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.‎

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