scholarly journals Aircraft Engine Performance Study Using Flight Data Recorder Archives

Author(s):  
Yashovardhan S. Chati ◽  
Hamsa Balakrishnan
2021 ◽  
pp. 1-25
Author(s):  
A. Filippone ◽  
B. Parkes ◽  
N. Bojdo ◽  
T. Kelly

ABSTRACT Real-time flight data from the Automatic Dependent Surveillance–Broadcast (ADS-B) has been integrated, through a data interface, with a flight performance computer program to predict aviation emissions at altitude. The ADS-B, along with data from Mode-S, are then used to ‘fly’ selected long-range aircraft models (Airbus A380-841, A330-343 and A350-900) and one turboprop (ATR72). Over 2,500 flight trajectories have been processed to demonstrate the integration between databases and software systems. Emissions are calculated for altitudes greater than 3,000 feet (609m) and exclude landing and take-off cycles. This proof of concept fills a gap in the aviation emissions inventories, since it uses real-time flights and produces estimates at a very granular level. It can be used to analyse emissions of gases such as carbon dioxide ( $\mathrm{CO}_2$ ), carbon monoxide (CO), nitrogen oxides ( $\mathrm{NO}_x$ ) and water vapour on a specific route (city pair), for a specific aircraft, for an entire fleet, or on a seasonal basis. It is shown how $\mathrm{NO}_x$ and water vapour emissions concentrate around tropospheric altitudes only for long-range flights, and that the cruise range is the biggest discriminator in the absolute value of these and other exhaust emissions.


Author(s):  
Donald L. Simon ◽  
Sanjay Garg

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.


2005 ◽  
Vol 127 (1) ◽  
pp. 8-17 ◽  
Author(s):  
Milt Davis ◽  
Peter Montgomery

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.


Author(s):  
Donald L. Simon ◽  
Jeffrey B. Armstrong

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.


2017 ◽  
Author(s):  
Christopher R. Yost ◽  
Kristopher M. Bedka ◽  
Patrick Minnis ◽  
Louis Nguyen ◽  
J. Walter Strapp ◽  
...  

Abstract. Recent studies have found that flight through deep convective storms and ingestion of high mass concentrations of ice crystals, also known as high ice water content (HIWC), into aircraft engines can adversely impact aircraft engine performance. These aircraft engine icing events caused by HIWC have been documented during flight in weak reflectivity regions near convective updraft regions that do not appear threatening in onboard weather radar data. Three airborne field campaigns were conducted in 2014 and 2015 to better understand how HIWC is distributed in deep convection, both as a function of altitude and proximity to convective updraft regions, and to facilitate development of new methods for detecting HIWC conditions, in addition to many other research and regulatory goals. This paper describes a prototype method for detecting HIWC conditions using geostationary (GEO) satellite imager data coupled with in-situ total water content (TWC) observations collected during the flight campaigns. Three satellite-derived parameters were determined to be most useful for determining HIWC probability: 1) the horizontal proximity of the aircraft to the nearest overshooting convective updraft or textured anvil cloud, 2) tropopause-relative infrared brightness temperature, and 3) daytime-only cloud optical depth. Statistical fits between collocated TWC and GEO satellite parameters were used to determine the membership functions for the fuzzy logic derivation of HIWC probability. The products were demonstrated using data from several campaign flights and validated using a subset of the satellite-aircraft collocation database. The daytime HIWC probability was found to agree quite well with TWC time trends and identified extreme TWC events with high probability. Discrimination of HIWC was more challenging at night with IR-only information. The products show the greatest capability for discriminating TWC ≥ 0.5 g m−3. Product validation remains challenging due to vertical TWC uncertainties and the typically coarse spatio-temporal resolution of the GEO data.


2019 ◽  
Vol 252 ◽  
pp. 05007 ◽  
Author(s):  
Łukasz Grabowski ◽  
Ksenia Siadkowska ◽  
Krzysztof Skiba

This paper reports the results of simulation works of Rotax 912 aircraft piston engine, which is a basic unit in most ultra-light aircrafts. The method for preparing the model aircraft engine operation process was presented. Simulation tests were carried out in the AVL Boost programme. The programme allows a full use of zero-dimensional and one-dimensional modelling. It also allows a comparison of other engine models. The developed model has enabled us to simulate the flow of air through the inlet pipes, carburettors, valves and combustion process. The preparation of the model required us to enter parameters that are not available in the manufacturer's catalogue, therefore, necessary measurements and analysis of the engine parts were carried out on a laboratory bench. The calculations in the AVL Boost programme were carried out in the conditions determined for the selected BMEP values with the objective of characterising the engine performance by determining its power, torque and fuel consumption.


2017 ◽  
Vol 139 (5) ◽  
Author(s):  
Felix Döring ◽  
Stephan Staudacher ◽  
Christian Koch ◽  
Matthias Weißschuh

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.


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