引用本文:姚玉东,艾延廷,关鹏,田晶,包天南.基于遗传算法的热障涂层寿命微观影响因素*[J].中国表面工程,2022,35(1):207~219
YAO Yudong,AI Yanting,GUAN Peng,TIAN Jing,BAO Tiannan.Microscopic Factors Influencing the Lifetime of Thermal Barrier Coatings Based on Genetic Algorithms[J].China Surface Engineering,2022,35(1):207~219
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基于遗传算法的热障涂层寿命微观影响因素*
姚玉东1, 艾延廷1, 关鹏1, 田晶1, 包天南2
1.沈阳航空航天大学辽宁省航空推进系统先进测试技术重点实验室 沈阳 100136;2.西北工业大学动力与能源学院 西安 710109 0
摘要:
热障涂层寿命受到界面波长和幅值等微观因素的影响，但对其影响机制并不清楚。首先，基于 Manson-Coffin 公式和累计损伤理论，建立热障涂层寿命预测模型，并将拟合问题转化为优化问题，采用遗传算法求解寿命模型中的系数。然后， 基于涂层试验数据建立热障涂层二维轴对称有限元模型，研究并确定可用于准确预测涂层寿命的应力应变信息类型。最后， 采用响应面法选取陶瓷层厚度、黏结层厚度、界面波长和幅值作为影响因素，开展涂层寿命的微观影响因素研究。结果表明， 使用循环等效应变范围进行涂层寿命预测的最大误差和平均误差最小，分别为 50%和 21%；涂层寿命随陶瓷层厚度的增加略微上升，随黏结层厚度的增加先下降后上升，随界面波长的增加先上升后下降，随界面幅值的增加而下降，且界面幅值对涂层寿命的影响最大；最优组合的涂层寿命为 947 次循环，与初始值相比提高了 163.1%。给出不同涂层厚度下使涂层寿命达到极值的波长与幅值选择公式，研究成果可为热障涂层的寿命预测和结构优化设计提供方法与理论指导。
关键词:  热障涂层  寿命预测  遗传算法  响应面  界面波长  界面幅值
DOI：10.11933/j.issn.1007-9289.20210803001
分类号:TG147
基金项目:国家自然科学基金(11702177)；辽宁省自然科学基金(2020-BS-174)；辽宁省教育厅(JYT2020019)资助项目
Microscopic Factors Influencing the Lifetime of Thermal Barrier Coatings Based on Genetic Algorithms
YAO Yudong1, AI Yanting1, GUAN Peng1, TIAN Jing1, BAO Tiannan2
1.Liaoning Key Laboratory of Advanced Measurement and Test Technology for Aircraft Propulsion System,Shenyang Aerospace University, Shenyang 110136 , China;2.School of Power and Energy, Northwestern Polytechnical University, Xi’an 710072 , China
Abstract:
The life of thermal barrier coatings (TBC) is affected by micro factors such as interface wavelength and amplitude, but its influencing mechanism is not clear. Therefore, a TBC life prediction model based on Manson-Coffin formula and cumulative damage theory is established. The fitting problem is transformed into an optimization problem, and the coefficient in the life model is solved by genetic algorithm. Then, a 2D axisymmetric finite element model of the TBC is established based on the experimental data of the coatings. Finally, response surface method is used to study the micro-influencing factors of coating life, and the influencing factors are ceramic layer thickness, bonding layer thickness, interface wavelength and amplitude, respectively. The results show that the maximum error and average error of coating life prediction using cyclic equivalent strain range are 50% and 21%, respectively. The coating life increases slightly with the increase of ceramic layer thickness, decreases first and then increases with the increase of bonding layer thickness, increases first and then decreases with the increase of interface wavelength, and decreases with the increase of interface amplitude, and the interface amplitude has the greatest influence on the coating life. The coating life of the optimal combination is 947 cycles, which is 163.1% higher than the initial value. The formula for selecting wavelength and amplitude to make the coating life reach the maximum at different coating thicknesses is given. The research results can provide theoretical and methodological guidance for life prediction and structural optimization design of TBC.
Key words:  thermal barrier coatings  life prediction  genetic algorithm  response surface methodology  interface wavelength  interface amplitude
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