To reasonably design the blade-tip radial running clearance(BTRRC) of high pressure turbine and improve the performance and reliability of gas turbine, the multi-object multi-discipline reliability sensitivity analysi...To reasonably design the blade-tip radial running clearance(BTRRC) of high pressure turbine and improve the performance and reliability of gas turbine, the multi-object multi-discipline reliability sensitivity analysis of BTRRC was accomplished from a probabilistic prospective by considering nonlinear material attributes and dynamic loads. Firstly, multiply response surface model(MRSM) was proposed and the mathematical model of this method was established based on quadratic function. Secondly, the BTRRC was decomposed into three sub-components(turbine disk, blade and casing), and then the single response surface functions(SRSFs) of three structures were built in line with the basic idea of MRSM. Thirdly, the response surface function(MRSM) of BTRRC was reshaped by coordinating SRSFs. From the analysis, it is acquired to probabilistic distribution characteristics of input-output variables, failure probabilities of blade-tip clearance under different static blade-tip clearances δ and major factors impacting BTRRC. Considering the reliability and efficiency of gas turbine, δ=1.87 mm is an optimally acceptable option for rational BTRRC. Through the comparison of three analysis methods(Monte Carlo method, traditional response surface method and MRSM), the results show that MRSM has higher accuracy and higher efficiency in reliability sensitivity analysis of BTRRC. These strengths are likely to become more prominent with the increasing times of simulations. The present study offers an effective and promising approach for reliability sensitivity analysis and optimal design of complex dynamic assembly relationship.展开更多
Because of the randomness of many impact factors influencing the dynamic assembly relationship of complex machinery, the reliability analysis of dynamic assembly relationship needs to be accomplished considering the r...Because of the randomness of many impact factors influencing the dynamic assembly relationship of complex machinery, the reliability analysis of dynamic assembly relationship needs to be accomplished considering the randomness from a probabilistic perspective. To improve the accuracy and efficiency of dynamic assembly relationship reliability analysis, the mechanical dynamic assembly reliability(MDAR) theory and a distributed collaborative response surface method(DCRSM) are proposed. The mathematic model of DCRSM is established based on the quadratic response surface function, and verified by the assembly relationship reliability analysis of aeroengine high pressure turbine(HPT) blade-tip radial running clearance(BTRRC). Through the comparison of the DCRSM, traditional response surface method(RSM) and Monte Carlo Method(MCM), the results show that the DCRSM is not able to accomplish the computational task which is impossible for the other methods when the number of simulation is more than 100 000 times, but also the computational precision for the DCRSM is basically consistent with the MCM and improved by 0.40-4.63% to the RSM, furthermore, the computational efficiency of DCRSM is up to about 188 times of the MCM and 55 times of the RSM under 10000 times simulations. The DCRSM is demonstrated to be a feasible and effective approach for markedly improving the computational efficiency and accuracy of MDAR analysis. Thus, the proposed research provides the promising theory and method for the MDAR design and optimization, and opens a novel research direction of probabilistic analysis for developing the high-performance and high-reliability of aeroengine.展开更多
Rotor blades in a radial turbine with nozzle guide vanes typically experience harmonic aerodynamic excitations due to the rotor stator interaction. Dynamic stresses induced by the harmonic excitations can result in hi...Rotor blades in a radial turbine with nozzle guide vanes typically experience harmonic aerodynamic excitations due to the rotor stator interaction. Dynamic stresses induced by the harmonic excitations can result in high cycle fatigue(HCF) of the blades. A reliable prediction method for forced response issue is essential to avoid the HCF problem. In this work, the forced response mechanisms were investigated based on a fluid structure interaction(FSI) method. Aerodynamic excitations were obtained by three-dimensional unsteady computational fluid dynamics(CFD) simulation with phase shifted periodic boundary conditions. The first two harmonic pressures were determined as the primary components of the excitation and applied to finite element(FE) model to conduct the computational structural dynamics(CSD) simulation. The computed results from the harmonic forced response analysis show good agreement with the predictions of Singh's advanced frequency evaluation(SAFE) diagram. Moreover, the mode superposition method used in FE simulation offers an efficient way to provide quantitative assessments of mode response levels and resonant strength.展开更多
基金Projects(51175017,51245027)supported by the National Natural Science Foundation of China
文摘To reasonably design the blade-tip radial running clearance(BTRRC) of high pressure turbine and improve the performance and reliability of gas turbine, the multi-object multi-discipline reliability sensitivity analysis of BTRRC was accomplished from a probabilistic prospective by considering nonlinear material attributes and dynamic loads. Firstly, multiply response surface model(MRSM) was proposed and the mathematical model of this method was established based on quadratic function. Secondly, the BTRRC was decomposed into three sub-components(turbine disk, blade and casing), and then the single response surface functions(SRSFs) of three structures were built in line with the basic idea of MRSM. Thirdly, the response surface function(MRSM) of BTRRC was reshaped by coordinating SRSFs. From the analysis, it is acquired to probabilistic distribution characteristics of input-output variables, failure probabilities of blade-tip clearance under different static blade-tip clearances δ and major factors impacting BTRRC. Considering the reliability and efficiency of gas turbine, δ=1.87 mm is an optimally acceptable option for rational BTRRC. Through the comparison of three analysis methods(Monte Carlo method, traditional response surface method and MRSM), the results show that MRSM has higher accuracy and higher efficiency in reliability sensitivity analysis of BTRRC. These strengths are likely to become more prominent with the increasing times of simulations. The present study offers an effective and promising approach for reliability sensitivity analysis and optimal design of complex dynamic assembly relationship.
基金supported by National Natural Science Foundation of China(Grant Nos.51175017,51245027)Innovation Foundation of Beihang University for PhD Graduates,China(Grant No.YWF-12-RBYJ008)Research Fund for the Doctoral Program of Higher Education of China(Grant No.20111102110011)
文摘Because of the randomness of many impact factors influencing the dynamic assembly relationship of complex machinery, the reliability analysis of dynamic assembly relationship needs to be accomplished considering the randomness from a probabilistic perspective. To improve the accuracy and efficiency of dynamic assembly relationship reliability analysis, the mechanical dynamic assembly reliability(MDAR) theory and a distributed collaborative response surface method(DCRSM) are proposed. The mathematic model of DCRSM is established based on the quadratic response surface function, and verified by the assembly relationship reliability analysis of aeroengine high pressure turbine(HPT) blade-tip radial running clearance(BTRRC). Through the comparison of the DCRSM, traditional response surface method(RSM) and Monte Carlo Method(MCM), the results show that the DCRSM is not able to accomplish the computational task which is impossible for the other methods when the number of simulation is more than 100 000 times, but also the computational precision for the DCRSM is basically consistent with the MCM and improved by 0.40-4.63% to the RSM, furthermore, the computational efficiency of DCRSM is up to about 188 times of the MCM and 55 times of the RSM under 10000 times simulations. The DCRSM is demonstrated to be a feasible and effective approach for markedly improving the computational efficiency and accuracy of MDAR analysis. Thus, the proposed research provides the promising theory and method for the MDAR design and optimization, and opens a novel research direction of probabilistic analysis for developing the high-performance and high-reliability of aeroengine.
基金supported by the National Natural Science Foundation of China(Grant No.51276018)
文摘Rotor blades in a radial turbine with nozzle guide vanes typically experience harmonic aerodynamic excitations due to the rotor stator interaction. Dynamic stresses induced by the harmonic excitations can result in high cycle fatigue(HCF) of the blades. A reliable prediction method for forced response issue is essential to avoid the HCF problem. In this work, the forced response mechanisms were investigated based on a fluid structure interaction(FSI) method. Aerodynamic excitations were obtained by three-dimensional unsteady computational fluid dynamics(CFD) simulation with phase shifted periodic boundary conditions. The first two harmonic pressures were determined as the primary components of the excitation and applied to finite element(FE) model to conduct the computational structural dynamics(CSD) simulation. The computed results from the harmonic forced response analysis show good agreement with the predictions of Singh's advanced frequency evaluation(SAFE) diagram. Moreover, the mode superposition method used in FE simulation offers an efficient way to provide quantitative assessments of mode response levels and resonant strength.