Life prediction of thermal barrier coatings on turbine blades based on a multiscale approach

authored by: Juan Ma, Fuqiang Zhang, Qingya Li, Shengxin Lai, Huawang Zhang, Kangfan Wang, Peter Wriggers
Abstract: The life prediction of thermal barrier coatings for turbine blades encounters many obstacles as a result of the intricate microstructure and the demanding diverse service conditions. This work examines the behavioral traits of turbine blades at micro- and macroscale using the concept of multiscale modeling. Subsequently, a life prediction model for thermal barrier coatings is proposed with the aid of an artificial neural network-based surrogate model. The model considers the impact of oxidation, creep, and thermal mismatch on the thermal barrier coating, as well as the collective influence of cooling conditions on the thermal barrier coatings of macroscopic blades. In comparison to the conventional finite element computation, the model exhibits superior predictive accuracy in assessing the interfacial oxidation and degradation of the thermal barrier coating on the turbine blade, particularly when considering the effects of the coupling field.
Organisation(s): Institute of Continuum Mechanics
External Organisation(s): Xidian University
Type: Article
Journal: Surface and Coatings Technology
Volume: 513
ISSN: 0257-8972
Publication date: 01.10.2025
Publication status: Published
Peer reviewed: Yes
ASJC Scopus subject areas: General Chemistry, Condensed Matter Physics, Surfaces and Interfaces, Surfaces, Coatings and Films, Materials Chemistry
Electronic version(s): https://doi.org/10.1016/j.surfcoat.2025.132494 (Access: Closed)
: Details in the research portal "Research@Leibniz University"

BibTeX

@article{ae319ecc24cf45a38bb0996a0a192592,
title = "Life prediction of thermal barrier coatings on turbine blades based on a multiscale approach",
abstract = "The life prediction of thermal barrier coatings for turbine blades encounters many obstacles as a result of the intricate microstructure and the demanding diverse service conditions. This work examines the behavioral traits of turbine blades at micro- and macroscale using the concept of multiscale modeling. Subsequently, a life prediction model for thermal barrier coatings is proposed with the aid of an artificial neural network-based surrogate model. The model considers the impact of oxidation, creep, and thermal mismatch on the thermal barrier coating, as well as the collective influence of cooling conditions on the thermal barrier coatings of macroscopic blades. In comparison to the conventional finite element computation, the model exhibits superior predictive accuracy in assessing the interfacial oxidation and degradation of the thermal barrier coating on the turbine blade, particularly when considering the effects of the coupling field.",
keywords = "Lifetime prediction, Multiphysics coupling analysis, Multiscale, Turbine blade",
author = "Juan Ma and Fuqiang Zhang and Qingya Li and Shengxin Lai and Huawang Zhang and Kangfan Wang and Peter Wriggers",
note = "Publisher Copyright: {\textcopyright} 2025 Elsevier B.V.",
year = "2025",
month = oct,
day = "1",
doi = "10.1016/j.surfcoat.2025.132494",
language = "English",
volume = "513",
journal = "Surface and Coatings Technology",
issn = "0257-8972",
publisher = "Elsevier BV",
}