Stochastic Model for High Temperature Oxidation of Cr-Ni Austenitic Steels Assisted by Spallation
Abstract
Cr-Ni austenitic steels offer significant high temperature corrosion protection by forming a surface oxide layer. However, above critical service conditions (temperature, atmosphere, thermal cycling), oxidized surface can experience intensive degradation because of scale spallation, which could be detrimental to the in-service life. To predict the effect of scale spallation on oxidation kinetics, a simulation was implemented using a stochastic model. The model considers topological parameters and intensity of spallation which can occur, while delivering a true oxidation constant. The experimental procedure identified the amount of formed spalled scale and topology of spallation based on the use of element mapping of the surface. This information was used to determine a true kinetic constant for a corresponding spallation intensity in oxidized Cr-Ni austenitic steel. To illustrate the capability of the stochastic model, a parametric analysis was performed. The model verified how the spallation parameters could change the oxidation processes from parabolic growth of an adhered oxide layer without spallation to a mixed linear-parabolic, or with a constant thickness of residual scale at high spallation intensity. The spallation model will be used in a separate article to characterize high temperature surface degradation of several Cr-Ni austenitic steels during harsh oxidation environments.
Recommended Citation
S. N. Lekakh et al., "Stochastic Model for High Temperature Oxidation of Cr-Ni Austenitic Steels Assisted by Spallation," Oxidation of Metals, Springer Verlag, Jan 2022.
The definitive version is available at https://doi.org/10.1007/s11085-022-10120-8
Department(s)
Materials Science and Engineering
Keywords and Phrases
Austenitic Steel; Oxidation Kinetics; Spallation
International Standard Serial Number (ISSN)
1573-4889; 0030-770X
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2022 Springer, All rights reserved.
Publication Date
01 Jan 2022
Comments
This research was supported by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) under the Award Number DE-EE0008458.