Gas nitriding is an important thermochemical surface treatment that is used to improve the wear and corrosion resistance as well as the fatigue endurance of steel parts. Accurate process control is the effective way to ensure the properties reliability of nitriding process. To realize the accurate process control, the nitriding process parameters need to be modeled and controlled to meet the specifications. There has been ongoing effort on the simulation of the gas nitriding process since 1990s. However, most of the work has been done to simulate the gas nitriding process of pure iron due to the limited thermodynamics and kinetics information available on the gas nitriding process of steels. The objective of this project is to develop an accurate and user friendly software model to simulate the gas nitriding process of steels based on the fundamental understanding of thermodynamics and kinetics. In this work, the customized Lehrer diagram which describes the phase stabilities in specified steel as a function of nitriding potential and temperature has been successfully constructed by computational thermodynamics for the first time. Based on the Lehrer diagrams for steels, the compound layer growth model is proposed to simulate the gas nitriding process of steels. By using this model, the properties of the nitrided steels based on the phase constitution, surface nitrogen concentration, nitrogen concentration profile, case depth, as well as growth kinetics can be simulated as a function of the process parameters (temperature, time, and the nitriding atmosphere). The results of the model are in excellent agreement with experimental results.
| Identifer | oai:union.ndltd.org:wpi.edu/oai:digitalcommons.wpi.edu:etd-dissertations-1126 |
| Date | 19 April 2012 |
| Creators | Yang, Mei |
| Contributors | Richard D. Sisson, Jr., Advisor, , |
| Publisher | Digital WPI |
| Source Sets | Worcester Polytechnic Institute |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Doctoral Dissertations (All Dissertations, All Years) |
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