Simulation Analysis on Martempering in Salt Bath Technology for Carburized Distortion Sample.
Saved in:
| Title: | Simulation Analysis on Martempering in Salt Bath Technology for Carburized Distortion Sample. |
|---|---|
| Authors: | Wang, Xin1,2 (AUTHOR) haiyang630@163.com, Li, Baokui1 (AUTHOR), Gu, Min1 (AUTHOR) |
| Source: | Metallurgical & Materials Transactions. Part A. Aug2019, Vol. 50 Issue 8, p3758-3766. 9p. 7 Diagrams, 5 Charts, 9 Graphs. |
| Subjects: | Salt analysis, Heat transfer coefficient, Martensitic transformations, Thermal stresses, Baths, Heat transfer |
| Abstract: | An analysis model of the martempering in salt bath technology (MISBT) is established, which incorporates temperature field, phase transformation kinetics, and a strain field. The heat transfer coefficient is estimated by the inverse heat transfer method for the calculation of temperature. The effect of carbon content on the martensite transformation is then determined. On the strain calculation, the interaction between the thermal and the phase transformation strain is considered. Then the model is applied to the C-shaped carburized distortion sample for the 17CrNiMo6 steel by DEFORM. The temperature and martensitic transformation results of the MISBT are quantitatively analyzed and calculated. In contrast to the oil-quenching process (OQP), the smaller thermal stress of the MISBT is a result of the smaller temperature difference between the surface and the core. The lower transformation stress of the MISBT is a result of the slow cooling rate below 400 °C and the martensitic grade transformation. Therefore, the stress and distortion of the MISBT is less than that of the OQP, and the distortion results are consistent with the experimental results. [ABSTRACT FROM AUTHOR] |
| Copyright of Metallurgical & Materials Transactions. Part A is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
Be the first to leave a comment!
