Rapid vulnerability assessment of naval structures subjected to localised blast

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dc.contributor.authorBortolan Neto, Len_AU
dc.contributor.authorSaleh, Men_AU
dc.contributor.authorPickerd, Ven_AU
dc.contributor.authorYiannakopoulos, Gen_AU
dc.contributor.authorMathys, Zen_AU
dc.contributor.authorReid, Wen_AU
dc.date.accessioned2023-05-05T00:35:42Zen_AU
dc.date.available2023-05-05T00:35:42Zen_AU
dc.date.issued2017-10-04en_AU
dc.date.statistics2023-05-04en_AU
dc.description.abstractThe development of modern naval vessels is driven by the optimum balance between operational performance, technology restrictions and the costs of ownership. These factors impose limitations on all features of surface ships, including weaponry, structural materials, radar systems, and propulsors. Strategies must be set to identify design features and materials that can enhance the vessels protection in the event of shock loadings e.g. air blast and underwater explosions. Assessment of design solutions is a complicated task due to the large number of unknowns involved. Appropriate computational models and experimental tests can give insights into the expected mechanical behaviour to support the design process. The authors are developing a framework for vulnerability assessment, which includes experimental tests and appropriate finite element (FE) models of representative structural parts subjected to blast loading. This combined approach provides a comprehensive analysis tool but its complexity prevents the quick assessment of the vessel structural vulnerability when various design features and a range of materials are to be considered. To overcome this hurdle, a machine learning model based on Artificial Neural Networks is proposed to identify patterns in numerical and experimental data, yielding timely conclusions about the structural response. © 2017 The Royal Institution of Naval Architectsen_AU
dc.identifier.booktitleProceedings of the International Maritime Conference (Pacific 2017), Sydney, Australia, 3-5 October 2017en_AU
dc.identifier.citationBortolan Neto, L., Saleh, M., Pickerd, V., Yiannakopoulos, G., Mathys, Z., & Reid, W. (2017). Rapid vulnerability assessment of naval structures subjected to localised blast. Paper presented to the International Maritime Conference (Pacific 2017), Sydney, Australia, 3-5 October 2017. In Proceedings of the International Maritime Conference (Pacific 2017), Sydney, Australia, 3-5 October 2017. Red Hook, New York: Curran Associates, Inc. Retrieved from: https://www.proceedings.com/content/048/048126webtoc.pdfen_AU
dc.identifier.conferenceenddate5 October 2017en_AU
dc.identifier.conferencenameInternational Maritime Conference (Pacific 2017)en_AU
dc.identifier.conferenceplaceSydney, Australiaen_AU
dc.identifier.conferencestartdate3 October 2017en_AU
dc.identifier.isbn9781510883055en_AU
dc.identifier.placeofpublicationRed Hook, New Yorken_AU
dc.identifier.urihttps://www.proceedings.com/content/048/048126webtoc.pdfen_AU
dc.identifier.urihttps://apo.ansto.gov.au/dspace/handle/10238/14999en_AU
dc.language.isoenen_AU
dc.publisherCurran Associatesen_AU
dc.subjectVulnerabilityen_AU
dc.subjectMaritime transporten_AU
dc.subjectExplosionsen_AU
dc.subjectMilitary equipmenten_AU
dc.subjectNeural networksen_AU
dc.subjectFinite element methoden_AU
dc.subjectStrain rateen_AU
dc.subjectSimulationen_AU
dc.titleRapid vulnerability assessment of naval structures subjected to localised blasten_AU
dc.typeConference Paperen_AU
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