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Neural network assisted crack and flaw identification in transient dynamics

Stavroulakis Georgios, Engelhardt, Markus, 1956-, Gallegos, Rómulo, 1884-1969, Likas, A, antes horst

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URIhttp://purl.tuc.gr/dl/dias/FD344BBC-B9D0-4780-8C62-8F2FB557F201-
Languageen-
Extent20 pagesen
TitleNeural network assisted crack and flaw identification in transient dynamicsen
CreatorStavroulakis Georgiosen
CreatorΣταυρουλακης Γεωργιοςel
CreatorEngelhardt, Markus, 1956-en
CreatorGallegos, Rómulo, 1884-1969en
CreatorLikas, Aen
Creatorantes horsten
Content SummaryCrack and flaw identification problems in two-dimensional elastomechanics are numerically studied in this paper. The mechanical modelling is based on boundary element techiques, with special care of hypersingular issues for the cracks. The possibility of partially or totally closed cracks (unilateral contact effects) is taken into account by linear complementarity techniques. Backpropagation neural networks are used for the solution of the inverse problems. For dynamical problems, a suitable preprocessing of the input data enhances the effectiveness of the procedure. For the two-dimensional examples presented here, the proposed method has similar performance for classical crack and flaw identification problems. The identification of unilateral cracks is a considerably more difficult task, which nevertheless, can also be solved by the same method, provided that a suitable dynamical test loading is applied.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-10-12-
Date of Publication2004-
SubjectApplied mechanicsen
SubjectEngineering, Mechanicalen
Subjectmechanics applieden
Subjectapplied mechanicsen
Subjectengineering mechanicalen
Bibliographic CitationG.E. Stavroulakis, M. Engelhardt, A. Likas, R. Gallego, H. Antes ,"Neural network assisted crack and flaw identification in transient dynamics ," J. of Theor. and Ap. Mech.,vol. 42, no.3 pp.629-649.2004.en

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