Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI | http://purl.tuc.gr/dl/dias/2F9C95EE-527C-4D31-B2AD-853E53B79F2F | - |
| Identifier | https://doi.org/10.1016/S0045-7825(98)00035-8 | - |
| Language | en | - |
| Extent | 17 pages | en |
| Title | Neural crack identification in steady state elastodynamics | en |
| Creator | Stavroulakis Georgios | en |
| Creator | Σταυρουλακης Γεωργιος | el |
| Creator | Antes, Horst, 1936- | en |
| Publisher | Elsevier | en |
| Content Summary | An 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 Item | Peer-Reviewed Journal Publication | en |
| Type of Item | Δημοσίευση σε Περιοδικό με Κριτές | el |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2015-10-11 | - |
| Date of Publication | 1998 | - |
| Subject | Engineering | en |
| Bibliographic Citation | G.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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