A novel security checkpoint concept has been proposed to address the continuing growth in passenger traffic that airports are experiencing globally. The new security checkpoint intends to employ Automated Guided Vehicles (AGVs) instead of conveyor belts for baggage tray transportation. However, the new concept poses new challenges to the classic Multi-Agent Path Finding (MAPF) problem due to its small environment and high agent density. The AGV fleet will thus have to effectively coordinate their paths to avoid gridlocks within the crowded security checkpoint environment. Firstly, this paper presents a detailed Agent-Based Model (ABM) to accurately represent the new automated security checkpoint and estimate its passenger throughput. Secondly, the paper presents a new MAPF algorithm for the AGV fleet: the Windowed Hierarchical Idle-Push (WHIP) algorithm. WHIP is a prioritised MAPF solver that uses Push-operations to efficiently resolve the bottlenecks of the automated security checkpoint, avoiding gridlock even at very high agent densities. Experimentally, WHIP achieves path efficiencies 5 percentage points higher than leading prioritised MAPF algorithms, while requiring only half the computational runtime. Using the WHIP algorithm, the automated security checkpoint is capable of achieving an 18% increase in passenger throughput with respect to existing security checkpoints using conveyor belts.

The aviation industry's shift towards sustainable propulsion, notably hydrogen-electric propulsion (HEPS), underscores the need to grasp its effects on flight procedures and pilot duties. This research aims to develop a HEPS engine powertrain model for evaluating its influence on flight procedures, especially during critical phases like go-around for regional turboprop aircraft. The HEPS engine powertrain model was constructed by selecting powertrain components important for modelling based on their relevance to important HEPS system outputs like the thrust generation, battery discharge, and fuel left in the tank. Subsystems such as the fuel cell system, battery, motor, propeller etc. were modelled using MATLAB/Simulink and integrated to form a holistic representation of the HEPS engine. The model underwent testing through a simulated go-around mission, followed by an analysis of its operational envelope, which unveiled significant parameters influencing system behaviour during such manoeuvres. Among the critical parameters identified were the initial battery state of charge (SoC), nominal battery capacity, and propeller efficiency. Thrust generation limitations were identified for heavier aircraft configurations, as well as the relatively low impact of go-around speed on the system's power path. For a HEPS-based Dash 8 Q-300 aircraft with a mass of 38,000 pounds and a go-around speed of 96 knots, the State of Charge (SoC) of a 200Ah battery should be at least 23% for a successful go-around manoeuvre. Using appropriate parameters, the presented model framework assists in identifying such constraints and delineating flight procedural changes for future regional aircraft. The study highlights areas for model enhancement, including better thermal management system models for the fuel cell stack and battery, and improved motor-propeller models. This research contributes to sustainable aviation, guiding the integration of HEPS into flight operations for enhanced efficiency and eco-friendly air travel.

The rise in high-speed quadrotor applications demands aerodynamic models that explain the flight characteristics at these broader flight regimes. For developing these models using system identification methods, having information-rich data at these flight conditions is crucial. While there have been sufficient works in the input design for identification procedures in quadrotors, there are limited guidelines for high-speed flights. This work focuses on two key contributions to aid the high-speed quadrotor model identification process. First, an automated flight testing pipeline using various software tools has been developed to support the iterative input design process. Second, various inputs such as position tracking, trajectory tracking, and attitude injection while trajectory tracking have been designed. The goal of these input designs was to push the quadrotor velocities while trying to maximize the excitation in forces and moments. The HITL simulation tool, being part of the testing pipeline, was used to iteratively design and verify inputs before actual flight tests. Finally, automated high-speed flight tests of the designed inputs were conducted at the Cyberzoo indoor facility, reaching maximum velocities of up to 7 m/s. The results show that attitude injection while trajectory tracking provides a method to excite forces and moments during high-speed flights. This work is an initial attempt at understanding the effects of input design at high-speed flights with the goal of obtaining data for quadrotor model identification. The methodology and pipeline developed here serve as a platform to build and explore various other identification inputs with the scope to push the quadrotor flight speeds even further.

The Flying-V aircraft could revolutionize commercial aviation, boasting a potential 25% increase in aerodynamic efficiency. Due to inherent design limitations regarding static stability, the need for a proper Flight Control System (FCS) is essential for the development of the aircraft. The concept of Hybrid Incremental Nonlinear Dynamic Inversion (INDI) was introduced to mitigate the insufficient stability margin encountered in existing sensor-based INDI systems due to sensor time delays, to achieve Level 1 Handling Qualities (HQ). Furthermore, the research introduces an exponential potential function-based command limiting Flight Envelope Protection (FEP) to enhance safety compared to the currently implemented linear-based FEP. The study compares and evaluates the effectiveness of the updated system under various flight conditions and parametric uncertainties. Results show improved stability margins and a safer FEP. However, additional research is required into actuator saturation and control allocation issues during the approach condition and to enhance fault tolerance.

The Flying-V, a novel aircraft design developed at Delft University of Technology, presents a revolutionary flying wing transport aircraft with a remarkable 20% reduction in energy consumption compared to traditional twin-aisle planes.
This thesis project delves into the study of optimizing the Flying-V's landing performance, emphasizing the necessity of reducing pitch attitude. High-lift devices, particularly split flaps, were explored for this purpose. Wind tunnel tests were carried out on a scaled-down model of the half- wing, in the Open Jet Facility of TU Delft. The tests yielded two successful flap configurations— a single-flap and a double-flap.
These were analyzed further using a flight performance tool to make a final selection on the flap configuration. The single-flap option proved effective in reducing landing pitch attitude by 3 degrees, significantly lowering obscured segment by 20 to 30 m and the pilot's eye altitude by 1 m. This is a quite desirable outcome for the landing performance of the Flying-V which significantly improves pilot’s vision.

Understanding individual differences in manual control cybernetics plays a principal role in personalizing human-machine systems. While much of the work in cybernetics utilizes models for the average controller, individualized models have also been explored, albeit constrained by data availability and the effectiveness of identification techniques. It has previously been theorized that human controller behavior may be defined by a cost function that the controller minimizes for a given control task. This cost function comprises weighted performance and effort terms, and the weightings have been connected to cybernetic models before, but not on an individualized basis. A proposed connection is through the equalization component of the cybernetic model, which has also been outlined as an indicator of individual differences. This claim was reinforced by the analysis of previously collected experiment data in this paper: Across three independent experiments, the equalization parameters, on average, showed 33.84% higher variation than the others and a greater impact on the cost function. Thus, this paper presents a human-controller-cost-function-centered approach to predict and generate individualized sets of cybernetic parameters. Individual cost function weightings were determined using the identified equalization parameters from earlier human-in-the-loop experiments. This process exhibited clear groupings in participants, as clusters of participants with similar equalization were not identified adequately. Individual cost function weightings were then employed to predict full sets of cybernetic parameters. The results indicated that the utilized cost function is incapable of reflecting the physical limitations of the human controller, as these parameters (time delay, neuromuscular natural frequency, and neuromuscular damping coefficient) showed 56.06%, -94.43%, and -170.34% deviation compared to the experimental values. Hence, a hybrid cybernetic data augmentation method was devised, yielding signal values within 15% of experimental data.

Increasing runway capacity is a key objective for many airports worldwide, including Schiphol Airport. One of the restricting factors that has become more prevalent throughout the years lies in the task load of the Air Traffic Ground Controllers. To overcome this limiting factor, it becomes essential to mitigate this high task load. This study proposes a methodology for estimating ground controller task load at Schiphol Airport, which is used for analyzing the effectiveness of a mitigation method employed at Schiphol Airport, namely the splitting of the combined North-Centre sector. To achieve this, the research adopts the concept of task load estimation via dynamic density modelling, which has primarily been explored when applying it to the airborne segments of Air Traffic Management. The task load estimation models for the different ground control sectors are developed through a multi-phase approach encompassing data collection, candidate independent variable selection, a double correlation analysis, and a sequential search regression for model building. The research successfully constructed task load estimation models for four out of the five analysed sectors. Furthermore, two of these models are employed in a case study to evaluate the task load reduction strategy. The findings highlight that splitting the combined North-Centre sector to alleviate the task load experienced by the North sector ground controller can be an effective mitigation strategy, particularly when the Centre sector experiences a significant level of traffic load.

Autonomous vehicles are becoming increasingly prevalent in society, but the transition from active driver to passive passenger is known to increase the risk and severity of motion sickness. Motion anticipation is a critical factor in this difference, and visual information is known to be a major contributor to motion anticipation. However, the underlying mechanisms of how visual information influences motion sickness remain largely unknown. This study aims to investigate the effect of visual translation on motion sickness development. To accomplish this, a proposal was made to extend an existing motion sickness prediction model with visual translational components. A human-out-of-the-loop experiment was conducted in a moving-base simulator to test the proposed model's reliability and determine whether visual translation influences motion sickness. The experiment simulated an urban ride that featured repetitive accelerating and breaking maneuvers on a straight road. Eighteen participants were subjected to three different visual conditions that varied in the amount of global optical flow, while the simulator's motion was identical. The results suggest that congruent visual translation may lead to a minor, non-significant reduction of motion sickness, while the amount of optical flow does not seem to affect it. The proposed motion sickness model was able to predict a slight decrease in motion sickness for conditions with visual optical flow, as demonstrated by the experiment. Nonetheless, it is still debatable whether congruent visual translation may influence the onset and severity of motion sickness, as the results of this study could not confirm this.

The Delft University of Technology (’TU Delft’) developed a real-time distributed system for scientific and educational purposes. Because of the high level of expertise required to learn from- and work in a real-time environment, TU Delft created a middleware layer, DUECA (Delft University Environment for Communication and Activation), and a simulation-specific addition framework: DUSIME (Delft University SIMulation Environment). A common practice is embedding the numerical optimization tool in an aircraft model and retrieving the starting conditions, referred to as the initial trim set. Setting up such an embedded tool for every aircraft model is very labor-intensive. For over 20 years, these issues have limited the overall user experience in DUECA. Hence, the research created an independent, generic, User-commanded, Sequential Quadratic Program (SQP) module capable of solving the aircraft trim problem in DUECA. The trim module works by a user selecting a desired steady-state aircraft trajectory through a Graphic User Interface (GUI) and then commands the trim module to search for the set of initial trim conditions. The advised flight trajectory found so far by minimizing the DASMAT trim problem are the straight-and-level descending, pull-up, and turning flight. The calculated initial trim sets allow the starting up of an aircraft simulation in a steady-state, stable enough such that a pilot can take over manual control.

This thesis is performed with the aim to investigate whether split flaps can be a feasible solution for increasing the Flying V directional control power. In order to do so, a set of wind tunnel experiments have been concluded with a 4.6% half wing model in the Open-Jet-Facility at the Delft University of Technology. Here, several split flap geometries have been tested on the model outboard wing section to fully establish their behaviour in terms of yaw and other parameters of interest. Additionally, calculations have been performed to provide an adequate split flap design for certification of the lateral-directional specifications from CS-25.

From the wind tunnel experiments, it was found that split flaps on the outboard wing section can effectively increase the directional control power over angles of attack between 0 and 30 degrees. However, yaw control is lost when over negative angles of attack due to lower wing stall. The maximum decrease in split flap effectiveness over positive angles of attack is found around 17.5 degrees, where a leading edge vortex is present over the outboard wing. This decreases pressure over the upper split flap, resulting in a effectiveness decrease of around 41%. As the effectiveness does not decrease further, split flaps can be continuously effective at higher angles of attack when compared to the winglet rudders. The low pressure on the upper flap also causes large adverse coupled moments in pitch and roll. The effect of split flaps on the yawing moment is found to be linear with deflection angle, where their effect on other aerodynamic properties is found to be more non-linear.

The deflection of outboard split flaps do not have a significant interference effect on rudder yaw power, but can have some interference effects on adjacent main wing control surfaces. Differential deflection between the upper and lower flap has been shown to potentially decrease coupling in pitch and roll. The split flaps can also be globally rotated trailing edge down to mitigate adverse coupled moments while beneficially increasing the total created yaw.

From trim calculations, it was found that a maximum additional yaw coefficient of 2.4113e-3 has to be provided by the split flaps. Designs with a maximum deflection angle above 30 degrees are deemed feasible, as this would maximally require only the replacement of the current CS3 surfaces. When a maximum deflection of 60 degrees is set by the designer, a sub-scale split flap width of 111.87 mm is needed, which translates to a full-scale split flap of 2.431 m. Based on the sensitivity analysis and projected Reynolds effects, this is considered a conservative design for the full-scale Flying V. At 0 degrees angle of attack, the recommended geometry is projected to increase the maximum directional control power of the Flying V by 38.1%. At 27.5 degrees, the maximum directional control power can even be increased by 85.5%. Both increases come at the cost of a significant drag penalty.

This project investigates the use of Augmented Reality (AR) in the context of research flight simulators to increase their visual fidelity in rotary-wing applications. The field of view of existing research simulators is often designed after fixed-wing aircraft and can be largely inferior to what is required to simulate helicopters. In particular, visibility downward and to the far side of the cockpit is limited, reducing the field of view of the outside environment available to the pilot. This can be potentially corrected by means of AR goggles adding virtual chin and side windows, supplementing those present in the simulator’s cabin. The visual system of the SIMONA Research Simulator (SRS) was complemented with AR goggles generating additional outside visuals, and this prototype was tested in a human-inthe-loop experiment where flight performance, workload and motion sickness parameters were evaluated in a precision piloting task, with and without the AR visuals. Results confirmed that the prototype was functionally working, with the selected piloting task having been completed both with and without the added AR visuals. However, further analysis found no significant effects of the AR visuals’ presence on flight performance, workload and motion sickness. It was concluded that the high levels of noise found in the data were caused by a mismatch between the piloting task and the participants population.

Participant feedback in previous research indicates a need for pilot training to handle non-routine situations with automation surprises. Therefore, we tested the effectiveness of using active problem solving during training on subsequent performance while dealing with automation surprises. We simulated a glass cockpit of a general aviation aircraft in a full motion flight simulator. An experimental group of private pilots (n = 10) was trained to actively diagnose and solve problems related to the autopilot, without foreknowledge of the training scenario. A control group (n = 10) received the same training scenarios with foreknowledge. The effectiveness of these pilots in dealing with both new and trained automation surprises was compared between groups. It was expected that the experimental group would be more effective in dealing with the new automation surprises, whereas the control group would be more effective in dealing with the repeated automation surprises. The experimental group indeed responded somewhat faster to the new automation surprises and were on average able to maintain the highest level of automation for a longer time than the control group. The opposite is true for the repeated automation surprises, where the control group was somewhat more effective in dealing with the automation surprises. Although these differences were of medium effect sizes (Cohens d = 0.5), they were not significant. Thus, the training approach taken in this study may need to be further enhanced and tested with more participants in order to have a significant effect.

The Eigenmode Distortion (EMD) analysis is a novel method for objective evaluation of simulator motion cueing fidelity, developed at Delft University of Technology. It expresses the distortions of the perceived motion cues in terms of the dynamic modes of a linear model of the vehicle and has been applied to assess rotorcraft simulations. This thesis presents the adaptation of EMD for fixed wing aircraft, including performing the analysis at the pilot station instead of the centre of gravity. The method is applied to a combined linear model of a Cessna Citation 500 aircraft and the Classical Washout Algorithm (CWA). EMD is compared to the current state-of-the-art objective method, the Objective Motion Cueing Test (OMCT), which does not consider the dynamics of the simulated vehicle in its analysis. The two methods show different results in their cueing fidelity assessment of four CWA configurations. An experiment with six pilots is performed in the SIMONA Research Simulator to test the capability of EMD and OMCT to predict the cueing fidelity as perceived by pilots. The subjects perform pairwise comparisons between the four CWA configurations by exciting the short period dynamics of the aircraft. Results indicate that preferences vary considerably between pilots, causing both EMD and OMCT to show poor, but similar, predictive capabilities.

The two performance areas “security” and “efficiency” in airport security operations cannot be analyzed apart from each other, since influencing one has a large impact on the other. In this research agent-based modelling is used to analyze dynamic relations and trade-offs between security and efficiency within airport security operations. Detailed decision making models and theories are used to model autonomous and diverse agents and to place them in a dynamic airport security environment. Results of experiments with the model are put in context of trade-off theories and a link with practice is made by comparing results with a real airport.