Current students

Eric van Pijlen (MSc) – Improving thrust and weight estimation for a Doc. 29 noise model by using ACMS-data to more accurately predict noise levels at Amsterdam Airport Schiphol

To regulate and mitigate noise impact of an airport on the surrounding communities, aircraft noise models are used to assess the impact. For these models, flights are modelled based on standard procedures of consecutive steps of speed and altitude changes and their corresponding delivered thrust. Under these procedures, however, lie a number of assumptions that could significantly alter the actual flown trajectory and thus noise pollution. Using real world data including data from the Aircraft Condition and Monitoring System (ACMS) and measurement data from the Noise Monitoring System (NOMOS), a comparison can be made between the estimated and real flight profiles.

 

 

Jens Bremer (MSc) – Improving the departure manager (DMAN) at Schiphol through PEGT Integration and optimization of the 10-minute bin mechanism

Schiphol’s current Departure Manager (DMAN) system, built around Target Off-Block Times (TOBT) and fixed 10-minute bins, offers operational stability but lacks the granularity needed to efficiently sequence departures in a high-density environment. This research investigates the integration of the Predicted End of Ground Handling Time (PEGT) into the DMAN. This new PEGT is a machine learning-based estimate developed by Schiphol Aviation Solutions’ Deep Turnaround project. PEGT leverages image-based machine learning algorithms to monitor over 70 unique turnaround events in real-time, generating predictive insights from over 150,000 historical turnarounds. These predictions enable early delay detection (up to 40 minutes in advance), supporting more precise TOBT estimates and improved gate and runway slot usage. Building on previous work and aligned with SESAR’s integrated DMAN-AMAN vision, this study also questions the effectiveness of rigid 10-minute departure bins. Using historical PEGT & TOBT data together with simulation models inspired by traffic flow constraints, this project evaluates dynamic bin sizing and delay damping mechanisms. The goal is to find a balance between operational stability and responsiveness in pre-departure sequencing. By combining turnaround predictions with more flexible pre-departure scheduling, this research aims to improve DMAN’s ability to manage departure flows efficiently, reduce last-minute gate conflicts, and enhance overall airport throughput at complex hub airports like Schiphol.

Lisa Blom (MSc) – Dynamic application of idle descents and off-idle geometric descents in the CTA

Many TBO techniques for Trajectory Management for arrivals involve either speed management by ATC or time management by the aircraft. However, in high density operations, both speed management and time management exhibit too many uncertainties, making them incompatible with high-density arrival operations. In previous research, the benefits of an alternative method of managing trajectories in a speed managed environment, have been demonstrated. In this alternative method, geometric descents are employed. Using these fixed angle descents, many uncertainties are eliminated. However, since such descents are flown off-idle, a different balance between capacity and flight efficiency is created. On the other hand, opportunities exist to allow aircraft to fly idle descents, when higher uncertainties can be permitted due to specific operational circumstances. This study will research the uncertainties associated with idle descents and off-idle geometric descents within the CTA related to EHAM. A model demonstrating the dynamic application of both descent techniques in a 24H operation will be developed based on determined criteria, and compared to static applications of the descent techniques.

Zeyad Fathallah (MSc) – Trajectory Management in High-Density XMAN Operations

Arrival management tools for optimizing arrival sequences have long been utilised; however, their potential is constrained by the size of airspace within a center’s control. Such limitations often manifest in inefficiencies such as delay vectoring and holdings at stacks. With more accurate trajectory information and technological enablers available in a TBO environment—such as ADS-C EPP, ED-254, and CPDLC—the time horizon for arrival management can be further extended to the cruise phase of flight, prior to top of descent. By impacting arrival aircraft at greater distances from their destination airport, upstream centres can contribute to meeting with merging and metering requirements through true 4D trajectory management; therefore further optimising the descent trajectory, reducing traffic bunching, and generating efficiency gains for airspace users.

This research aims to develop a trajectory solver providing (sub-)optimal, conflict-free trajectories in high-density operations in order to maximize TBO capabilities.

Jasper van Renssen (BSc) – A-Typical Approaches

Airports Control Traffic Regions (CTR) and Terminal Manoeuvring Areas (TMA) are characterized by a dense flow of air traffic with high complexity levels. In nominal operations, approach flight path safety management consists in procedures which guide the aircraft to intercept the final approach axis, and the runway slope with an expected configuration to land. Current Single European Sky ATM Research (SESAR) publications introduced the concept of atypical approaches. Currently, atypical approaches do not have a formal definition.

Certain abnormal flights have been observed in previous studies. These include both Non-Compliant Approaches (NCAs) and Non-Stabilized Approaches (NSA). A stabilized approach is one in which the pilot established and maintains a constant angle glide-path, an approach speed and an aircraft configuration towards a predetermined point on the landing runway. NCA approaches occur when the intermediate and final leg intercepting conditions do not comply with the prescription of the operational documentation. These approaches have found to generate difficulties for both crew and Air Traffic Control (ATC). The concern of NCA occurrence is that it may induce undesirable events such as NSAs or ultimate events such as Controlled Flight Into Terrain (CFIT).

This research will use historical surveillance data from the Amsterdam Flight Information Region, along with past studies on NCA and NSA, to define, identify, and quantify atypical approaches. The goal is to assess the frequency and occurrence of atypical approaches for Amsterdam’s  Airport Schiphol’s runways 18C and 18R.

Pam Smit (BSc) – Disturbance of Global Navigation Satellite System Signal Assignment

Flight Management System (FMS) navigation is sometimes disturbed by certain events in the form of (un)intentional jamming and spoofing of Global Navigation Satellite System (GNSS) signals. Often through Radio Frequency Interference (RFI). Due to the growing use and dependence on GNSS in aviation a loss of navigation could be a safety issue. It is for that reason that it is needed to investigate if, and for what duration GNSS signal occurs in the Dutch flight region. The primary goal is knowing what the reliability of the GNSS signals is, as received and reported by the aircraft.

By the use of data analysis, the reliability can be tested. Messages are downlinked by aircraft using ADS-B or Mode-S links. Some of those messages contain data related to the GNSS quality, thse are the so-called NIC/NAC values. This research aims to get a clear insight of the quality of the GNSS signals in the Dutch airspace.

 

Lydia Hoogendijk (BSc) – Automation in service provision: Reducing ATCO workload while achieving sustainability goals

Becoming an Air Traffic Control Officer (ATCO) is a rigorous and demanding process, requiring candidates to pass a series of aptitude, psychological, and physical assessments. The low success rate in training results in a shortage of ATCOs, leading to increased workload for those already in service. This, combined with rising air traffic volumes and the urgent need for sustainable aviation operations, underlines the necessity of enhanced automation in air traffic management. Furthermore, the transition from the AAA system to the iCAS system in the coming years is a key priority for LVNL. This research, grounded in the SESAR Master Plan 2025, explores automation opportunities within the iCAS system in comparison to the AAA system. The aim is to identify how automation can help address the challenges faced by ATCO’s, reduce their workload, and support more sustainable aviation operations, ultimately contributing to the efficiency and safety of air traffic management.

 

Rosemarijn Remmers (BSc) – Evaluating Safety Measures for Converging Runway Operations at Schiphol Airport

At many airports around the world, runways are used in different ways, including parallel, diverging, and converging operations. Each type of operation comes with its own challenges, depending on the airport’s layout and the way aircraft arrive and depart at the same time. At Schiphol Airport, due to its runway layout, not only parallel and diverging runways are used, but also converging runways. These converging runway operations require special safety measures to ensure that all aircraft can land and take off safely. These measures follow both international and Dutch safety regulations. However, maintaining a high level of safety is an ongoing process. It is important to regularly review whether these measures are effective and how they work in practice. In 2022, after thorough research, LVNL introduced new safety measures to improve the operation of runway combinations where aircraft take off and land on converging runways. These new measures are specifically designed for use in good visibility conditions and during the uniform daylight period. To ensure continuous improvement in safety, it is essential to assess how these measures are applied in daily practice and whether they effectively reduce operational risks. By analyzing real-world data and operational procedures, this research will provide insights into their effectiveness and identify any potential areas for further improvement.

Thomas Groothoff (MSc) – Effects of a decision support tool for the planner operating in multiple airport regions

Currently the workload of the executive operating in sector 3 is relatively high compared to other sectors within the Dutch airspace. An explanation one could give for the relative high workload is the fact that the diversity of the traffic passing through the sector is high, the traffic consists out of inbound and outbound traffic for EHAM, regional traffic from EHRD and EHEH and finally transit flights passing over the sector. In order to make such sectors more manageable for the executive a decision support tool for the planner for decision support in such sectors will be developed. Due to the higher fidelity of information available in the future through ADS-C data, new possibilities with regards to planning become possible. The tool that will be developed will make use of this ADS-C data in order to provide new insights to the planner, which allow for better planning that might reduce the complexity of the airspace. Due to this reduced complexity of the airspace, the workload of the executive will be reduced.

 

Lilien Madi (MSc) – Flight performance

Despite regulatory efforts at harmonizing and enhancing ATM performance, ANSPs still utilize indicators based on extra distance and time flown, such as Horizontal Flight Efficiency (HFE) to periodically report on their performance. However, additional distance and time flown may not necessarily correlate with increased fuel consumption particularly if the flight operates under more favourable conditions for fuel burn, such as optimal wind conditions, speed, and altitude. In certain cases, there is a negative correlation between horizontal efficiency and total fuel efficiency. Nonetheless, fuel-based metrics are not enforced as their complexity remain a limiting factor in their implementation. Given these metrics offer a more accurate representation of a flight’s environmental efficiency, this study will focus on fuel-based performance indicators and will utilize an open-source aircraft performance model (OpenAP) to reconstruct historical and flight plan trajectories, generate reference optimal trajectories and calculate each flight’s fuel consumption. The discrepancy in the fuel consumption of this set of trajectories will allow the identification of strategic, tactical, horizontal and vertical efficiencies in LVNL’s airspace.

Suze Garstman (BSc) – Implementing FF-ICE release 1

The concept of FF-ICE is to reduce the limitations of the current flight plan 2012 in order to support the future environment as detailed in the global ATM operational concept. Which concept is to support future ATM operations. Through the EU implementing rule 118/2021 phase 1, a.o. the introduction and use of a new flight plan will be mandatory 2025, December 31st. To reach this goal it is necessary to investigate if and how these new flight plan alterations can and will be supported by LVNL and her stakeholders.  Today’s flight plan presents the ATCO and other stakeholders the initial intend of a flight. No modifications during the flight are possible. However, FF-ICE phase 1 is designed to manage this problem specially towards Trajectory Based Operations. This new flight plan will be introduced to provide richer route/trajectory descriptions to support the efficient use of air space worldwide. This research aims to identify the alterations already in place or needed within LVNL and her stakeholders to comply with EU implementing rule 118/2012.

Matthijs Slobbe (MSc) – ETA predictions based on accurate weather

The weather is something that impacts everyone on a daily basis and much research has been done to improve weather forecasting in the past. This is also the case in the aviation industry, using traditional data sources as well as aircraft measurements. Previous research in this domain has developed the Meteo-Particle (MP) model which constructs a wind field based on data collected by aircraft and UAVs. Research has also been done with new physically inspired machine-learning approaches to create wind fields. This research, with the ultimate goal being to reduce uncertainty in aircraft estimated time of arrival (ETA), intends to approach the problem of creating accurate 3D wind fields with a diffusion neural network, filling in the gaps where there is no aircraft data available. Previous models struggle with non-uniform wind fields, this new approach presents an opportunity for better reconstruction of the wind fields under these conditions.

Teun Vleming (MSc) – Effects of a decision support tool on merging ILS and EoR traffic in approach control

Established on RNP AR APCH (EoR) is a navigation technique built upon Required Navigation Performance Authorization Required approaches, which use self-monitoring capabilities to achieve a high navigation accuracy. This allows aircraft to be established on complex (curved) approach paths and be released from standard radar separation requirements, which brings benefits in terms of reduced level segments, more predictable ground tracks and reduced track miles. Since not all operators at Schiphol Airport are equipped for EoR, the air traffic controller will have to handle a mix of traffic. Evaluations from previous implementations of EoR highly recommend offering a support tool to the approach controller. This research focuses on designing and evaluating a Decision Support Tool (DST) to enable merging EoR traffic with vectored ILS traffic on final approach for a single runway. The design will follow principles from Ecological Interface Design to create an effective and accepted tool. A simulation will be used to evaluate the DST in terms of controller workload, traffic capacity and ability to robustly handle different traffic mixes.

Ahmed Kubba (MSc) – Integration of Uncertainty Quantification in Extended Arrival Management and Long-Range Air Traffic Flow Management for Transatlantic Flights

The field of Air Traffic Management (ATM) is evolving to meet the growing complexities of air travel, yet traditional systems like Air Traffic Flow Management (ATFM) and Arrival Management (AMAN) still rely heavily on deterministic inputs. This reliance leads to inefficiencies, especially in long-haul operations such as transatlantic flights, where uncertainties in weather, demand, and capacity often disrupt planning. Despite recent advances in machine learning and delay prediction models, integrating uncertainty quantification into ATM systems remains underexplored, limiting their adaptability in dynamic environments. This research seeks to address these challenges by integrating uncertainty quantification into an Extended AMAN and LR-ATFM framework, with a focus on transatlantic operations. The goal is to develop a dynamic speed management system that adjusts flight speeds based on real-time uncertainty predictions. By enhancing predictability and optimizing sequencing, the approach aims to reduce fuel consumption, minimize delays, and improve overall efficiency. This is especially relevant as the aviation industry faces increasing pressures to manage growing air traffic sustainably and reduce carbon emissions.

Jorn van Beek (MSc) – Evaluation of Arrival Manager Horizon Extension in a Trajectory Management context

The Arrival Manager (AMAN) system is used to provide regulation on aircraft entering the Terminal Maneuvering Area (TMA). New regulations require the AMAN to freeze the sequence further ahead than the current 14 minutes with the aim of reducing fuel burn and decreasing controller workload. The increased horizon combined with uncertainty on arriving aircraft cause these aircraft to “pop-up”. This causes sequence errors which increase workload and fuel burn. These effects are more pronounced when using the AMAN in a Trajectory Based Operation (TBO) environment. Previously, research on the horizon extension and pop-up impact and solutions has been performed, although in idealized scenarios without a realistic solution. This research aims to model the Arrival Manager in high fidelity to support decisions on the Arrival Manager design, and to develop and test realistic solutions to decrease the impact of the pop-up traffic when extending the AMAN horizon towards TBO operations.