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Neural crack identification in steady state elastodynamics

Stavroulakis Georgios, Antes, Horst, 1936-

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URIhttp://purl.tuc.gr/dl/dias/2F9C95EE-527C-4D31-B2AD-853E53B79F2F-
Identifierhttps://doi.org/10.1016/S0045-7825(98)00035-8-
Languageen-
Extent17 pagesen
TitleNeural crack identification in steady state elastodynamicsen
CreatorStavroulakis Georgiosen
CreatorΣταυρουλακης Γεωργιοςel
CreatorAntes, Horst, 1936-en
PublisherElsevieren
Content SummaryAn inverse crack identification problem with harmonic excitation in linear elastodynamics is treated here by means of back-propagation neural network methods and boundary element techniques. The problem concerns the determination of the existence and the characteristics of a hidden crack within an elastic structure by means of measurements of the structural response on the accessible boundary for given external time-periodic loadings. The direct problem is solved by a boundary element formulation in the frequency domain which leads to a system of linear equations with frequency-dependent matrices. Thus, for a given frequency, certain similarities with linear elastostatics exist. Feed-forward multilayer neural networks trained by back-propagation are used to learn the (inverse) input-output relation of the structural system. Then, the inverse problem is solved by a simple application of the neural network recalling (production) ability. en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-10-11-
Date of Publication1998-
SubjectEngineeringen
Bibliographic CitationG.E. Stavroulakis, H. Antes ," Neural crack identification in steady state elastodynamics," Com. Methods in Ap. Mechanics and Eng. vol. 165, no. 1–4, pp.129–146, November 1998. doi: h10.1016/S0045-7825(98)00035-8 en

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