Deep learning-based modeling method for probabilistic LCF life prediction of turbine blisk

Turbine blisk is one of the typical components of gas turbine engines.The fatigue life of turbine blisk directly affects the reliability and safety of both turbine blisk and aeroengine whole-body.To monitor the performance degradation of an aeroengine,an efficient deep learning-based modeling method called convolutional-deep neural network(C-DNN)method is proposed by absorbing the advantages of both convolutional neural network(CNN)and deep neural network(DNN),to perform the probabilistic low cycle fatigue(LCF)life prediction of turbine blisk regarding uncertain influencing parameters.In the C-DNN method,the CNN method is used to extract the useful features of LCF life data by adopting two convolutional layers,to ensure the precision of C-DNN modeling.The two close-connected layers in DNN are employed for the regression modeling of aeroengine turbine blisk LCF life,to keep the ac-curacy of LCF life prediction.Through the probabilistic analysis of turbine blisk and the com-parison of methods(ANN,CNN,DNN and C-DNN),it is revealed that the proposed C-DNN method is an effective mean for turbine blisk LCF life prediction and major factors affecting the LCF life were gained,and the method holds high efficiency and accuracy in regression modeling and simulations.This study provides a promising LCF life prediction method for complex structures,which contribute to monitor health status for aeroengines operation.

Structural design of aeroengine radiators:State of the art and perspectives

Structural modularization,lightweight and functional integration are the urgent devel-opment directions for next generation high-performance aeroengines.Heat concentration during aeroengine operation would lead to local high temperature,which tremendously negative impacts on aeroengine structural life and performance.Therefore,the design and optimization of radiator structures are significant for the efficiency and reliability of aeroengine.The structural geometry design and layout optimization of radiators is promising to improve the heat dissipation efficiency and reduce aerodynamic loss.The purpose of this study is to investigate the state of the art and perspectives of aeroengine radiator structural design by a comprehensive literature review.The main contents involve the review on the structural design and layout optimization technologies of radiator structures,the analyses of the structural features,design theory and methods of existed radiator structures,the induction of the theory and method of different radiators structural opti-mization design,and the discussion on the application perspectives of advanced structures in aeroengine radiators,the report on the current challenges and development directions of the design of radiator structures,including smart materials,lattice structures,variable structures,advanced optimization theories and methods,heat dissipation methods and so forth.The efforts of this study are promising to support the high-performance and lightweight design of aeroengine structures besides radiators,and thermal management system.