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| Content Provider | Springer Nature Link |
|---|---|
| Author | Fereshteh Saniee, F. Sepahi Boroujeni, A. Sepahi Boroujeni, S. |
| Copyright Year | 2016 |
| Abstract | Severe plastic deformation (SPD) methods have extensive capabilities to improve the mechanical properties of metals. Growing applications of SPD techniques in various industries demand comprehensive optimizations and parametric analyses. Expansion equal channel angular extrusion (Exp-ECAE) is recently proposed as an SPD process. In this research, effects of the geometrical parameters of Exp-ECAE tools on the distribution of effective strain on the product’s cross section are investigated. Then, the die geometry is optimized in order to achieve a product with desirable quality. In this regard, an artificial neural network (ANN), incorporated in a genetic algorithm (GA), is utilized. Required database, created by means of finite element (FE) analyses, is also used for ANN training. FE results are validated by experimental findings. The design of experiments is carried out based on nondimensionalized geometrical parameters. Finally, using two different approaches, the optimum die geometries are proposed for the Exp-ECAE process. |
| Starting Page | 3471 |
| Ending Page | 3482 |
| Page Count | 12 |
| File Format | |
| ISSN | 02683768 |
| Journal | The International Journal of Advanced Manufacturing Technology |
| Volume Number | 86 |
| Issue Number | 9-12 |
| e-ISSN | 14333015 |
| Language | English |
| Publisher | Springer London |
| Publisher Date | 2016-02-15 |
| Publisher Place | London |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Expansion equal channel angular extrusion Severe plastic deformation Homogeneous plastic strain genetic Algorithm Artificial neural network Industrial and Production Engineering Production Mechanical Engineering Computer-Aided Engineering (CAD, CAE) and Design |
| Content Type | Text |
| Resource Type | Article |
| Subject | Industrial and Manufacturing Engineering Control and Systems Engineering Mechanical Engineering Computer Science Applications Software |
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