Turbine blisks are assembled using blades,disks and casings.They can endure complex loads at a high temperature,high pressure and high speed.The safe operation of assembled structures depends on the reliability of eac...Turbine blisks are assembled using blades,disks and casings.They can endure complex loads at a high temperature,high pressure and high speed.The safe operation of assembled structures depends on the reliability of each component.Monte Carlo(MC)simulation is commonly used to analyze structural reliability,but this method needs to run thousands of computations.In order to assess the clearance reliability of assembled structures in an efficient and precise manner,the novel Kriging-based decomposed-coordinated(DC)(DCNK)approach is proposed by integrating the DC strategy,the Kriging model and the importance sampling-based Markov chain(MCIS)technique.In this method,the DC strategy is used to decompose a multi-objective problem into many single-objective problems.The relationships between these many single-objectives and the overall objective are then coordinated.The Kriging model is applied to establish the limit state functions of the single-objectives and multi-objective problems,while the MCIS method is used to assess the structural assembled clearance reliability.Moreover,a highly nonlinear complex compound function is first utilized to verify the DCNK model from a mathematical perspective.Then,the reliability of an aeroengine high-pressure turbine(HPT)blade-tip radial running clearance(BTRRC)is analyzed to validate the DCNK approach by considering thermo-structural interaction.The analytical results show that the reliability is 0.9976 when the allowance value of the BTTRC is 1.7650×10^(−3)m.Compared with different methodologies(including direct simulation,the classical Kriging model,and the weighted response surface method(WRSM)),the proposed method holds obvious advantages in computing time and precision,as well as simulation efficiency and precision.The efforts of this paper provide a useful approach to analyzing assembled clearance reliability and contribute to the development of structural reliability theory.展开更多
Because of the fractional order derivatives, the identification of the fractional order system（FOS） is more complex than that of an integral order system（IOS）. In order to avoid high time consumption in the system...Because of the fractional order derivatives, the identification of the fractional order system（FOS） is more complex than that of an integral order system（IOS）. In order to avoid high time consumption in the system identification, the leastsquares method is used to find other parameters by fixing the fractional derivative order. Hereafter, the optimal parameters of a system will be found by varying the derivative order in an interval. In addition, the operational matrix of the fractional order integration combined with the multi-resolution nature of a wavelet is used to accelerate the FOS identification, which is achieved by discarding wavelet coefficients of high-frequency components of input and output signals. In the end, the identifications of some known fractional order systems and an elastic torsion system are used to verify the proposed method.展开更多
基金This paper is supported by the National Natural Science Foundation of China(51875465)the Civil Aircraft Scientific Research Project.The authors would like to thank their generous supports.
文摘Turbine blisks are assembled using blades,disks and casings.They can endure complex loads at a high temperature,high pressure and high speed.The safe operation of assembled structures depends on the reliability of each component.Monte Carlo(MC)simulation is commonly used to analyze structural reliability,but this method needs to run thousands of computations.In order to assess the clearance reliability of assembled structures in an efficient and precise manner,the novel Kriging-based decomposed-coordinated(DC)(DCNK)approach is proposed by integrating the DC strategy,the Kriging model and the importance sampling-based Markov chain(MCIS)technique.In this method,the DC strategy is used to decompose a multi-objective problem into many single-objective problems.The relationships between these many single-objectives and the overall objective are then coordinated.The Kriging model is applied to establish the limit state functions of the single-objectives and multi-objective problems,while the MCIS method is used to assess the structural assembled clearance reliability.Moreover,a highly nonlinear complex compound function is first utilized to verify the DCNK model from a mathematical perspective.Then,the reliability of an aeroengine high-pressure turbine(HPT)blade-tip radial running clearance(BTRRC)is analyzed to validate the DCNK approach by considering thermo-structural interaction.The analytical results show that the reliability is 0.9976 when the allowance value of the BTTRC is 1.7650×10^(−3)m.Compared with different methodologies(including direct simulation,the classical Kriging model,and the weighted response surface method(WRSM)),the proposed method holds obvious advantages in computing time and precision,as well as simulation efficiency and precision.The efforts of this paper provide a useful approach to analyzing assembled clearance reliability and contribute to the development of structural reliability theory.
基金Project supported by the National Natural Science Foundation of China(Grant No.61271395)the Natural Science Foundation of Jiangsu Province,China(Grant No.BK20161513)
文摘Because of the fractional order derivatives, the identification of the fractional order system（FOS） is more complex than that of an integral order system（IOS）. In order to avoid high time consumption in the system identification, the leastsquares method is used to find other parameters by fixing the fractional derivative order. Hereafter, the optimal parameters of a system will be found by varying the derivative order in an interval. In addition, the operational matrix of the fractional order integration combined with the multi-resolution nature of a wavelet is used to accelerate the FOS identification, which is achieved by discarding wavelet coefficients of high-frequency components of input and output signals. In the end, the identifications of some known fractional order systems and an elastic torsion system are used to verify the proposed method.
