Gas-path-analysis (GPA) based diagnostic techniques enable health estimation of individual gas turbine components without the need for engine disassembly. Currently, the Gas turbine Simulation Program (GSP) gas path analysis tool is used at KLM Engine Services to assess component conditions of the CF6-50, CF6-80 and CFM56-7B engine families during post-overhaul performance acceptance tests. The engine condition can be much more closely followed if on-wing (i.e., in-flight) performance data are analyzed also. By reducing unnecessary maintenance due to incorrect diagnosis, maintenance costs can be reduced, safety improved and engine availability increased. Gas path analysis of on-wing performance data is different in comparison to gas path analysis with test cell data. Generally fewer performance parameters are recorded on-wing and the available data are more affected by measurement uncertainty including sensor noise, sensor bias and varying operating conditions. Consequently, this reduces the potential and validity of the diagnostic results. In collaboration with KLM Engine Services, the feasibility of gas path analysis with on-wing performance data is assessed. In this paper the results of the feasibility study are presented, together with some applications and case studies of preliminary GPA results with on-wing data.
Most of the improvement in aviation during the last 7 decades has been mainly due to the advancement in the propulsion systems and technologies. The Advisory Council for Aeronautics Research in Europe (ACARE) has set ambitious objectives to be completed by 2020 and beyond; the major being reduction of CO2 emissions by more than 50%, for which significant improvement of the propulsion systems is required. However, it appears that a technological plateau has been reached with conventional engine architecture. The paper presents a novel hybrid engine architecture with inter turbine burner (ITB). The hybrid engine with two combustion chambers offers the possibility of operating on hydrocarbon fuels as well as liquid hydrogen, enabling the aimed reduction of CO2 emissions by 50% without encountering the storage problems related to pure hydrogen powered aircraft.
Compressor impellers for mass-market turbochargers are die-casted and machined with an aim to achieve high dimensional accuracy and acquire specific performance. However, manufacturing uncertainties result in dimensional deviations causing incompatible operational performance and assembly errors. Process capability limitations of the manufacturer can cause an increase in part rejections, resulting in high production cost. This paper presents a study on a centrifugal impeller with focus on the conceptual design phase to obtain a turbomachine that is robust to manufacturing uncertainties. The impeller has been parameterized and evaluated using a commercial computational fluid dynamics (CFDs) solver. Considering the computational cost of CFD, a surrogate model has been prepared for the impeller by response surface methodology (RSM) using space-filling Latin hypercube designs. A sensitivity analysis has been performed initially to identify the critical geometric parameters which influence the performance mainly. Sensitivity analysis is followed by the uncertainty propagation and quantification using the surrogate model based Monte Carlo simulation. Finally, a robust design optimization has been carried out using a stochastic optimization algorithm leading to a robust impeller design for which the performance is relatively insensitive to variability in geometry without reducing the sources of inherent variation, i.e., the manufacturing noise.
The paper presents generic simulation procedures for air-planes and aero-engines to support in-flight exhaust emission studies. They take a detailed account of the vehicle aerodynamics and performance as well as engine performance during typical flight missions. The procedures are coupled via lookup tables containing engine data for standard thrust settings. The models and their applicability to emission analysis were tested in a case study for a long-haul airliner with two large turbofans. The Boeing Method 2 fuel flow methodology [1] was selected as a test pollutants model. CO2 and H2O were found by directly linking them to the fuel flow via constant emission indexes. The case study first proved the accuracy of the airplane and engine models by matching available validation data. Secondly, it demonstrated the possibilities of evaluating exhaust emissions at different segments of a flight mission. Both emission profiles and the cumulative environmental footprint of the mission were estimated. The paper concludes by applying the models for the analysis of engine exhaust under varying flight conditions and engine deterioration. This can be used as a tool for optimizing operational procedures for emission reduction and assessing the environmental performance of an aging fleet.
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