Export record
Altmetrics
Contributors
Author:
James Underwood
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics