Prediction of the collapse modes of PVC cylindrical shells under compressive axial loads using Artificial Neural Networks

Markopoulos, AP; Manolakos, DE; Vaxevanidis, NM

dc.contributor.author	Markopoulos, AP	en
dc.contributor.author	Manolakos, DE	en
dc.contributor.author	Vaxevanidis, NM	en
dc.date.accessioned	2014-03-01T02:44:55Z
dc.date.available	2014-03-01T02:44:55Z
dc.date.issued	2007	en
dc.identifier.issn	15715736	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32022
dc.subject	Artificial Neural Network	en
dc.subject	Neural Network	en
dc.title	Prediction of the collapse modes of PVC cylindrical shells under compressive axial loads using Artificial Neural Networks	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/978-0-387-74161-1_27	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-0-387-74161-1_27	en
heal.publicationDate	2007	en
heal.abstract	In the present paper Artificial Neural Networks (ANN) are applied in order to predict the buckling modes of thin-walled PVC tubes under compressive axial forces. For the development of the models the neural network toolbox of Matlab® was applied. The results show that these models can satisfactorily face these problems and they constitute not only a fast method, compared to time consuming experiments, but also a reliable tool that can be used for the studying of such parts which are usually employed as structural elements for the absorption of the energy of an impact, in automotive and aerospace applications. © 2007 International Federation for Information Processing.	en
heal.journalName	IFIP International Federation for Information Processing	en
dc.identifier.doi	10.1007/978-0-387-74161-1_27	en
dc.identifier.volume	247	en
dc.identifier.spage	251	en
dc.identifier.epage	258	en