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 ,
Full TextAbstract
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 pattern
@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},
}
%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
