In this study, numerical models are used to analyse the influence of isolated component deterioration as well as the combination of miscellaneous deteriorated components on the transient performance of a high-bypass jet engine. For this purpose, the aerodynamic impact of major degradation effects in a high-pressure compressor (HPC) and turbine (HPT) is modelled and simulated by using 3D CFD (Computational Fluid Dynamics). The impact on overall jet engine performance is then modelled using an 1D Reduced Order Model (ROM). Initially, the HPC performance is investigated with a typical level of roughness on vanes and blades and the HPT performance with an increasing tip clearance. Subsequently, the overall performance of the jet engines with the isolated and combined deteriorated domains is computed by the in-house 1D performance tool ASTOR (AircraftEngine Simulation for Transient Operation Research). Degradations have a significant influence on the system stability and transient effects. In ASTOR, a system of differential equations including the equations of motion and further ordinary differential equations is solved. Compared to common ROMs, this enables a higher degree of accuracy. The results of temperature downstream of the high-pressure compressor and low-pressure turbine as well as the specific fuel composition and the HP rotational speed are used to estimate the degree and type of engine deterioration. However, the consideration of the system stability is necessary to analyse the characterisation in more detail. Finally, a simplified model which merges two engines with individual deteriorated domains into one combined deteriorated engine, is proposed. The simplified model predicts the performance of an engine which has been simulated with combined deteriorated components.
The effects of real combined variances in components and modules of aero engines, due to production tolerances or deterioration, on the performance of an aircraft engine are analysed in a knowledge-based process. For this purpose, an aero-thermodynamic virtual evaluation process that combines physical and probabilistic models to determine the sensitivities in the local module aerodynamics and the global overall performance is developed. Therefore, an automatic process that digitises, parameterises, reconstructs and analyses the geometry automatically using the example of a real turbofan high-pressure turbine blade is developed. The influence on the local aerodynamics of the reconstructed blade is investigated via a computational fluid dynamics (CFD) simulations. The results of the high-pressure turbine (HPT) CFD as well as of a Gas-Path-Analysis for further modules, such as the compressors and the low-pressure turbine, are transferred into a simulation of the performance of the whole aircraft engine to evaluate the overall performance. All results are used to train, validate and test several deep learning architectures. These metamodels are utilised for a global sensitivity analysis that is able to evaluate the sensitivities and interactions. On the one hand, the results show that the aerodynamics (especially the efficiency <inline-formula><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"><mml:msub><mml:mi>η</mml:mi><mml:mrow><mml:mi>H</mml:mi><mml:mi>P</mml:mi><mml:mi>T</mml:mi></mml:mrow></mml:msub></mml:math></inline-formula> and capacity <inline-formula><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"><mml:msub><mml:mrow><mml:mover><mml:mi>m</mml:mi><mml:mo>˙</mml:mo></mml:mover></mml:mrow><mml:mrow><mml:mi>H</mml:mi><mml:mi>P</mml:mi><mml:mi>T</mml:mi></mml:mrow></mml:msub></mml:math></inline-formula>) are particularly driven by the variation of the stagger angle. On the other hand, <inline-formula><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"><mml:msub><mml:mi>η</mml:mi><mml:mrow><mml:mi>H</mml:mi><mml:mi>P</mml:mi><mml:mi>T</mml:mi></mml:mrow></mml:msub></mml:math></inline-formula> is significantly related to exhaust gas temperature (Tt5), while specific fuel consumption (SFC) and mass flow <inline-formula><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"><mml:msub><mml:mrow><mml:mover><mml:mi>m</mml:mi><mml:mo>˙</mml:mo></mml:mover></mml:mrow><mml:mrow><mml:mi>H</mml:mi><mml:mi>P</mml:mi><mml:mi>T</mml:mi></mml:mrow></mml:msub></mml:math></inline-formula> are related to HPC exit temperature (Tt3). However, it can be seen that the high-pressure compressor has the most significant impact on the overall performance. This novel knowledge-based approach can accurately determine the impact of component variances on overall performance and complement experience-based approaches.
Malfunctions in the combustion chamber of aircraft engines influence downstream turbines. If individual burners vary in their performance, cold or hot streaks can enter and propagate through the turbine section and alter the temperature distribution in the exhaust of the engine. Analysing the variances in the temperature distribution of the exhaust jet provides information on the failure modes of the combustor. This can be used to identify damage to the aircraft engine, accelerate the inspection process and reduce maintenance cost. To investigate the influence of combustor failure on the temperature distribution, CFD simulations of a defined defect are carried out in this paper for a real size gasturbine engine. For this purpose, the total failure of one fuel nozzle in the combustion chamber, which results in a cold gas streak entering the turbine, is simulated. The cold streak is analysed by performing a turbine simulation for which the combustor exit profile is used on as an inlet condition. The simulations were performed using two different techniques. A frozen-rotor approach was used for the steady-state method to estimate the geometric influence on the mixing. The influence of the blade rotation is considered via unsteady simulation. The disturbance width and propagation were determined for both methods. The mixing and dispersion processes are found to be strong in the high pressure part of the turbine and are strongly influenced by the engine rotational speed.
The effects of real combined variances in components and modules of aero engines, due to production tolerances or deterioration, on the performance of an aircraft engine are analysed in a knowledge-based process. For this purpose, an aerothermodynamic virtual evaluation process that combines physical and probabilistic models to determine the sensitivities in the local module aerodynamics and the global overall performance is developed. Therefore, an automatic process that digitises, parameterises, reconstructs and analyses the geometry automatically using the example of a real turbofan highpressure turbine blade is developed. The influence on the local aerodynamics of the reconstructed blade is investigated via a computational fluid dynamics (CFD) simulations. The results of the high-pressure turbine (HPT) CFD as well as of a Gas- Path-Analysis for further modules, such as the compressors and the low-pressure turbine, are transferred into a simulation of the performance of the whole aircraft engine to evaluate the overall performance. All results are used to train, validate and test several deep learning architectures. These metamodels are utilised for a global sensitivity analysis that is able to evaluate the sensitivities and interactions. On the one hand, the results show that the aerodynamics (especially the efficiency hHPT and capacity m˙ HPT ) are particularly driven by the variation of the stagger angle. On the other hand, hHPT is significantly related to exhaust gas temperature (Tt5), while specific fuel consumption (SFC) and mass flow m˙ HPT are related to HPC exit temperature (Tt3). However, it can be seen that the high-pressure compressor has the most significant impact on the overall performance. This novel knowledge-based approach can accurately determine the impact of component variances on overall performance and complement experience-based approaches.
In this study, numerical models are used to analyse the influence of isolated component deterioration as well as the combination of miscellaneous deteriorated components on the transient performance of a high-bypass jet engine. For this purpose, the aerodynamic impact of major degradation effects in a high-pressure compressor (HPC) and turbine (HPT) is modelled and simulated by using 3D CFD (Computational Fluid Dynamics). The impact on overall jet engine performance is then modelled using an 1D Reduced Order Model (ROM). Initially, the HPC performance is investigated with a typical level of roughness on vanes and blades and the HPT performance with an increasing tip clearance. Subsequently, the overall performance of the jet engines with the isolated and combined deteriorated domains is computed by the in-house 1D performance tool ASTOR (AircraftEngine Simulation for Transient Operation Research). Degradations have a significant influence on the system stability and transient effects. In ASTOR, a system of differential equations including the equations of motion and further ordinary differential equations is solved. Compared to common ROMs, this enables a higher degree of accuracy. The results of temperature downstream of the high-pressure compressor and low-pressure turbine as well as the specific fuel composition and the HP rotational speed are used to estimate the degree and type of engine deterioration. However, the consideration of the system stability is necessary to analyse the characterisation in more detail. Finally, a simplified model which merges two engines with individual deteriorated domains into one combined deteriorated engine, is proposed. The simplified model predicts the performance of an engine which has been simulated with combined deteriorated components. (CRC) 871 "Regeneration of Complex Capital Goods" which is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)-SFB 871/3-119193472. The authors would like to thank the DFG for the support. Moreover, the authors would like to acknowledge the substantial contribution of the DLR Institute of Propulsion Technology and MTU Aero Engines AG for providing TRACE.
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