Predicting the Temporal Progression of Aircraft Engine Compressor Performance Deterioration due to Particle Deposition

2017 ◽  
Author(s):  
Felix Döring ◽  
Stephan Staudacher ◽  
Christian Koch
Keyword(s):  
High Pressure ◽  
Particle Deposition ◽  
Operating Time ◽  
Engine Performance ◽  
Aircraft Engine ◽  
Operating Costs ◽  
Maximum Efficiency ◽  
Published Data ◽  
Blade Row ◽  
Performance Deterioration

Aircraft engine performance deterioration due to particle deposition on compressor blading and end walls gradually progresses with increasing time of operation. Deposition effects can be mitigated by on-wing maintenance actions. Application of condition based maintenance strategies in order to minimize operating costs requires high-grade physical deterioration models. In previous work, a model and experimental setup were developed to quantify both magnitudes and timescales of deposition effects on blade row performance as a function of engine operating time. The model and experimental data published therein were now used to predict the deteriorated performance of aircraft engine high-pressure compressors. A given procedure to analytically derive stage characteristics from blade row data was altered in such a way as to account for stage performance deterioration through a set of modifiers. These time-dependent modifiers were calculated from the blade row performance deterioration model. As an example of application, the stage characteristics of the NASA Energy Efficient Engine high-pressure compressor were derived from published data. The stage characteristics were gradually modified according to the aforementioned approach. A stage-stacking procedure was then used to calculate the full map of the deteriorated compressor. Results showed a gradually progressing shift of compressor speed lines to lower mass flows and pressure ratios as well as a collapsing of efficiency isolines. The design point of the new engine and the point of maximum efficiency no longer coincide. Maximum efficiency decreased. The methodology presented enables aircraft engine operators to predict individual engine on-wing recoverable performance deterioration to optimize maintenance scheduling and, thus, reduce operating costs.

Modeling Particle Deposition Effects in Aircraft Engine Compressors

2017 ◽  
Vol 139 (5) ◽  
Author(s):  
Felix Döring ◽  
Stephan Staudacher ◽  
Christian Koch ◽  
Matthias Weißschuh
Keyword(s):  
Gas Turbines ◽  
Particle Deposition ◽  
Axial Compressor ◽  
Pressure Rise ◽  
Engine Performance ◽  
Aircraft Engine ◽  
Deposition Process ◽  
Aircraft Engines ◽  
Blade Row ◽  
Performance Deterioration

Airborne particles ingested in aircraft engines deposit on compressor blading and end walls. Aerodynamic surfaces degrade on a microscopic and macroscopic scale. Blade row, compressor, and engine performance deteriorate. Optimization of maintenance scheduling to mitigate these effects requires modeling of the deterioration process. This work provides a deterioration model on blade row level and the experimental validation of this model in a newly designed deposition test rig. When reviewing previously published work, a clear focus on deposition effects in industrial gas turbines becomes evident. The present work focuses on quantifying magnitudes and timescales of deposition effects in aircraft engines and the adaptation of the generalized Kern and Seaton deposition model for application in axial compressor blade rows. The test rig's cascade was designed to be representative of aircraft engine compressor blading. The cascade was exposed to an accelerated deposition process. Reproducible deposition patterns were identified. Results showed an asymptotic progression of blade row performance deterioration. A significant increase in total pressure loss and decrease in static pressure rise were measured. Application of the validated model using existing particle concentration and flight cycle data showed that more than 95% of the performance deterioration due to deposition occurs within the first 1000 flight cycles.

scholarly journals An Integrated Approach for Aircraft Engine Performance Estimation and Fault Diagnostics

2013 ◽  
Vol 135 (7) ◽  
Author(s):  
Donald L. Simon ◽  
Jeffrey B. Armstrong
Keyword(s):  
Kalman Filter ◽  
Engine Performance ◽  
Aircraft Engine ◽  
Fault Isolation ◽  
Performance Estimation ◽  
Estimation Accuracy ◽  
Fault Diagnostics ◽  
Tuning Parameters ◽  
Performance Deterioration ◽  
Health Parameters

A Kalman filter-based approach for integrated on-line aircraft engine performance estimation and gas path fault diagnostics is presented. This technique is specifically designed for underdetermined estimation problems where there are more unknown system parameters representing deterioration and faults than available sensor measurements. A previously developed methodology is applied to optimally design a Kalman filter to estimate a vector of tuning parameters, appropriately sized to enable estimation. The estimated tuning parameters can then be transformed into a larger vector of health parameters representing system performance deterioration and fault effects. The results of this study show that basing fault isolation decisions solely on the estimated health parameter vector does not provide ideal results. Furthermore, expanding the number of the health parameters to address additional gas path faults causes a decrease in the estimation accuracy of those health parameters representative of turbomachinery performance deterioration. However, improved fault isolation performance is demonstrated through direct analysis of the estimated tuning parameters produced by the Kalman filter. This was found to provide equivalent or superior accuracy compared to the conventional fault isolation approach based on the analysis of sensed engine outputs, while simplifying online implementation requirements. Results from the application of these techniques to an aircraft engine simulation are presented and discussed.

scholarly journals An Integrated Approach for Aircraft Engine Performance Estimation and Fault Diagnostics

2012 ◽  
Author(s):  
Donald L. Simon ◽  
Jeffrey B. Armstrong
Keyword(s):  
Kalman Filter ◽  
Engine Performance ◽  
Aircraft Engine ◽  
Fault Isolation ◽  
Performance Estimation ◽  
Estimation Accuracy ◽  
Fault Diagnostics ◽  
Tuning Parameters ◽  
Performance Deterioration ◽  
Health Parameters

A Kalman filter-based approach for integrated on-line aircraft engine performance estimation and gas path fault diagnostics is presented. This technique is specifically designed for underdetermined estimation problems where there are more unknown system parameters representing deterioration and faults than available sensor measurements. A previously developed methodology is applied to optimally design a Kalman filter to estimate a vector of tuning parameters, appropriately sized to enable estimation. The estimated tuning parameters can then be transformed into a larger vector of health parameters representing system performance deterioration and fault effects. The results of this study show that basing fault isolation decisions solely on the estimated health parameter vector does not provide ideal results. Furthermore, expanding the number of the health parameters to address additional gas path faults causes a decrease in the estimation accuracy of those health parameters representative of turbomachinery performance deterioration. However, improved fault isolation performance is demonstrated through direct analysis of the estimated tuning parameters produced by the Kalman filter. This was found to provide equivalent or superior accuracy compared to the conventional fault isolation approach based on the analysis of sensed engine outputs, while simplifying online implementation requirements. Results from the application of these techniques to an aircraft engine simulation are presented and discussed.

scholarly journals Aircraft Gas Turbine Engine Health Monitoring System by Real Flight Data

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Mustagime Tülin Yildirim ◽  
Bülent Kurt
Keyword(s):  
Gas Turbine ◽  
Engine Performance ◽  
Aircraft Engine ◽  
Gas Turbine Engine ◽  
Gas Temperature ◽  
Turbine Engine ◽  
Fuel Flow ◽  
The Status ◽  
Performance Deterioration ◽  
Artificial Neural Network Ann

Modern condition monitoring-based methods are used to reduce maintenance costs, increase aircraft safety, and reduce fuel consumption. In the literature, parameters such as engine fan speeds, vibration, oil pressure, oil temperature, exhaust gas temperature (EGT), and fuel flow are used to determine performance deterioration in gas turbine engines. In this study, a new model was developed to get information about the gas turbine engine’s condition. For this model, multiple regression analysis was carried out to determine the effect of the flight parameters on the EGT parameter and the artificial neural network (ANN) method was used in the identification of EGT parameter. At the end of the study, a network that predicts the EGT parameter with the smallest margin of error has been developed. An interface for instant monitoring of the status of the aircraft engine has been designed in MATLAB Simulink. Any performance degradation that may occur in the aircraft’s gas turbine engine can be easily detected graphically or by the engine performance deterioration value. Also, it has been indicated that it could be a new indicator that informs the pilots in the event of a fault in the sensor of the EGT parameter that they monitor while flying.

scholarly journals Monte Carlo Predictions of Aero-Engine Performance Degradation Due to Particle Ingestion

Aerospace ◽  
2021 ◽  
Vol 8 (6) ◽  
pp. 146
Author(s):  
Matthew Ellis ◽  
Nicholas Bojdo ◽  
Antonio Filippone ◽  
Rory Clarkson
Keyword(s):  
High Pressure ◽  
Monte Carlo ◽  
Particle Deposition ◽  
Monte Carlo Model ◽  
Engine Performance ◽  
Performance Data ◽  
High Pressure Turbine ◽  
Particle Cloud ◽  
Validation Data ◽  
Particle Properties

Aero-engines, which encounter clouds of airborne particulate, experience reduced performance due to the deposition of particles on their high-pressure turbine nozzle guide vanes. The rate of this degradation depends on particle properties, engine operating state and the duration of exposure to the particle cloud, variables that are often unknown or poorly constrained, leading to uncertainty in model predictions. A novel method coupling one-dimensional gas turbine performance analysis with generalised predictions of particle deposition is developed and applied through the use of Monte Carlo simulations to better predict high-pressure turbine degradation. This enables a statistical analysis of deterioration from which mean performance losses and confidence intervals can be defined, allowing reductions in engine life and increased operational risk to be quantified. The method is demonstrated by replicating two particle cloud encounter events for the Rolls-Royce RB211-524C engine and is used to predict empirical particle properties by correlating measured engine performance data with Monte Carlo model inputs. Potential improvements in the confidence of these predictions due to more tightly constrained input and validation data are also demonstrated. Finally, the potential combination of the Monte Carlo coupled degradation model with in-service engine performance data and particle properties determined through remote or in situ sensing is outlined and its role in a digital twin to enable a predictive approach to operational capability is discussed.

Blade stacking and clocking effects in two-stage high-pressure axial turbine

2019 ◽  
Vol 91 (8) ◽  
pp. 1133-1146
Author(s):  
Kaddour Touil ◽  
Adel Ghenaiet
Keyword(s):  
High Pressure ◽  
Leading Edge ◽  
Maximum Efficiency ◽  
Two Stage ◽  
Axial Turbine ◽  
Content Type ◽  
Second Stage ◽  
Blade Row ◽  
Practical Implications ◽  
Isentropic Efficiency

Purpose The purpose of this paper is to characterize the blade–row interaction and investigate the effects of axial spacing and clocking in a two-stage high-pressure axial turbine. Design/methodology/approach Flow simulations were performed by means of Ansys-CFX code. First, the effects of blade–row stacking on the expansion performance were investigated by considering the stage interface. Second the axial spacing and the clocking positions between successive blade–rows were varied, the flow field considering the frozen interface was solved, and the flow interaction was assessed. Findings The axial spacing seems affecting the turbine isentropic efficiency in both design and off-design operating conditions. Besides, there are differences in aerodynamic loading and isentropic efficiency between the maximum efficiency clocking positions where the wakes of the first-stage vanes impinge around the leading edge of the second-stage vanes, compared to the clocking position of minimum efficiency where the ingested wakes pass halfway of the second-stage vanes. Research limitations/implications Research implications include understanding the effects of stacking, axial spacing and clocking in axial turbine stages, improving the expansion properties by determining the adequate spacing and locating the leading edge of vanes and blades in both first and second stages with respect to the maximum efficiency clocking positions. Practical implications Practical implications include improving the aerodynamic design of high-pressure axial turbine stages. Originality/value The expansion process in a two-stage high-pressure axial turbine and the effects of blade–row spacing and clocking are elucidated thoroughly.

scholarly journals Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation

2009 ◽  
Vol 132 (3) ◽  
Author(s):  
Donald L. Simon ◽  
Sanjay Garg
Keyword(s):  
Kalman Filter ◽  
Estimation Error ◽  
Engine Performance ◽  
Aircraft Engine ◽  
Operating Conditions ◽  
Performance Estimation ◽  
Experimental Simulation ◽  
Tuning Parameter ◽  
Estimation Accuracy ◽  
On Line

A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multivariable iterative search routine that seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared with the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy.

A Flight Simulation Vision for Aeropropulsion Altitude Ground Test Facilities

2005 ◽  
Vol 127 (1) ◽  
pp. 8-17 ◽  
Author(s):  
Milt Davis ◽  
Peter Montgomery
Keyword(s):  
System Performance ◽  
Engine Performance ◽  
Aircraft Engine ◽  
Flight Simulation ◽  
Propulsion System ◽  
Test Facility ◽  
Flight Testing ◽  
Test Environment ◽  
Ground Test ◽  
Aircraft System

Testing of a gas turbine engine for aircraft propulsion applications may be conducted in the actual aircraft or in a ground-test environment. Ground test facilities simulate flight conditions by providing airflow at pressures and temperatures experienced during flight. Flight-testing of the full aircraft system provides the best means of obtaining the exact environment that the propulsion system must operate in but must deal with limitations in the amount and type of instrumentation that can be put on-board the aircraft. Due to this limitation, engine performance may not be fully characterized. On the other hand, ground-test simulation provides the ability to enhance the instrumentation set such that engine performance can be fully quantified. However, the current ground-test methodology only simulates the flight environment thus placing limitations on obtaining system performance in the real environment. Generally, a combination of ground and flight tests is necessary to quantify the propulsion system performance over the entire envelop of aircraft operation. To alleviate some of the dependence on flight-testing to obtain engine performance during maneuvers or transients that are not currently done during ground testing, a planned enhancement to ground-test facilities was investigated and reported in this paper that will allow certain categories of flight maneuvers to be conducted. Ground-test facility performance is simulated via a numerical model that duplicates the current facility capabilities and with proper modifications represents planned improvements that allow certain aircraft maneuvers. The vision presented in this paper includes using an aircraft simulator that uses pilot inputs to maneuver the aircraft engine. The aircraft simulator then drives the facility to provide the correct engine environmental conditions represented by the flight maneuver.

Sign in / Sign up

Export Citation Format

Share Document