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| Content Provider | Springer Nature Link |
|---|---|
| Author | Luo, Yi Wu, Xiao chun |
| Copyright Year | 2012 |
| Abstract | The suggested model for designing nonquenched prehardened steels for large molds for plastics combines simulation of temperature fields and computation of hardness on the basis of an artificial neural network (ANN). The temperature field is simulated for round steel preforms from 400 to 700 mm in diameter and up to 10 tons in mass. The ANN is introduced into the design model for analyzing and simulating the relation between the chemical composition and the hardness of alloyed steels cooled at a rate of 0.5, 0.3, 0.05, and 0.03 K/sec. The suggested model is used to develop two chemical compositions for preforms from prehardened steels for casting plastics. The preforms have been tested in production of commercial articles. |
| Starting Page | 360 |
| Ending Page | 367 |
| Page Count | 8 |
| File Format | |
| ISSN | 00260673 |
| Journal | Metal Science and Heat Treatment |
| Volume Number | 54 |
| Issue Number | 7-8 |
| e-ISSN | 15738973 |
| Language | English |
| Publisher | Springer US |
| Publisher Date | 2012-11-22 |
| Publisher Place | Boston |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | prehardened steel for large molds for casting plastics nonquenched steels simulation of temperature fields artificial neural network design of chemical composition Metallic Materials Characterization and Evaluation of Materials Mechanics Materials Science Engineering Thermodynamics, Heat and Mass Transfer |
| Content Type | Text |
| Resource Type | Article |
| Subject | Mechanics of Materials Metals and Alloys Condensed Matter Physics |
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