南京航空航天大学学报（英文版）2025，Vol.42Issue(6)：813-829,17.DOI:10.16356/j.1005-1120.2025.06.008
基于MLP神经网络的热障涂层局部剥离对叶片冷效影响的快速预估
Rapid Prediction of Effect of Localized Spallation of Thermal Barrier Coatings on Blade Cooling Efficiency Based on an MLP Neural Network
摘要
Abstract
The study of the spallation of thermal barrier coatings on turbine blades and its influence is of great significance for gas turbine safety operation.However,numerical simulation related to thermal barrier coatings is difficult and time-costly,which makes it hard to meet engineering demands.Therefore,this work establishes a rapid prediction model for the surface temperature and cooling efficiency of turbine blades with localized spallation of thermal barrier coatings based on a thin-wall thermal resistance model.Firstly,the influence of localized spallation of thermal barrier coatings on the cooling efficiency of typical turbine blades is numerically investigated.Then,based on the simulation data set and multi-layer perception(MLP)neural network,an intelligent prediction model for the temperature and cooling efficiency distribution of localized spallation of coatings is constructed,which can rapidly predict the surface temperature and cooling efficiency of the blade under the situation of spallation of coating at any position on the blade surface.The results show that,under a certain spallation area,the shape of localized coating spallation has little influence on the cooling efficiency,while the increase of spallation thickness will cause a linear increase in the average temperature of the blade surface.The prediction error of the proposed rapid prediction model for the average surface temperature and cooling efficiency of blades is within 2%,and the prediction error of the temperature and cooling efficiency at the spallation position is within 6%for 80%of the samples,with an overall average error within 10%.It is concluded from the rapid prediction model that when the depth of coating spallation increases,the closer the spallation position is to the leading edge of the blade,the greater the difference in cooling efficiency is,and the degree of influence of coating spallation on the cooling efficiency also increases.关键词
热障涂层/冷却性能/快速预测/MLP神经网络Key words
thermal barrier coating(TBC)/cooling performance/rapid prediction/multi-layer perception(MLP)neural network分类
航空航天引用本文复制引用
张烨苓,王飞龙,王于群,王玉彬,毛军逵..基于MLP神经网络的热障涂层局部剥离对叶片冷效影响的快速预估[J].南京航空航天大学学报（英文版）,2025,42(6):813-829,17.基金项目
This work was supported by the Na-tional Natural Science Foundation of China(No.52206090),the Jiangsu Provincial Natural Science Foundation(No.BK20220901),the National Major Science and Technology Projects of China(No.Y2022-Ⅲ-0004-0013),Engineering Research Center of Low-Carbon Aerospace Power Ministry of Education(No.CEPE2024020),and the China Postdoc-toral Science Foundation(No.2022TQ0149). （No.52206090）
