Marta Norte Vale de Almeida (MSc) – Modelling of de-icing operations at Schiphol Airport
Winter weather is known to cause major disruptions at airports worldwide, including Schiphol. One of the main causes of this is the need for aircraft de-icing, which adds an extra layer of complexity to airport ground operations, forcing airports to operate at limited capacity. As both inbound and outbound traffic have to be reduced, many flights are either cancelled or delayed.
An increase in the efficiency of the de-icing operations and in their coordination with the turnaround and runway scheduling processes could allow airports to operate at a less limited capacity despite severe winter weather conditions.
This project aims to model the de-icing operations at Schiphol Airport in severe winter weather conditions, with a focus on operational planning. The resulting model will be used to evaluate potential areas of improvement and will have the potential to serve as a tool for the evaluation of operational changes.
Wouter Cijsouw (MSc) – Airport and Network Aware Runway Forecasting Model for Schiphol Airport
Research question: How can improved flight and airport data be incorporated into an airport and network aware runway forecasting model for Schiphol Airport for usage in congestion prevention?
Within Air Traffic Control Netherlands (LVNL), there is currently a desire for more accurate predictions of the runway configurations. Due to the hub role of Schiphol along with the unique layout of its runways, the active take-off and landing runways alter multiple times per day which has large implications on daily operations. Knowing what runways will be in use ahead of time is crucial for preventing unnecessary delay and congestion within the airspace. If discrepancies exist between the forecasted and actual configurations, more flights may arrive within the FIR than can be accommodated for by the runway capacity, causing costly delays and increased fuel usage. Departing flights can also experience delays by such an issue, causing aircraft to remain on the ground for longer than necessary.
Currently, the runway configurations are predicted based on flight plan data, predicted load and meteo data. However, factors such as knock-on delay, load uncertainty modelling and gate occupancy are not yet taken into account and as such could provide an avenue for more accurate predictions. With a model taking this into account, new decision information is provided which can lead to more optimized capacity management along with more streamlined airport and airline hub operations. Within my thesis, I aim to identify the influence of these factors amongst others. After identification, modelling techniques shall be explored in order to find the best candidate for constructing an airport and network aware runway configuration prediction model, which will then be created. Lastly, a performance evaluation will be done on the resulting model.
Tim Honing (MSc) – Assessing Operational Impact of Taxiway Centreline Pushback Positioning at Schiphol using Agent-Based Simulation
As part of the Tug Release Points (TRP) project, LVNL is preparing to introduce
new pushback procedures at Amsterdam Airport Schiphol. Aircraft will be positioned straight on the taxiway centreline rather than diagonally, aiming to reduce fuel consumption and emissions at the stands (VOPs). While environmentally beneficial, this change introduces new operational constraints, particularly when multiple aircraft are aligned behind each other. Under these procedures, simultaneous pushbacks may lead to situations where tug drivers of trailing aircraft cannot exit once the leading aircraft has started its engines, potentially increasing pushback durations. The operational impact of these constraints is currently unclear, creating the need for a quantitative, system-level assessment.
This research aims to evaluate the impact of these new pushback procedures using an Agent-Based Model (ABM) currently under development. The model will be extended with detailed pushback logic to capture these operations, focusing on additional delays, downstream effects, and implications for ground controller workload.
Javier Crespo Núñez (MSc) – Development of a data driven realistic agent based model for current ground surface operations at Schiphol
The development of this tool aims to provide a modular and flexible platform for users to easily develop and simulate Agent Based Models (ABM) for current Airport Surface Operations. Because of the future air traffic growth expectations, many researchers and companies around the globe are focusing on new developments and the optimization of current Air Traffic Management (ATM) processes and procedures. All of these proposed concepts are being tested and validated with different simplistic self-made simulations or expensive and rigid private commercial simulators.
The architecture to be implemented aims to provide an open source simulator framework that could bridge the gap between custom self-made simulations and private commercial simulators. By having a common open-source framework to easily implement and test new research, students, researchers and companies could accelerate their development and better contribute to the challenges faced today in a more standardized and collaborative way.
Furthermore, a realistic and well calibrated model of the current operations is critical to serve as the baseline and first step to test, evaluate, verify and analyze any future or current implementation. The availability of such a model would be incredibly useful to quickly and flexibly test new procedures, human machine interfaces, interactions between the stakeholders, infrastructure sizing analysis, workload, etc.
Amine Nari (MSc) – Modeling Delay Propagation for LVNL’s Decision Support Tool (DST)
Air traffic flow management depends on accurate demand prediciton, yet a major source of error comes from knock-on delays, which are primary delays that propagate to subsequent flights. These cascading effects create significant uncertainty in the European network, affecting both planning and operational decisions. This research focuses on understanding how delays develop and spread over ti
me across flights and connections, using Schiphol Airport as the primary case study. By analysing large-scale delay data, the study aims to identify key patterns and mechanisms driving delay propagation.
The goal is to develop a model that represents how delays evolve throughout the network and can simulate their impact on traffic demand. The model will be integrated into LVNL’s Decision Support Tool (DST) to improve demand prediction and support operational decision making.
Albert Chou (MSc) – Analysis Noise Abatement Procedures Schiphol
Noise Abatement Procedures (NAPs) are specific procedures designed to reduce noise impact in the airport surroundings. At Schiphol Airport, three main NAPs are considered; Noise Abatement Departure Procedures (NADP), Continuous Descent Approaches (CDA), and reduced flap setting descents. These NAPs reduce noise through a reduction in aircraft thrust and drag. However, the implementation of these NAPs is sensitive to aircraft type, aircraft mass, weather, air traffic, and other factors. Therefore, analysing compliance of flight tracks with NAPs is challenging. This research aims to incorporate a data-driven approach to analyse the compliance of flight tracks with NAPs such as NADP, CDA, and reduced flap setting descents through Automatic Dependent Surveillance–Broadcast (ADS-B) and Automatic Dependent Surveillance–Contract (ADS-C) data. By improving NAP detection, this research supports better evaluation of NAP compliance and aircraft noise emissions at Schiphol.
Niels Prins (MSc) – Trajectory-Based Operations in Dutch medium-altitude airspace under mixed ADS-C equipage conditions
Trajectory-Based Operations (TBO) aim to improve the predictability, efficiency, and safety of air traffic management through the use of intent-based trajectory information. With the growing availability of Automatic Dependent Surveillance–Contract (ADS-C) technology, TBO is becoming increasingly feasible. This thesis focuses on developing a trajectory management framework for the Dutch Flight Information Region (FIR) within the FL100–FL260 range, managed by Amsterdam Area Control Centre. Designed for mixed equipage conditions, it will accommodate both ADS-C-equipped and conventional aircraft, managing inbound and outbound traffic while integrating a conflict detection and resolution module. Operating on a time horizon of minutes to tens of minutes, the framework enables continuous trajectory planning and strategic conflict resolution, while retaining tactical intervention capability. Tested with real-world Dutch traffic scenarios, and potentially extended to lower altitude sectors, the framework represents a pragmatic, evolutionary step towards TBO, enhancing planning capabilities while preserving the flexibility required in current operations.