| About this Abstract |
| Meeting |
13th International Conference on the Technology of Plasticity (ICTP 2020)
|
| Symposium
|
13th International Conference on the Technology of Plasticity (ICTP 2020)
|
| Presentation Title |
Study on Back-propagation Artificial Neural Network Model of TC4 Titanium Alloy |
| Author(s) |
Hongchao Ji, Yiming Li, Yaogang Li |
| On-Site Speaker (Planned) |
Hongchao Ji |
| Abstract Scope |
Using the Gleeble-1500D thermal simulation machine, and taking the flow stress as the objective function, the TC4 titanium alloy was subjected to isothermal compression test under the conditions of deformation temperature of 1023-1323K, strain rate of 0.01-10s-1 and maximum deformation degree of 60% (the true strain is 0.916), and the stress and strain data under different deformation conditions were obtained. Based on the stress and strain data, the Back-Propagation Artificial Neural Network (BP-ANN) model was obtained by using MATLAB software. The accuracy of the BP-ANN model was evaluated by correlation coefficient (R) and average absolute relative error (AARE). The results can provide important basic data for the simulation of TC4 titanium alloy plastic deformation process. |
| Proceedings Inclusion? |
Definite: At-meeting proceedings |