Current students

Julia Huigen (MSc) – Environmental performance of TBO implementation evolutions at Mainport Schiphol

The aviation industry contributes significantly to global greenhouse gas emissions, and its environmental impact is expected to grow as air traffic continues to increase. As a result, both Airlines and Air Navigation Service Providers (ANSP) are required to reduce emissions. Numerous studies have shown the benefits of Continuous Climb Operations (CCO) and Continuous Descent Operations (CDO) in reducing fuel consumption and emissions. However, these studies often focus on simplified situations and do not fully consider the real challenges of busy and complex airspace using real-world data. This research aims to provide practical insights into the potential of TBO in the Dutch airspace. This thesis will investigate how vertical flight performance can be improved by quantifying, visualising, and mitigating inefficiencies through the implementation of TBO, particularly in the climb and descent phases. Airline data will be utilised as a necessary input to understand real-world operations and identify areas where performance can be improved.

 

 

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.

 

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.

 

 

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.