Nowadays,there has been an increasing focus on integrated flight propulsion control and the inlet-exhaust design for the aero-propulsion system.Traditional component-level models are inadequate due to installed perfor...Nowadays,there has been an increasing focus on integrated flight propulsion control and the inlet-exhaust design for the aero-propulsion system.Traditional component-level models are inadequate due to installed performance deviations and mismatches between the real engine and the model,failing to meet the accuracy requirements of supersonic conditions.This paper establishes a quasi-one-dimensional model for the inlet-exhaust system and conducts experimental calibration.Additionally,a mechanism-data fusion adaptive modeling scheme using an Extreme Learning Machine based on the Salp Swarm Algorithm(SSA-ELM)is proposed.The study reveals the inlet model’s efficacy in reflecting installed performance,flow matching,and mitigating pressure distortion,while the nozzle model accurately predicts flow coefficients and thrust coefficients,and identifies various operational states.The model’s output closely aligns with typical experimental parameters.By combining offline optimization and online adaptive correction,the mechanismdata fusion adaptive model substantially reduces output errors during regular flights and varying levels of degradation,and effectively handles gradual degradation within a single flight cycle.Notably,the mechanism-data fusion adaptive model holistically addresses total pressure errors within the inlet-exhaust system and normal shock location correction.This approach significantly curbs performance deviations in supersonic conditions.For example,at Ma=2.0,the system error impressively drops from 34.17%to merely 6.54%,while errors for other flight conditions consistently stay below the 2.95%threshold.These findings underscore the clear superiority of the proposed method.展开更多
Iterative coupled methods are widely used in multi-fidelity simulation of rotating components due to the simple implementation,which iteratively eliminates the errors between the computational fluid dynamics models an...Iterative coupled methods are widely used in multi-fidelity simulation of rotating components due to the simple implementation,which iteratively eliminates the errors between the computational fluid dynamics models and approximate characteristic maps.However,the convergence and accuracy of the iterative coupled method are trapped in characteristic maps.In particular,iterative steps increase sharply as the operation point moves away from the design point.To address these problems,this paper developed an auxiliary iterative coupled method that introduces the static-pressure-auxiliary characteristic maps and modification factor of mass flow into the component-level model.The developed auxiliary method realized the direct transfer of static pressure between the high-fidelity models and the component-level model.Multi-fidelity simulations of the throttle characteristics were carried out using both the auxiliary and traditional iterative coupled methods,and the simulation results were verified using the experimental data.Additionally,the consistency between the auxiliary and traditional iterative coupled methods was confirmed.Subsequently,multi-fidelity simulations of the speed and altitude characteristics were also conducted.The auxiliary and traditional iterative coupled methods were evaluated in terms of convergence speed and accuracy.The evaluation indicated that the auxiliary iterative coupled method significantly reduces iterative steps by approximately 50%at the near-choked state.In general,the auxiliary iterative coupled method is preferred as a development of the traditional iterative coupled method in the near-choked state,and the combined auxiliary-traditional iterative coupled method provides support for successful multi-fidelity simulation in far-off-design conditions.展开更多
Aero-engine gas path health monitoring plays a critical role in Engine Health Management(EHM). To achieve unbiased estimation, traditional filtering methods have strict requirements on measurement parameters which som...Aero-engine gas path health monitoring plays a critical role in Engine Health Management(EHM). To achieve unbiased estimation, traditional filtering methods have strict requirements on measurement parameters which sometimes cannot be measured in engineering. The most typical one is the High-Pressure Turbine(HPT) exit pressure, which is vital to distinguishing failure modes between different turbines. For the case of an abrupt failure occurring in a single turbine component, a model-based sensor measurement reconstruction method is proposed in this paper. First,to estimate the missing measurements, the forward algorithm and the backward algorithm are developed based on corresponding component models according to the failure hypotheses. Then,a new fault diagnosis logic is designed and the traditional nonlinear filter is improved by adding the measurement estimation module and the health parameter correction module, which uses the reconstructed measurement to complete the health parameters estimation. Simulation results show that the proposed method can well restore the desired measurement and the estimated measurement can be used in the turbofan engine gas path diagnosis. Compared with the diagnosis under the condition of missing sensors, this method can distinguish between different failure modes, quantify the variations of health parameters, and achieve good performance at multiple operating points in the flight envelope.展开更多
Multi-fidelity simulations incorporate computational fluid dynamics(CFD) models into a thermodynamic model,enabling the simulation of the overall performance of an entire gas turbine with high-fidelity components.Trad...Multi-fidelity simulations incorporate computational fluid dynamics(CFD) models into a thermodynamic model,enabling the simulation of the overall performance of an entire gas turbine with high-fidelity components.Traditional iterative coupled methods rely on characteristic maps,while fully coupled methods directly incorporate high-fidelity simulations.However,fully coupled methods face challenges in simulating rotating components,including weak convergence and complex implementation.To address these challenges,a fully coupled method with logarithmic transformations was developed to directly integrate high-fidelity CFD models of multiple rotating components.The developed fully coupled method was then applied to evaluate the overall performance of a KJ66 micro gas turbine across various off-design simulations.The developed fully coupled method was also compared with the traditional iterative coupled method.Furthermore,experimental data from ground tests were conducted to verify its effectiveness.The convergence history indicated that the proposed fully coupled method exhibited stable convergence,even under far-off-design simulations.The experimental verification demonstrated that the multi-fidelity simulation with the fully coupled method achieved high accuracy in off-design conditions.Further analysis revealed inherent differences in the coupling methods of CFD models between the developed fully coupled and traditional iterative coupled methods.These inherent differences provide valuable insights for reducing errors between the component-level model and CFD models in different coupling methods.The developed fully coupled method,introducing logarithmic transformations,offers more realistic support for the detailed and optimal design of high-fidelity rotating components within the overall performance platform of gas turbines.展开更多
基金co-supported by the National Natural Science Foundation of China(Nos.61890921,61890924)the National Science and Technology Major Project,China(No.J2019-1-0019-0018).
文摘Nowadays,there has been an increasing focus on integrated flight propulsion control and the inlet-exhaust design for the aero-propulsion system.Traditional component-level models are inadequate due to installed performance deviations and mismatches between the real engine and the model,failing to meet the accuracy requirements of supersonic conditions.This paper establishes a quasi-one-dimensional model for the inlet-exhaust system and conducts experimental calibration.Additionally,a mechanism-data fusion adaptive modeling scheme using an Extreme Learning Machine based on the Salp Swarm Algorithm(SSA-ELM)is proposed.The study reveals the inlet model’s efficacy in reflecting installed performance,flow matching,and mitigating pressure distortion,while the nozzle model accurately predicts flow coefficients and thrust coefficients,and identifies various operational states.The model’s output closely aligns with typical experimental parameters.By combining offline optimization and online adaptive correction,the mechanismdata fusion adaptive model substantially reduces output errors during regular flights and varying levels of degradation,and effectively handles gradual degradation within a single flight cycle.Notably,the mechanism-data fusion adaptive model holistically addresses total pressure errors within the inlet-exhaust system and normal shock location correction.This approach significantly curbs performance deviations in supersonic conditions.For example,at Ma=2.0,the system error impressively drops from 34.17%to merely 6.54%,while errors for other flight conditions consistently stay below the 2.95%threshold.These findings underscore the clear superiority of the proposed method.
基金funded by the Science and Technology Innovation Committee Foundation of Shenzhen,China(Nos.JCYJ20200109141403840 and ZDSYS20220527171405012)the National Natural Science Foundation of China(No.52106045)the Pearl River Talent Recruitment Program,China(No.2019CX01Z084)。
文摘Iterative coupled methods are widely used in multi-fidelity simulation of rotating components due to the simple implementation,which iteratively eliminates the errors between the computational fluid dynamics models and approximate characteristic maps.However,the convergence and accuracy of the iterative coupled method are trapped in characteristic maps.In particular,iterative steps increase sharply as the operation point moves away from the design point.To address these problems,this paper developed an auxiliary iterative coupled method that introduces the static-pressure-auxiliary characteristic maps and modification factor of mass flow into the component-level model.The developed auxiliary method realized the direct transfer of static pressure between the high-fidelity models and the component-level model.Multi-fidelity simulations of the throttle characteristics were carried out using both the auxiliary and traditional iterative coupled methods,and the simulation results were verified using the experimental data.Additionally,the consistency between the auxiliary and traditional iterative coupled methods was confirmed.Subsequently,multi-fidelity simulations of the speed and altitude characteristics were also conducted.The auxiliary and traditional iterative coupled methods were evaluated in terms of convergence speed and accuracy.The evaluation indicated that the auxiliary iterative coupled method significantly reduces iterative steps by approximately 50%at the near-choked state.In general,the auxiliary iterative coupled method is preferred as a development of the traditional iterative coupled method in the near-choked state,and the combined auxiliary-traditional iterative coupled method provides support for successful multi-fidelity simulation in far-off-design conditions.
基金supported by the Fundamental Research Funds for the Central Universities(NO.NS2018018)
文摘Aero-engine gas path health monitoring plays a critical role in Engine Health Management(EHM). To achieve unbiased estimation, traditional filtering methods have strict requirements on measurement parameters which sometimes cannot be measured in engineering. The most typical one is the High-Pressure Turbine(HPT) exit pressure, which is vital to distinguishing failure modes between different turbines. For the case of an abrupt failure occurring in a single turbine component, a model-based sensor measurement reconstruction method is proposed in this paper. First,to estimate the missing measurements, the forward algorithm and the backward algorithm are developed based on corresponding component models according to the failure hypotheses. Then,a new fault diagnosis logic is designed and the traditional nonlinear filter is improved by adding the measurement estimation module and the health parameter correction module, which uses the reconstructed measurement to complete the health parameters estimation. Simulation results show that the proposed method can well restore the desired measurement and the estimated measurement can be used in the turbofan engine gas path diagnosis. Compared with the diagnosis under the condition of missing sensors, this method can distinguish between different failure modes, quantify the variations of health parameters, and achieve good performance at multiple operating points in the flight envelope.
基金funded by the Science and Technology Innovation Committee Foundation of Shenzhen,Grant No.JCYJ20200109141403840 and Grant No.ZDSYS20220527171405012the National Natural Science Foundation of China (NSFC),Grant No.52106045。
文摘Multi-fidelity simulations incorporate computational fluid dynamics(CFD) models into a thermodynamic model,enabling the simulation of the overall performance of an entire gas turbine with high-fidelity components.Traditional iterative coupled methods rely on characteristic maps,while fully coupled methods directly incorporate high-fidelity simulations.However,fully coupled methods face challenges in simulating rotating components,including weak convergence and complex implementation.To address these challenges,a fully coupled method with logarithmic transformations was developed to directly integrate high-fidelity CFD models of multiple rotating components.The developed fully coupled method was then applied to evaluate the overall performance of a KJ66 micro gas turbine across various off-design simulations.The developed fully coupled method was also compared with the traditional iterative coupled method.Furthermore,experimental data from ground tests were conducted to verify its effectiveness.The convergence history indicated that the proposed fully coupled method exhibited stable convergence,even under far-off-design simulations.The experimental verification demonstrated that the multi-fidelity simulation with the fully coupled method achieved high accuracy in off-design conditions.Further analysis revealed inherent differences in the coupling methods of CFD models between the developed fully coupled and traditional iterative coupled methods.These inherent differences provide valuable insights for reducing errors between the component-level model and CFD models in different coupling methods.The developed fully coupled method,introducing logarithmic transformations,offers more realistic support for the detailed and optimal design of high-fidelity rotating components within the overall performance platform of gas turbines.
