Key Results

This work package has compiled an analysis of the current situation, relating ATC commands with on-board actions and the associated noise and fuel impact, which is available as D2.3, and so achieved the project’s first high-level objective. Furthermore, an operational concept for on-board configuration management to allow the flight crew to deal with ATC restrictions in a more environmentally friendly way was developed. This initial concept is laid down in D2.4, which concluded the bulk of the work in WP 2.

DLR as leader for WP 2 performed the data extraction and matching activity to combine data from all sources into 667 comprehensive data sets describing one approach operation each with all relevant onboard, Air Traffic Control (ATC), radar, weather and noise parameters including information on surrounding traffic, as documented in D2.2. This included development of software for automatic determination of the relevant phase of flight, development of data drivers and matching of data timestamps and conversion to common a format but also more mundane activities like the transcription of audio recordings from ATC. All data sets were anonymised to meet the requirements for personal data protection including the pilots’ unions’ prerequisites, and the data base has been provided to the project partners. It will also be used to prepare realistic scenarios for the real-time simulation in WP 4.

The main use of the database, however, was to allow a detailed analysis of the dependencies and effects of different common situations at Zurich airport. This analysis (D2.3) shows the bandwidth of pilots’ and ATCOs’ handling of different comparable situations and the consequential impact on noise, fuel consumption and safety margins like approach stabilisation. Potential for improvements was identified and presented to the experts of the advisory board as well as operational experts in the first project workshop.

These approaches and the experts’ feedback were consolidated into the initial Operational Concept (D2.4). A summary of the state of the art related to ATC, aircraft and aircraft systems and regulations and an extended analysis of the operationally observed energy dissipation strategies were produced. The Deliverable describes the initial operational concept of how the situation in the TMA can be improved related to fuel burn and noise exposure by supporting the pilots and controllers. It points out in detail how this concept will work and which parts of the current applied processes, regulations, tools or systems need to be changed or extended. This also includes the description of which data will be required for the extended functionality and if this data is already existing or how it could be gathered or transferred. The expected effects, positive but also negative, not only to fuel burn and noise exposure but also to all other important factors like workload for controllers and pilots, the throughput at airports and safety were considered and described.

D2.5 addresses the fourth objective and contains the final operational concept description, expanding on the initial one (D2.4) in view of the results of the validation exercise. It points out changes and extensions to the current applied processes, regulations, tools or systems, including data sources required for the extended functionality, taking into account the outcomes of both experts’ workshop with pilots, ATC controllers, scientists and experts from authorities. The expected effects, positive and negative, to fuel burn and noise exposure and other important factors like workload for controllers and pilots, the throughput at airports and safety are considered and described.

Proof of Concept

For the assessment of the potential noise reduction by implementing the DYNCAT system, the calculation capabilities of the sonAIR aircraft noise calculation program have been extended by a so-called "moved along receiver". There, Empa defined a receiver point which has a fixed distance and angle to the simulated aircraft to assess its noise emission along the flight trajectories independently of any receiver position on ground. This further allows a sensitivity analysis of all flight parameters in terms of their impact on the aircraft's noise emission and shows the key parameters for potential noise reduction. The required data interface between the simulation bench and sonAIR has been defined by Empa and Thales.

The validation activity started with the flight records analysis (WP2) and ended with the RTS analysis and benefits evaluation (WP4). The general idea was to benefit from the experience acquired thanks to the operational data analysis in order to set up piloted Real-Time Simulation exercises based on realistic operational scenarios.

One objective was to formally cover and verify the implementation described in D3.3 of all the requirements defined in the Preliminary High-Level System Specification (D3.1), as described in the Implementation Validation Plan (D3.2). Each requirement is linked to one or more validation objectives, each validation objective being associated to a unique success criterion that was to be verified by the validation scenario.

The experimental implementation comprised numerous functional items of the selected components, namely FMS and CDS evolutions. The FMS functions were extended with dynamic pseudo-waypoints, calculation of an optimised Continuous Descent Approach (CDA) vertical profile, lateral path determination, next speed and altitude restrictions release points, improvements on the speed brakes messages and an optimised distance-to-land computation. The CDS evolutions included controller intent entry as well as strategic and tactical energy management cues including over-energy warnings (D3.3). The way to present them was not validated though; the aim was to show that all necessary information for an optimised descent and energy management is available.

D3.4 updates and supersedes the Preliminary System High-Level Specification (D3.1) following the conduction of the piloted real-time simulation exercise. The update’s main objective is to adjust the high-level system requirements where necessary to match the DYNCAT prototype that has been implemented during the evaluation. Indeed, some modifications were brought to the Solution prototype in order to take into account the preliminary operational feedbacks and the maturity assessment of the initial requirements during the prototyping phase. This new version of the system specification relies on the DYNCAT Function Experimental Implementation Report (D3.3) and will support the further work beyond DYNCAT.

Environmental Benefits Quantification

Based on the descriptions in the Deliverable D3.2, the real-time simulator trials have been performed with pilots in the loop on an FMS test bench employing typical Airbus controls, notably an A320 family Flight Control Unit (FCU), and an A321 aircraft simulation model. The CDS and FMS were experimental evolutions, with which the pilots were familiarised first. Actual flight scenarios from the operations data set representing typical over-energy situations were chosen as reference for the scenario design: a shortcut from “NEGRA” waypoint using vectoring with an initial continuation on present heading and a three-step vectored left turn onto the localiser. This scenario was flown by active airline crews, with and without the new support functions. All pilots held type ratings for the Airbus A320 family and often further Airbus aircraft types; all seniority levels from first officer to training captain were represented.

All the validation means used to study the DYNCAT solution were defined with the objectives to assess the concept operational and technical feasibility, to conduct a preliminary performance assessment in terms of environment, human performance and safety, and to evaluate the flight predictability improvements thanks to the FMS trajectory stabilisation in selected modes (D3.3). The real-time pilot-in-the-loop simulation combined with the preliminary exercises involved an air traffic controller and twelve operational pilots that strongly contributed to increase the maturity of the solution and to refine the concept. Through questionnaires it was verified that they considered the scenarios, the simulation bench hardware and software (input devices, displays, accuracy of aircraft model, etc.) and the conduction of the experiment (briefing, ATC communication, crew resource management, etc.) respectively, sufficiently representative of the approach operations at Zurich airport, of the real aircraft and of real operations (D4.1).

The evaluation of the study addressed both operational issues (D4.1) and environmental considerations (D4.2). Operational improvements, e.g. predictability and stabilisation margins, were quantified through analysis of recorded data with pilot questionnaires complementing the human factors and overall system evaluation (D4.1). The environmental quantification relied on the fuel flow obtained from the simulation but especially on the aircraft state and configuration parameters supporting the noise simulation. Noise emission and propagation were calculated with the high-fidelity spectral aircraft noise simulation tool sonAIR that is able to take into account the aircraft’s configuration (high-lift devices and landing gears setting) and engine parameters and hence can demonstrate the effects of configuration changes in the noise footprint. The model was extended with a “moving receiver” (cf. D2.3) which has a fixed relative distance and angle to the simulated aircraft to assess its noise emission along the flight trajectories independently of any receiver position on ground, whose measured noise would also be influenced by any deviations in the trajectories. Thus, it was possible to quantify both noise emission (noise emitted from the source) and noise immission (noise felt at the observer’s location). These results are shown in more detail in D4.2.

The real-time simulation study thus served to address the second and third high-level goals of the project, namely to quantify the potential for environmental impact (noise, CO2 emission) reduction by comparing flights with and without the DNYCAT functions, and to measure improvements through novel pilot support functions on flights’ predictability and flyability in terms of pilot workload and safety.

Recommendations and Way Forward