Details
| Originalsprache | Englisch |
|---|---|
| Aufsatznummer | 132494 |
| Fachzeitschrift | Surface and Coatings Technology |
| Jahrgang | 513 |
| Frühes Online-Datum | 17 Juli 2025 |
| Publikationsstatus | Veröffentlicht - 1 Okt. 2025 |
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.
ASJC Scopus Sachgebiete
- Chemie (insg.)
- Allgemeine Chemie
- Physik und Astronomie (insg.)
- Physik der kondensierten Materie
- Physik und Astronomie (insg.)
- Oberflächen und Grenzflächen
- Werkstoffwissenschaften (insg.)
- Oberflächen, Beschichtungen und Folien
- Werkstoffwissenschaften (insg.)
- Werkstoffchemie
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in: Surface and Coatings Technology, Jahrgang 513, 132494, 01.10.2025.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Life prediction of thermal barrier coatings on turbine blades based on a multiscale approach
AU - Ma, Juan
AU - Zhang, Fuqiang
AU - Li, Qingya
AU - Lai, Shengxin
AU - Zhang, Huawang
AU - Wang, Kangfan
AU - Wriggers, Peter
N1 - Publisher Copyright: © 2025 Elsevier B.V.
PY - 2025/10/1
Y1 - 2025/10/1
N2 - 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.
AB - 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.
KW - Lifetime prediction
KW - Multiphysics coupling analysis
KW - Multiscale
KW - Turbine blade
UR - http://www.scopus.com/inward/record.url?scp=105011291657&partnerID=8YFLogxK
U2 - 10.1016/j.surfcoat.2025.132494
DO - 10.1016/j.surfcoat.2025.132494
M3 - Article
AN - SCOPUS:105011291657
VL - 513
JO - Surface and Coatings Technology
JF - Surface and Coatings Technology
SN - 0257-8972
M1 - 132494
ER -