دومین کنفرانس بین المللی ساخت و تولید (TICME 2007) , 2007-12-10

Title : ( Application of Neural Network and FEM to optimize ‎load path of T-shape tube hydroforming )

Authors: Abdolrahman Jaamialahmadi , Mehran Kadkhodayan , ehsan masoumi khalil Abad ,

Citation: BibTeX | EndNote

Abstract During tube hydroforming (THF) process, failure modes such as buckling, necking ‎and bursting may occur because axial feeding and internal pressure are imposed ‎simultaneously. As load path has great influence on THF, prediction of required ‎specificationsproperties of final product is difficult and time consuming work. In this ‎study, Neural Network algorithm and ANSYS LS-DYNA and ANSYS Program ‎Language Design (APDL), was used to predict final product specifications properties ‎such as bulging height and thinning (thickness reduction) of T- shape branch ‎workpiece by using stress based FLD. FE model and Neural Network were verified ‎using experimental result for a determined load path. Finally direct search method ‎has been used to obtain optimum load path for higher formability.‎

Keywords

, Keywords: Tube hydroforming, Bursting failure, Load path, Neural Network, Direct ‎search
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@inproceedings{paperid:1016210,
author = {Jaamialahmadi, Abdolrahman and Kadkhodayan, Mehran and Masoumi Khalil Abad, Ehsan},
title = {Application of Neural Network and FEM to optimize ‎load path of T-shape tube hydroforming},
booktitle = {دومین کنفرانس بین المللی ساخت و تولید (TICME 2007)},
year = {2007},
location = {IRAN},
keywords = {Keywords: Tube hydroforming; Bursting failure; Load path; Neural Network; Direct ‎search pattern},
}

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%0 Conference Proceedings
%T Application of Neural Network and FEM to optimize ‎load path of T-shape tube hydroforming
%A Jaamialahmadi, Abdolrahman
%A Kadkhodayan, Mehran
%A Masoumi Khalil Abad, Ehsan
%J دومین کنفرانس بین المللی ساخت و تولید (TICME 2007)
%D 2007

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