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REVIEW

Review of Numerical Simulation of TGO Growth in Thermal Barrier Coatings

Quan Wen1, Fulei Jing1,*, Changxian Zhang1, Shibai Tang1, Junjie Yang2,*

1 Aero Engine Academy of China, Aero Engine (Group) Corporation of China, Beijing, 101304, China
2 Institute for Aero Engine, Tsinghua University, Beijing, 100084, China

* Corresponding Authors: Fulei Jing. Email: email; Junjie Yang. Email: email

(This article belongs to the Special Issue: Recent Trends in Thermal Barrier Coatings for Turbine Blades: Theory, Simulation, and Experiment)

Computer Modeling in Engineering & Sciences 2022, 132(2), 361-391. https://doi.org/10.32604/cmes.2022.019528

Abstract

Thermally grown oxide (TGO) is a critical factor for the service life of thermal barrier coatings (TBC). Numerical simulations of the growth process of TGO have become an effective means of comprehensively understanding the progressive damage of the TBC system. At present, technologies of numerical simulation to TGO growth include two categories: coupled chemical-mechanical methods and mechanical equivalent methods. The former is based on the diffusion analysis of oxidizing elements, which can describe the influence of bond coat (BC) consumption and phase transformation in the growth process of TGO on the mechanical behavior of each layer of TBC, and has high accuracy for the thickness evolution of TGO, but they cannot describe the lateral growth of TGO and the rumpling phenomenon induced. The latter focuses on describing the final stress and strain state after the growth of a specific TGO rather than the complete growth processes of TGO. Based on the measured TGO thickness growth curve, simulations of thickening and lateral growth can be achieved by directly applying anisotropic volumetric strain to oxidized elements and switching elements properties from the BC to the TGO.

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Cite This Article

Wen, Q., Jing, F., Zhang, C., Tang, S., Yang, J. (2022). Review of Numerical Simulation of TGO Growth in Thermal Barrier Coatings. CMES-Computer Modeling in Engineering & Sciences, 132(2), 361–391. https://doi.org/10.32604/cmes.2022.019528



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