Simulation and Optimization of U-Bending Springback Using Genetic Algorithms

Lei Chen

doi:10.4028/www.scientific.net/AMM.69.17

Paper Titles

Preface and Committee

Finite Element Analysis of Bending Resistance for RC Beams Strengthened with AFRP Sheets
p.1

Structure Information of Barium Hexaferrite and Strategies for its Syntheses
p.6

Platelet Adhesion on Silicon Modified Carbon Nanotubes Films
p.12

Simulation and Optimization of U-Bending Springback Using Genetic Algorithms
p.17

Load and Deformation Properties of Steel Fiber Reinforced Concrete ShearWall
p.23

Study on Control of Hydraulic Disc Brake System Based on PWM High Speed On/Off Valve
p.28

Study on Statistical Damage Softening Constitutive Model and Determination of Parameters for Rock Based on Lognormal Distribution
p.33

Strain Fatigue Behavior of Thin-Walled Tubes of Zr-1Nb and Zr-4 and Thin Plates of N18 at Elevated Temperatures
p.39

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 69Simulation and Optimization of U-Bending...

Simulation and Optimization of U-Bending Springback Using Genetic Algorithms

Abstract:

Springback during unloading affects the dimensional accuracy of sheet metal parts. This paper proposes a finite element model to predict springback with contact evolution between the sheet and dies. The underlying formulation is based on updated Lagrangian elastoplastic materials model. The solutions validated with experimental data of NUMISHEET’93 show more accurately. The effects of the variable blank holding force (VBHF) on springback results are investigated based on genetic algorithms (GAs) for the determination of the parameters in blank holding operations. It has been found that the GAs based optimization technique is very effective in solving this kind of problem. The difficulty of choosing correct starting values for the constants in the traditional optimization techniques has been completely overcome and the GAs technique provides a better chance to converge to the global minimum.