Model-Based Dynamic Performance Simulation of a Microturbine Using Flight Test Data

none3siMicroturbines can be used not only in models and education but also to propel UAVs. However, their wider adoption is limited by their relatively low efficiency and durability. Validated simulation models are required to monitor their performance, improve their lifetime, and to design engine control systems. This study aims at developing a numerical model of a micro gas turbine intended for prediction and prognostics of engine performance. To build a reliable zero-dimensional model, the available compressor and turbine maps were scaled to the available test bench data with the least squares method, to meet the performance of the engine achieved during bench and flight tests. A steady-state aeroengine model was implemented in the Gas turbine Simulation Program (GSP) and was compared with experimental operating points. The selected flight data were then used as input for the transient engine model. The exhaust gas temperature (EGT) and fuel flow were chosen as the two key parameters to validate the model, comparing the numerical predicted values with the experimental ones. The observed difference between the model and the flight data was lower than 3% for both EGT and fuel flow.openErario M.L.; De Giorgi M.G.; Przysowa R.Erario, M. L.; De Giorgi, M. G.; Przysowa, R

Analysis of Fan Blade Vibration with a Non-Contact Method

AbstractComposite fan blades are more and more common both in aviation and ground applications. This work aims to characterize the vibration parameters of plastic blades installed in a wind tunnel fan by a non-contact method, namely blade tip timing (BTT). Blade dynamics was predicted with finite element modelling (FEM) and confirmed experimentally by tip timing measurements and analysis of data. BTT results were acquired and compared in two different configurations. A good agreement between predicted and measured frequency values was obtained for the fundamental mode. Significant differences were observed for the second and third modes due to material anisotropy and contact effects which could not be modelled because necessary material data were unavailable

Extreme Learning Machine-Based Diagnostics for Component Degradation in a Microturbine

Micro turbojets are used for propelling radio-controlled aircraft, aerial targets, and personal air vehicles. When compared to full-scale engines, they are characterized by relatively low efficiency and durability. In this context, the degraded performance of gas path components could lead to an unacceptable reduction in the overall engine performance. In this work, a data-driven model based on a conventional artificial neural network (ANN) and an extreme learning machine (ELM) was used for estimating the performance degradation of the micro turbojet. The training datasets containing the performance data of the engine with degraded components were generated using the validated GSP model and the Monte Carlo approach. In particular, compressor and turbine performance degradation were simulated for three different flight regimes. It was confirmed that component degradation had a similar impact in flight than at sea level. Finally, the datasets were used in the training and testing process of the ELM algorithm with four different input vectors. Two vectors had an extensive number of virtual sensors, and the other two were reduced to just fuel flow and exhaust gas temperature. Even with the small number of sensors, the high prediction accuracy of ELM was maintained for takeoff and cruise but was slightly worse for variable flight conditions

Tip-Clearance Measurement in the First Stage of the Compressor of an Aircraft Engine

In this article, we report the design of a reflective intensity-modulated optical fiber sensor for blade tip-clearance measurement, and the experimental results for the first stage of a compressor of an aircraft engine operating in real conditions. The tests were performed in a ground test cell, where the engine completed four cycles from idling state to takeoff and back to idling state. During these tests, the rotational speed of the compressor ranged between 7000 and 15,600 rpm. The main component of the sensor is a tetrafurcated bundle of optical fibers, with which the resulting precision of the experimental measurements was 12 mu m for a measurement range from 2 to 4 mm. To get this precision the effect of temperature on the optoelectronic components of the sensor was compensated by calibrating the sensor in a climate chamber. A custom-designed MATLAB program was employed to simulate the behavior of the sensor prior to its manufacture.This work has been funded in part by the Fondo Europeo de Desarrollo Regional (FEDER); by the Ministerio de Economia y Competitividad under project TEC2015-638263-C03-1-R; by the Gobierno Vasco/Eusko Jaurlaritza under projects IT933-16 and ELKARTEK; and by the University of the Basque Country UPV/EHU under programmes UFI11/16 and Euskampus

Special Issue “Technologies for Future Distributed Engine Control Systems”

Current trends in aviation greatly expand the use of highly integrated, increasingly autonomous air vehicles, with distributed engine control systems (DECS) [...

Correlative Method for Diagnosing Gas-Turbine Tribological Systems

Lubricated tribosystems such as main-shaft bearings in gas turbines have been successfully diagnosed by oil sampling for many years. In practice, the interpretation of wear debris analysis results can pose a challenge due to the intricate structure of power transmission systems and the varying degrees of sensitivity among test methods. In this work, oil samples acquired from the fleet of M601T turboprop engines were tested with optical emission spectrometry and analyzed with a correlative model. Customized alarm limits were determined for iron by binning aluminum and zinc concentration into four levels. Two-way analysis of variance (ANOVA) with interaction analysis and post hoc tests was carried out to study the impact of aluminum and zinc concentration on iron concentration. A strong correlation between iron and aluminum, as well as a weaker but still statistically significant correlation between iron and zinc, was observed. When the model was applied to evaluate a selected engine, deviations of iron concentration from the established limits indicated accelerated wear long before the occurrence of critical damage. Thanks to ANOVA, the assessment of engine health was based on a statistically proven correlation between the values of the dependent variable and the classifying factors

Determination of serviceability limits of a turboshaft engine by the criterion of blade natural frequency and stall margin

This paper analyses the health and performance of 12–stage axial compressor of the TV3–117VM/VMA turboshaft operated in a desert environment. The results of the dimensional control of 4,800 worn blades are analysed to model the wear process. Operational experience is used to assess the effectiveness of an Inlet Particle Separator. Numerical modal analysis is performed to generate the Campbell diagram of worn blades and identify resonant blade vibration which can lead to high cycle fatigue (HCF). It is shown that the gradual loss of the stall margin over time determines the serviceability limits of compressor blades. Recommendations setting out go / no–go criteria are made to maintenance and repair organisations

Determination of Serviceability Limits of a Turboshaft Engine by the Criterion of Blade Natural Frequency and Stall Margin

This paper analyzes the health and performance of the 12-stage axial compressor of the TV3-117VM/VMA turboshaft operated in a desert environment. The results of the dimensional control of 4800 worn blades are analyzed to model the wear process. Operational experience and two-phase flow simulations are used to assess the effectiveness of an inlet particle separator. Numerical modal analysis is performed to generate the Campbell diagram of the worn blades and identify resonant blade vibrations which can lead to high cycle fatigue (HCF): mode 7 engine order 30 in the first stage and mode 8 engine order 60 in the fourth. It is also shown that the gradual loss of the stall margin over time determines the serviceability limits of compressor blades. In particular, the chord wear of sixth-stage blades as high as 6.19 mm results in a reduction of the stall margin by 15–17% and a permanent stall at 770–790 flight hours. In addition, recommendations setting out go/no-go criteria are made to maintenance and repair organizations

An influence of shroud design parameters on the static stresses of blade assemblies

In this study, the structural analysis of the blade assemblies was carried out using the finite element method to determine the influence of design parameters of shroud couplings on the static stresses of turbine rotor blades with zigzag and slant shroud couplings. An angle of inclination of the shroud contact surfaces with respect to the rotor rotation axis was selected as the design parameter. Based on the calculation results, it has been found that irrespective of the type of the shroud coupling, the values of the contact pressure and the stresses in the shroud increase with the angle of inclination of the contact surfaces. Also, for the slant shroud coupling, the stresses increase in the blade airfoil portion with the increase of angle of inclination of the contact surfaces, while for the zigzag shroud coupling the contact stresses decrease with the increase of this angle. It was concluded that the zigzag shroud coupling causes the increase in static stresses when compared to the slant one

Estimation of performance parameters of turbine engine components using experimental data in parametric uncertainty conditions

Gas Path Analysis and matching turbine engine models to experimental data are inverse problems of mathematical modelling which are characterized by parametric uncertainty. It results from the fact that the number of measured parameters is significantly less than the number of components’ performance parameters needed to describe the real engine. Inthese conditions, even small measurement errors can result in a high variation of results, and obtained efficiency, lossfactors etc. can appear out of the physical range. The paper presents new method for setting a priori information about the engine and its performance in view of fuzzy sets, forming objective functions and scalar convolutions synthesis of these functions to estimate gas-path components’ parameters. The comparison of the proposed approach with traditional methods showed that its main advantage is high stability of estimation in the parametric uncertainty conditions. It reduces scattering, excludes incorrect solutions which do not correspond to a priori assumptions, and also helps to implement the Gas Path Analysis at the limited number of measured parameters