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dc.contributor.authorXie, Chaoyang
dc.contributor.authorWang, Pingfeng
dc.contributor.authorWei, Fayuan
dc.contributor.authorHuang, Hongzhong
dc.date.accessioned2016-09-16T15:13:07Z
dc.date.available2016-09-16T15:13:07Z
dc.date.issued2015
dc.identifier.citationC. Xie, F. Wei, P. Wang and H. Huang, "Modeling of corrosion pit growth for prognostics and health management," Prognostics and Health Management (PHM), 2015 IEEE Conference on, Austin, TX, 2015, pp. 1-7en_US
dc.identifier.isbn978-1-4799-1894-2
dc.identifier.otherWOS:000380466500012
dc.identifier.urihttp://dx.doi.org/10.1109/ICPHM.2015.7245024
dc.identifier.urihttp://hdl.handle.net/10057/12419
dc.descriptionClick on the DOI link to access the article (may not be free).en_US
dc.description.abstractPitting corrosion is one of the most destructive types of metal degradation and it can result in catastrophic failure of components due to transition of pits to stress corrosion cracks under loading. To facilitate the implementation of corrosion prognostics and health management, in paper presents a finite element approach for the simulation of stable pit growth with stress loads through a multi-physics field coupling technique. A potential drop (IR)-controlled corrosion is assumed to governing the pit evolution, whereas the potential distribution in electrolyte is solved by Laplace equation with a time-dependent solution. As the metal equilibrium potential varies with loads, a time-discrete stationary mechanical analysis was coupled with the corrosion modeling for stress distribution computing and updating. A case study of pitting corrosion growth with stress loads was used to demonstrate the proposed approach, in which the stress effects for pit depth, width and stress concentration factor were discussed.en_US
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.relation.ispartofseries2015 IEEE Conference on Prognostics and Health Management (PHM);
dc.subjectPitting corrosionen_US
dc.subjectGrowth simulationen_US
dc.subjectMultiphysics modelingen_US
dc.subjectStress effectsen_US
dc.titleModeling of corrosion pit growth for prognostics and health managementen_US
dc.typeConference paperen_US
dc.rights.holder© Copyright 2016 IEEE - All rights reserved.en_US


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