3922

3700

كارشناسي ارشد

طراحي كاربردي

اصفهان: دانشگاه صنعتي اصفهان، دانشكده مكانيك

1386

هشت، 106، [II] ص. : مصور، نمودار، جدول

ص. ع. به فارسي و انگليسي

حسن خادمي زاده، حسن موسوي

محمود فرزين

06/03/87

محمد رضا فروزان، محسن اصفهانيان

1396/03/03

كتابنامه

مكانيك

مهندسي مكانيك

ID3700

به فارسي و انگليسي: قابل رويت در نسخه ديجيتال

Iut 77142Degree master of scienceTitle Hydroforming of Y shape process study using FEA simulation optimization ofprocess using neural network genetic algorithm compare with experimental resultsAuther amir rahimiSupervisor H Khademi Zadeh Associated prof H Moosavi Associated ProfDepartment mechanical engineeringDate 2008 3 16Language PersianAbstractHydroforming process is one of the newest metal forming methods that isgradually converted to the one of the most important forming methods Comparedto stamping tube hydroforming offers higher part quality tighter tolerances increased rigidity with lower manufacturing costs reduced number of formingand assembly operations In this study the estimation of the process parametersfor hydroforming Y shapes i e pressure levels axial feeds initial tube length friction effect mesh size effect and corner radius of protrusion effect onhydroformability of tube are discussed using ABAQUS 6 6 1 in simulation ofprocess effect of counter punch is applied show that using of counter punch canprevent failures during process extremely Then these estimated parameters are verified with hydroforming experiments Finally some of These estimated parameters are then optimized using FEAsimulations neural network genetic algorithms Y shape hydroforming loading paths axial feeding counter punch Keywords neural network genetic algorithm

حسن خادمي زاده، حسن موسوي

محمود فرزين

محمد رضا فروزان، محسن اصفهانيان