DYNCAT will exemplarily study and quantify the shortcomings of the current practice of interaction between ATM/ATC and on-board flight management and demonstrate through analysis and simulation the potential benefits of improved operations:
The DYNCAT consortium has access to complete sets of operational data from the A320 family fleet of Swiss International Airlines (existing and recorded dedicatedly during the project; refer to Data Management section for more details). These data are complemented with recordings of the ATC instructions issued; which are checked against their implementation as manual inputs to the flight management and control systems. Also the type of approach or departure flown (such as Low Drag Low Power (LDLP) or Continuous Descent Operations (CDO)) can be categorised automatically so as to aggregate data sets for comparison. The associated methodology has already been demonstrated in previous research [SCHOLZ and SENSKE 2018]. By aggregating sets of approaches flown against comparable external circumstances, this initial data analysis already allows to quantify the ATM influence on fuel consumption (hence CO2 generation) and safety margins (stabilisation of the approach, braking distance, …). The data for this purpose will be provided and processed by SWISS’s Flight Data Office and analysed by DLR.
The combination of on-board data and noise measurements at ground reference stations will allow not only to additionally quantify both noise emission and exposure, but to relate it to the flight state and consequently to the ATC instructions. Earlier studies have already shown noise differences of up to 10 dB(A) (a doubling of the perceived noise) for outwardly identical overflights at measuring stations [KÖNIG 2010]. In these studies, however, only aircraft type, altitude and ground speed were known, and the reasons for the differences could not be identified. It is a unique opportunity for the DYNCAT consortium to be able to have access to all required data sources so as to analyse in detail the influence of ATC instructions and pilots’ actions on the environmental impact of the individual procedure. To this end, the Empa will measure and process the noise impact of the flights to be analysed at ground reference stations. The Empa will also acquire the necessary environmental/weather data via Meteo Swiss so that the subsequent analysis by DLR can be based on a complete view of a single flight in all its aspects.
Based on the analysis, an operational concept for supporting pilots in better dealing with ATC instructions and the actual (as opposed to predicted) weather situation will be developed. In order to quantify and justify the expected performance benefits, development and reference implementation of an improved Flight Management System (FMS) algorithm to better support the pilots in dealing with ATM constraints and actual weather situation is foreseen. In detail, THALES will perform iterative early prototyping based on system high-level specification, developing the DYNCAT algorithms into the Flight Management System. This includes Adapting the Theoretical Descent Path (TDP) and computing dynamically the predictions including optimized high-lift actuators extension. Maintaining the situation awareness and providing the associated HMI is a major aspect of this exercise.
Human-in-the-Loop Real-Time Simulation on an industry platform is performed in order to validate the pilots’ and air traffic controllers’ perspective of the new operational concepts and assess operational acceptability and feasibility. The simulation results will allow quantifying fuel efficiency and CO2 emissions and their comparison with both simulated and real-world approaches not using the DYNCAT solution.
While the benefits in terms of fuel consumption (and hence pollutants) can be extracted directly from the simulation, the assessment of the DYNCAT algorithms on noise footprint is performed separately with the sonAIR tool by the Empa [WUNDERLI 2018]. Noise footprints of the optimized approach trajectories will be calculated with the scientific aircraft noise calculation tool sonAIR. sonAIR allows for a highly detailed analysis of source as well as sound propagation phenomena. As a result, acoustic footprints of the sound exposure at the ground can be generated. As an example, figure 1.1 shows the acoustic footprint of an approach on Zurich airport. On this basis different single flight simulations can be compared. Simulations can either be performed for idealized situations, for example over a flat terrain and with a homogenous atmosphere, or for existing airports accounting for topography, ground properties, wind influences and a stratified atmosphere. The sonAIR noise emission model
([ZELLMANN et al. 2018], [ZELLMANN 2018]) accounts for the influence of the engine rotational speed N1, the airspeed and the aeroplane configuration model parameters. As an example, figure 1.2 shows the acoustic emission of the airframe noise of an A320-200 for different speed brake (SB) and landing gear (LG) settings in dependence of the Mach number.
In this way, the influence of the changes of airspeed, reduced usage of thrust as well as different flap-settings can be assessed. Conventional approaches will also be simulated by sonAIR and compared to the measurements (see above) to validate the model. Finally, the conventional approaches will be compared to flights with dynamic configuration changes to determine the environmental benefit of the new concept.
Adaption and extension of the sonAIR simulation tool: Already today, the sonAIR aircraft noise simulation model covers all mandatory features which are necessary to perform the task of evaluating and comparing the acoustic footprint of different landing configurations and procedures. Nevertheless, the model’s abilities need to be extended with regard to the goals of this project. The main task thereby is an extension allowing an automated assignment of individual flights to their specific meteorological conditions. In addition, a moving receiver at a fixed distance will be established to allow for a comparison of the sound exposure along the whole flight path.
The evaluation of flyability of the procedures will include pilots’ assessment of workload and situational awareness as well as the technical rating of the key approach parameters. Also the ATCo community will be invited to participate in the study. The organisation of the workshop(s) and the availability operational experts, namely of pilots from SWISS and Lufthansa as well as air traffic controllers from Skyguide will be assured through SkyLab foundation.
The same operational experts, in addition to experts from the consortium, will elaborate the recommendations for improvement of (airborne and ATM) procedures and identify possible regulatory changes. The potential needs for enabling technologies such as Extended Projected Profile (EPP) data link will also be considered.
[SCHOLZ and SENSKE 2018] Scholz, M. and Senske, V., Auswirkungen unterschiedlicher Anflugverfahren auf den Treibstoffverbrauch auf Grundlage operationeller Flugbetriebsdaten (Effects of Different Approach Procedures on Fuel Consumption based on Flight Operational Data). German Aerospace Congress (DLRK), Friedrichshafen: 2018.
[KÖNIG 2010] König, R.: Operational Evaluation of Steeper Final Landing Approaches, International Conference on Active Noise Abatement, 23.-24. September 2010, Frankfurt/Main, 2010.
[WUNDERLI et al. 2018] Wunderli, J. M., Zellmann, C., Köpfli, M., Habermacher, M., Schwab, O., Schlatter, F., & Schäffer, B.: sonAIR - a GIS-integrated spectral aircraft noise simulation tool for single flight prediction and noise mapping. Acta Acustica United with Acustica, 104(3), 440-451: 2018.
[ZELLMANN 2018] Zellmann, C.: Development of an aircraft noise emission model accounting for flight parameters (Doctoral dissertation). Technische Universität Berlin, Berlin, 2018.
[ZELLMANN et al. 2018] Zellmann, C., Schäffer, B., Wunderli, J. M., Isermann, U., & Paschereit, C. O.: Aircraft noise emission model accounting for aircraft flight parameters. Journal of Aircraft, 55(2), 682-695, 2018.
This project has received funding from the SESAR Joint Undertaking under the European Union's Horizon 2020 research and innovation programme under grant agreement No 893568.
SESAR 3 Joint Undertaking
(© SESARJU 2020-2022)
(© European Union, 1995-2022)
Copyright DYNCAT Consortium 2020-2022. All rights reserved. Licensed to the SJU under conditions.