Abstract
Plastic constitutive parameters (PCP) of tube are one of key factors for the study of forming qualities in numerical control (NC) tube bending. A new method for parameters identification is presented, which combines the artificial neural network (ANN), the finite element analysis (FEA) and the tension experiment based on planar stress status (PSS). The PCP of aluminum alloy tube (5052O) with size factor (D/t) of 50 are acquired. Meanwhile, based on the ABAQUS software environment, a 3D elastic-plastic FE model for NC bending is established, and the effects of different tube PCP on plastic deformation behaviors (PDB) in tube bending are studied using this model. The results reveal that compared with the traditional axial tension test, the PDB in the bending of tube extrados simulated by FEA with PCP obtained by the presented method are closer to experimental results.
| Original language | English |
|---|---|
| Pages (from-to) | 297-300 |
| Number of pages | 4 |
| Journal | Cailiao Kexue yu Gongyi/Material Science and Technology |
| Volume | 17 |
| Issue number | 3 |
| State | Published - Jun 2009 |
Keywords
- Artificial neural network
- Finite element analysis
- NC tube bending
- Parameters identification