Application of Neural Network and FEM to Optimize Load Path of T-shape Tube Hydro Forming
عنوان مقاله: Application of Neural Network and FEM to Optimize Load Path of T-shape Tube Hydro Forming
شناسه ملی مقاله: ICME08_028
منتشر شده در دومین کنفرانس بین المللی و هشتمین کنفرانس ملی مهندسی ساخت و تولید در سال 1386
شناسه ملی مقاله: ICME08_028
منتشر شده در دومین کنفرانس بین المللی و هشتمین کنفرانس ملی مهندسی ساخت و تولید در سال 1386
مشخصات نویسندگان مقاله:
A Jaamialahmadi - Lecturer Department of Mechanical Engineering Ferdowsi University of Mashhad,
M Kadkhodayan - Associated Professor Department of Mechanical Engineering Ferdowsi University of Mashhad,
E Masumi - BSc Department of Mechanical Engineering Ferdowsi University of Mashhad,
خلاصه مقاله:
A Jaamialahmadi - Lecturer Department of Mechanical Engineering Ferdowsi University of Mashhad,
M Kadkhodayan - Associated Professor Department of Mechanical Engineering Ferdowsi University of Mashhad,
E Masumi - BSc Department of Mechanical Engineering Ferdowsi University of Mashhad,
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 properties of final product is difficult and a 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 properties of T- shapebranch workpiece. 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.
کلمات کلیدی: Tube hydroforming, Bursting failure, Load path, Neural Network, Direct search pattern
صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/81413/