Institutional Repository [SANDBOX]
Technical University of Crete
EN  |  EL

Search

Browse

My Space

A genetically optimized neural classifier applied to numerical pile integrity tests considering concrete piles

Protopapadakis Eftychios, Schauer Marco, Pierri Erika, Doulamis Anastasios, Stavroulakis Georgios, Böhrnsen, Jens Uwe, Langer Sabine Christine

Simple record


URIhttp://purl.tuc.gr/dl/dias/E3804C1D-C1A2-4245-ABBC-D6EC1FC0900B-
Identifierhttps://www.sciencedirect.com/science/article/pii/S0045794915002321?via%3Dihub-
Identifierhttps://doi.org/10.1016/j.compstruc.2015.08.005-
Languageen-
Extent12 pagesen
TitleA genetically optimized neural classifier applied to numerical pile integrity tests considering concrete pilesen
CreatorProtopapadakis Eftychiosen
CreatorΠρωτοπαπαδακης Ευτυχιοςel
CreatorSchauer Marcoen
CreatorPierri Erikaen
CreatorDoulamis Anastasiosen
CreatorΔουλαμης Αναστασιοςel
CreatorStavroulakis Georgiosen
CreatorΣταυρουλακης Γεωργιοςel
CreatorBöhrnsen, Jens Uween
CreatorLanger Sabine Christineen
PublisherElsevieren
Content SummaryA genetically optimized neural detector is utilized for the identification of structural defects in concrete piles. The proposed methodology is applied on numerically generated data, involving two major defect types. A coupled finite element and scaled boundary finite element method approach is used to model the pile and its surrounding soil. The oscillation patterns, produced on the surface of the pile, depend strongly on the introduced defect type. The proposed defect detection system provides information about the type and the placement of the defect(s), given the surface's oscillation patterns.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2018-11-16-
Date of Publication2016-
SubjectImpact-echoen
SubjectIsland genetic algorithmen
SubjectLow strain methoden
SubjectNeural networks optimizationen
SubjectPile integrity testen
SubjectScaled boundary finite element methoden
Bibliographic CitationE. Protopapadakis, M. Schauer, E. Pierri, A. D. Doulamis, G. E. Stavroulakis, J.-U. Böhrnsen and S. Langer, "A genetically optimized neural classifier applied to numerical pile integrity tests considering concrete piles," Comput. Struct., vol. 162, pp. 68-79, Jan. 2016. doi: 10.1016/j.compstruc.2015.08.005en

Services

Statistics