Alumni - Page 5 of 9 - Knowledge and Development Centre Mainport Schiphol

Stijn van Selling (MSc)

Supporting Time-Based Separation and Merging in Approach Control

Aviation as a whole is expected to grow, therefore adjustments to the current air traffic management system will need to be made. Part of these adjustments is the switch from distance-based separation to time-based separation. This will allow the airport capacity to increase when strong headwinds are present on the active runway. An increase in runway capacity will also result in less holding time required as more aircraft can land in the same amount of time, hence saving fuel and thus making for a more environment friendly operation. In order to facilitate time-based separation, the air traffic controller will need assistance in terms of decision support tools as time-based separation is not easily visualised on a 2D map. This research will thus try to design, implement and test such a decision support tool in order to support time-based separation in approach control.

Graduated: April 2023

Eneko Rodríguez (MSc)

Investigating the effects of Flexible Use of Airspace availability and plannability on fuel efficiency

All military airspace in the Amsterdam Flight Information Region (FIR) falls under the concept of Flexible Use of Airspace (FUA), which no longer considers airspace as purely ‘civil’ or ‘military’ but rather as a continuum to be allocated temporarily according to user requirements. The complexity of FUA lies in the challenge to harmonize the airspace usage according to these requirements, which largely contradict one another. On the one hand, the military user benefits from using the airspace flexibly, as the effectiveness of their missions and exercises depend on the availability of weather and equipment conditions. On the other hand, the civil users benefit from a high plannability to efficiently execute their operations. By modeling the fuel consumption of civil traffic, the effects of availability and plannability of the FUA in Amsterdam FIR can be computed. While FUA availability determines the route followed by a flight, FUA plannability determines how early the true trajectory is known. Announcing the FUA usage earlier results in avoiding to carry a surplus fuel, which increases the weight and thus fuel burnt of the aircraft. By understanding these effects, new guidelines of FUA usage and plannability may be proposed in the context of the ongoing Dutch Airspace Redesign Programme.

Graduated: August 2022

Bart Rozendaal (MSc)

A neural network approach in optimising airport strategy with trajectory prediction

As the airspace is getting increasingly crowded worldwide, the capacity management of airports is more important than ever. To avoid unnecessary and costly delays, it is crucial for airports to have well timed strategies and reliable arrival predictions. To achieve this, airports need accurate long-term trajectory predictions such that arrival times can be estimated with high precision. Countless factors such as weather conditions, restricted fly areas and air traffic control clearances cause route uncertainties, making it difficult to predict long-term trajectories accurately. In this thesis, a bidirectional LSTM recurrent neural network is proposed to solve a sequence-to-sequence learning problem and predict the most likely route flown by the aircraft before take off. The network is trained on historical flight plans only, making it easy to implement. The data exists of incoming flights on Schiphol international airport within Europe. Different Hyperparameters are tested to improve performance of the network.

Graduated: July 2022

Thomas Vermeulen (MSc)

Evaluation and assessment of the performance of the KNMI Schiphol Kansverwachting (SKV) for Mainport Schiphol with respect to wind direction and wind gusts

Accurate weather forecasts are crucial information to regulate the operations at Schiphol Airport. Sudden changes in weather conditions need to be communicated in a fast and efficient way to maintain the safety and efficiency for flight operations. KNMI provides a probabilistic weather forecast, called the Schiphol Kansverwachting (SKV), which is produced using output of numerical weather prediction models in combination with the latest observations and several statistical post-processing tools. In particular information on the wind direction and the wind gusts is highly important to support air traffic control. Relatively large errors could lead to restrictions which were in the end not needed or it could lead to restrictions which were issued too late. This research will evaluate the performance of the SKV of wind direction and wind gusts for three different weather models: HIRLAM, HARMONIE and ECMWF. Quantitative information on the forecasting errors will be identified, but also suggestions for possible improvements on the weather forecasts will be part of the result of this study.

Graduated: July 2022

Wesley Vork (BSc)

Develop sequential steps towards a Multi Airport System (MAS)

Dutch airports have grown significantly over the years. This growth is occurring almost autonomously. No mechanisms have been put in place to strategically balance this growth between Dutch airports, routes, or airspace. Without major reforms, the maximum capacity of the airspace will soon be reached. The relationship between EHLE, EHEH, EHRD and EHAM is under scrutiny. With autonomous growth and without mitigating measures, this will lead to the first airspace bottlenecks in 2023 and contiguous bottlenecks in 2035. By examining how air traffic can be better handled through joint air traffic management, the capacity bottlenecks can be addressed. By conducting a thorough research on the MAS, it will become clear what problem the MAS solves and how this system can be used to solve the capacity bottlenecks.

Graduated: July 2022

Max Aalberse (MSc)

Optimizing the distribution of aircraft over the IAF

Around Schiphol and many other airports the amount of movements allowed is constrained due to the considerable noise pollution from aircraft. For a large part the noise pollution is created by arriving aircraft that are in between the IAF and the RWY. During this period the aircraft are in so called transition. These transition routes are usually already optimized to reduce the noise disturbance to surrounding residents, but due to the positioning of the runways this is not always possible. A different distribution of the aircraft over the IAF could result in less noise disturbance for surrounding residents, but would also increase flight times and fuel usage and therefore an increase in other emissions such as CO₂. The goal of this research is to create a parameterized model that optimally distributes the aircraft over the IAF based on a quantitative trade-off between noise disturbance and CO₂ emissions. Resulting in a model that is potentially able to reduce noise disturbance around airports while keeping the increase in environmental impact at a minimum.

Graduated: June 2022

Edzer Oosterhof (MSc)

Effect of Trajectory Prediction Uncertainty on Debunching of Inbound Air Traffic

With the current growth in air traffic and the resulting developments in terms of environmental issues and noise abatement, the pressure on the Area Control Center (ACC) is growing. On the one hand the Terminal Control Area (TMA) requires arriving traffic to be handed over accurately sequenced and merged, and on the other hand the ACC tries to minimize the miles flown in its sector. At the tactical level, there are Air Traffic Flow Management (ATFM) measures in place for traffic within Europe. However, no such tactical measures exist for traffic from the North Atlantic Tracks, increasing the probability that bunching occurs in the ACC during peak loads. By tactically predicting bunching in the sector and at the Initial Approach Fixes, a concept for debunching should be devised that focusses on airborne delay consumption and sequencing of traffic in the Upper control Areas (UTA) before it enters the Control Area (ACC), decreasing the pressure on the ACC.

Graduated: March 2022

Rebekka van der Grift (MSc)

Aircraft Noise Model Improvement by Calibration of Noise-Power-Distance Values Using Acoustic Measurements

The impact of the aircraft industry on the environment becomes more evident every day. Especially for local communities around the airport, the noise nuisance is an important factor which puts a strain on the capacity of Schiphol mainport. This capacity is based on the noise levels around airports, which are calculated with noise models based of key input parameters. The accuracy of these models is thus of great importance for the Schiphol mainport and the local communities. This research aims to develop a dynamic noise model based on real world aircraft noise measurements taken by NOMOS. The measurements will be used to calibrate certain input parameters to minimise any differences between model and measurements. This method helps to keep the model up to date and validated. Using measurements instead of standard input parameters is expected to increase the accuracy of the model, but also increase the trust of local communities in noise modelling.

Graduated: January 2022

Stephanie Wiechers (MSc)

Design and Evaluation of a Support Tool for Planning Adherence While Holding Inbound Air Traffic

As Schiphol is one of the busiest airport in the world, with tight flight schedules and urban areas that lie under arrival routes, adherence to the time planning is very important. When extreme weather conditions cause delays over the entire arriving fleet, holding stacks are installed at the three Initial Approach Fixes (IAFs) around Schiphol. In the current operational environment, little support is offered to the holding stack controller (ACC) to gain an overview of the effects of speed and wind on the turn times and difference between inbound and outbound leg velocity. With increased support, the controller will be able to make decisions based on representative information and with that, deliver inbound aircraft to Approach (APP). The (expected) resulting increased EAT adherence should lead to more orderly traffic in the TMA, improving capacity and workload.

Graduated: December 2021

Soraya van Beek (MSc)

Improving probabilities of poor visibility and ceiling

In order to optimize the current Schiphol operations, an accurate weather forecast is of great importance. The Royal Netherlands Meteorological Institute (KNMI) provides a probabilistic weather forecast for Low Visibility Procedures (LVPs) to Schiphol, which is computed using deterministic weather models. If these LVPs occur due to low visibility or low ceiling, adjusted capacity and flow restriction are needed within airport operations. Inaccurate forecasting can lead to last-minute restrictions or restrictions when not needed. This research will assess the performance of the probabilistic forecast of visibility and ceiling at Schiphol airport. This will be done for the performance of three different weather models: HIRLAM, HARMONIE and ECMWF. Causes for inaccurate forecasting will be identified and suggestions for improvement of the probabilistic weather forecast will be the end result of this research.

Graduated: October 2021