New generation combat aircraft are expected to operate over extended flight envelopes, including flight at high flow angles and rapid maneuvers. Conditions beyond traditional limits are giving rise to nonlinear phenomena, such as flow separation, large scale energetic vortices, fluctuations etc. These phenomena have significant impact on aircraft performance and if not resolved accurately design uncertainties are increased risking lack of performance or even costly redesigns. Thus, accurate modelling of unsteady nonlinear aerodynamics is essential for modern and future combat aircraft.

Unfortunately, conventional modelling tools either lack the required fidelity or they are too expensive. Traditional, highly-efficient approaches are not suitable for modelling nonlinear flow phenomena. Concurrently, high fidelity Computational Fluid Dynamics (CFD) simulations are computationally demanding and therefore impractical in many cases. To enhance aircraft design, it is desirable to obtain models joining the best of these two worlds. A common approach is to distill high fidelity methods into Reduced-Order Models (ROMs) that can accurately approximate unsteady aerodynamics at orders of magnitudes lower costs than CFD. Relevant literature offers many different ROM techniques for varying purposes. Nonetheless, constructing such models is still challenging and currently there is no generally agreed method.

In the current thesis a ROM technique that may be applicable to wider ranges of problems and simpler to construct is sought. The objective is to obtain a model that can promote aircraft control design, performance assessment and structural analysis throughout dynamic maneuvers over complete flight envelopes. The thesis proposes a novel approach utilizing modern, deep convolutional neural networks (CNNs). The devised model consists of three main components. First it incorporates a geometry description constituted by coordinates of an aircraft CFD surface grid. Second, a primary encoding-decoding CNN predicts pressure distribution at the grid points of the geometry. The final and third part of the model is an auxiliary encoding CNN deriving integral aerodynamic loads corresponding to the pressure field predictions of the primary network. The model evaluates and produces instantaneous values. Given a maneuver, it proceeds in timesteps. The predictions of the separate instances are computed directly without the need of subiterations (as it would be the case for CFD simulations).

As a proof of concept, the model is applied to symmetric motions in the vertical plane at fixed Mach number and altitude. The subject of the investigations is the MULDICON configuration of the 251 th Science and Technology Organization work-group of NATO. To fully exploit the advantages of reduced-order modelling, flow characteristics are inferred from a single excitation following an efficient system identification technique using Schroeder sweeps as input signals. The performance of the model is assessed by numerous test cases performed in CFD. First, steady conditions of varying incidence angles are investigated. Second, harmonic pitch and plunge oscillations around different angles of attack at different amplitudes and frequencies are considered. Third, additional test cases of a linear pitch up-down -- and a climbing maneuver are studied.

Considering computational efficiency, the results show robust model performance. GPU-accelerated CNN calculations are conducted roughly 5000 times faster than CFD simulations. The primary network can accurately resolve the pressure distributions over large portions of the geometry. Lower surface predictions are very accurate. However, among certain conditions discrepancies are observable on the upper surface towards the wingtips. Still, the secondary network can predict corresponding aerodynamic forces accurately. In contrast, its moment predictions are sensitive to errors in pressure distributions. Consequently, moment predictions can largely deviate from reference data, especially when nonlinear phenomena are prominent. However, in many cases errors are attributed to insufficient regressor space coverage, i.e.\ certain input combinations are explored poorly by the Schroeder sweeps. Reconsidering system identification practices might mitigate those issues. Nevertheless, the thesis proves the applicability of deep CNNs to the problems at hand. Additionally, the results encourage further investigations.

In the year 2050, global anthropogenic radiative forcing from aircraft emissions are projected to increase significantly. Recent studies have considered climate optimized flight trajectories to be a promising measure to mitigate non-CO2 emissions’ environmental impact, which is highly sensitive to locus and time of emissions. Estimating the maximum mitigation potential from these trajectories requires accounting of air traffic regulations. As designing regulated climate optimal trajectories necessitates solving a hybrid optimal control system with unknown mode sequence and associated switching times, there is a need to build an efficient and systematic control technique. In this thesis, a bi-level optimal control algorithm is proposed for designing climate optimal cruise trajectories, the lower level calculates the optimal switching times and control
inputs of a fixed mode sequence and, the upper level updates the mode sequence with mode insertion which lower the cost locally. The problem for trajectory optimization is formulated here as a hybrid optimal control problem with a switched system and with a variable mode sequence, where step-climb and descent modes are included in the mode sequence. Optimal Control problems for minimizing operating cost and climate cost with fictitious climate cost functions (CCF), varying with altitude, are solved to study the performance of the algorithm. The algorithm is implemented within the Trajectory Optimization Module (TOM) by building a bi-level framework. The framework was validated by solving the operating cost optimal control problem. The maximum error between the cost reduction estimated by the algorithm and the actual cost reduction was found to be less than 15%. With high probability it can be stated that the bi-level framework is able to calculate an optimal mode sequence as the framework allow for zero entry modes in the mode sequence i.e. modes of zero duration. Although, careful consideration is required while selecting a mode for insertion as the framework is highly dependent on the sequence of the set of modes.

Despite a satisfactory performance of the bi-level optimal control technique there are few challenges which limits the scope of this technique. The maximum error was found to increase for optimal control problems with AirClim CCFs. The dependence of the AirClim CCFs on position of the aircraft influences the locus of the trajectory at each flight level. Because of this the the trajectories calculated in each iteration of the framework are found to be inconsistent. A flight trajectory guided by waypoints is proposed as a solution for future studies to handle the inconsistency between trajectories. As future studies are expected to focus on finding optimal mode definitions for designing climate optimal trajectories, the bi-level optimal control algorithm can act as an intermediary tool with which the researchers can systematically investigate cost benefits along the trajectories.

Preface In the wake of the economical crisis of 2008, the shipping industry changed from a very profitable industry to a struggling one, aiming to optimize vessel operations in order to survive. Theories regarding route optimization based on weather and oceanic currents exist, but only few reliable industrial applications can be found. This, together with nowadays global environmental concerns, is where the roots of this project, aiming at developing a route optimization tool for seagoing vessels, based on real-life vessel data, short-term weather forecasts and oceanic currents and monthly averaged sailing conditions can be found. Due to the huge amount of fuel burned by seagoing vessels, achieving just a fraction of fuel savings already results in a significant reduction of global greenhouse gas production. The concept of weather routing is not new, but the results that can be achieved by using it are not widely documented. In order to quantify this, a weather route optimization tool has been developed. The availability of detailed hindcast datasets made it possible to incorporate monthly averaged sailing conditions in the optimization process, influencing the decision on which route to take when weather forecasts are not available anymore. Analysis of different ratios between forecasts, monthly averaged conditions and taking the shortest path to describe the sailing environment, led to the conclusion that forecasts are more reliable than sailing according to the monthly averages or taking the shortest path, as long as these forecasts are available. When no forecasts are available, using monthly averages as reference environment is favored over taking the shortest path. While evaluating randomly selected routes, it became clear that the usage of these monthly averaged sailing conditions can reduce the fuel consumption by 0.59 %, where the total effect of applying weather route optimization is found to be approximately 3.18 %. Due to the limited number of simulations performed and the unstructured nature of the data distribution, the 95 % confidence interval of the expected fuel savings ranges from 2.54 % to 4.02 %. When assuming the achieved savings are approximating reality, application of weather route optimization on the entire CMB fleet, containing close to 100 vessels, leads to a CO2 emission reduction almost 80 thousand metric tonnes per year. This is the result of a fuel consumption reduction of 23.5 thousand tons, which would roughly saves 9.35 million US Dollar in bunker costs.

Aircraft manufacturers are increasingly exploring emission-free flight or emission reduction for larger passenger aircraft. The low energy density of state-of-the-art battery technology limits the application to small, electric, fixed wing aircraft up to a flight time of approximately one hour. To overcome these limits, a combination of fuel cells and batteries to exploit the benefits of battery power density and hydrogen energy density was studied. Current Lithium-Ion battery cells reach approximately 1.6 kW/kg of maximum power density, much higher than fuel cell systems. On the other hand, the energy storage capacity of suitable hydrogen storage methods is much larger than battery cells, the latter have an energy density of 240 Wh/kg.

Because most demonstrated applications are for fixed wing aircraft, the unmanned GeoCopter GC-201 helicopter was used for performance requirements, weight and volume analysis. The study focuses on the preliminary sizing of the powertrain and the optimization of fuel cell and mission profile variables for this vehicle. Helicopter performance modelling, fuel cell static behavior as well as a battery discharge simulation are combined with lower fidelity models for other components.

The study results in a comparison of battery-only and fuel cell-battery configurations through payload-range diagrams, allowing for a quick evaluation of application areas. These mainly show that batteries excel at high payload, low range applications whereas a fuel cell-battery combination shows clear advantages at low payload, longer range applications. Liquid hydrogen will be shown to be comparable to the current micro gas turbine powered rotorcraft, with 400 and 500 km range capabilities respectively. Range capabilities for 300 bar and 700 bar compressed gas tank storage options show 140 and 180 km, with battery-only reaching a maximum range of 80 km.

Deployable morphing aircraft are gaining popularity in the academic and industrial world. Their deployability offer the possibility to be stored and takes less space. This is advantageous in volume limited applications like space explorations, where every cubic centimeter is important. Another field where this aircraft is increasingly used is the military field. Deploying it in the battlefield directly from a carrier aircraft opens endless possibility to the operation of such aircraft. However, mid-air deployment is subjected to several internal and external factors that could lead to the failure of the deployment.

In this study, a method to assess the safety of deployment of a deployable morphing UAV is constructed. To do this, an aircraft test case is taken and a corresponding model of the aircraft is made using the Multibody dynamics approach. This model is then verified and validated by two different methods. First, a comparison of the stability derivatives of the created model and an off-the-shelf aerodynamic solver is performed. Secondly, the response of the created model is compared with actual flight test data, where the test case aircraft performs a maneuver. For both validation methods used in this study, the created model is able to resemble the output from the off-the-shelf aerodynamic solver and the flight test data. The validated model is then used as to test the method developed in this study.

The method developed starts with the definition of a safe deployment of a deployable morphing aircraft, where three different safety concerns are considered. The definition of a safe deployment also helps in deriving different categories of deployment which includes safe and various unsafe deployment depending on what causes the deployment to be unsafe. This method is tested on two different deployment scenarios.

By using the method developed in this study, safety deployment spaces are constructed from the range of input parameters determined for the two different scenarios. It is revealed from this safety deployment space what combination of input parameters is favorable for a safe deployment, and what causes the different unsafe deployments. Unsafe deployments are also categorized to understand which of the safety concern causes the deployment to be unsafe.

Current Ballistic Missile (BM) defence systems intercept an incoming threat in its terminal phase, and to some extend during its coast phase. During the boost phase of a BM, the initial velocity of the BM is low and the hot exhaust plume is easy to spot for infrared sensors, which provides a good opportunity for interception. To do so, the Network Centric Airborne Defense Element (NCADE) is a missile in development, which is to be launched from a 5$^{\text{th}}$ generation fighter aircraft. A tracking algorithm model has already been developed at TNO, which performs the tracking and trajectory prediction of the BM, based on the location measurements performed by the IR sensors of both the aircraft and the missile. Tracking a BM and predicting its trajectory poses a challenge, as the mass, thrust and acceleration cannot be measured directly, resulting in an uncertainty in the trajectory prediction. The NCADE therefore must be able to intercept the BM in its boost phase, considering the uncertainties in the trajectory prediction. The main research goal of this thesis is to develop a guidance algorithm for the NCADE, which plans a trajectory of an air launched missile, intercepting a BM in its boost phase. To do so, the NCADE has been modelled, and the tracking algorithm has been implemented. The actual guidance is performed using trajectory optimisation. 
The NCADE is designed to disable its target by means of kinetic penetration, meaning that there is no explosive warhead present. The missile is derived from the AIM120D AMRAAM, with a similar outer shape and suspension points. The NCADE consists of two stages, where the first stage is equipped with a solid booster for a fast acceleration. Control deflections are provided with aerodynamic surfaces. The second stage, also called Kill Vehicle (KV), is equipped with an IR sensor to determine the location of the target. Some sensor inaccuracy is present due to the amount of pixels used in the sensor. Control inputs on the second stage are performed using monopropellant pulses. Both control inputs and thrust of the KV use monopropellant from the same source, meaning that when the monopropellant tank is depleted, both control deflections and thrust cannot be delivered. To calculate different trajectories of the NCADE, the equations of motion are set up, where the NCADE is modelled as a 3 degrees of freedom point mass. Aerodynamic coefficients are obtained using software applying empirical methods, for which an extended database of projectiles is available. Verification of the equations is performed using a validated generic missile model, made by TNO using Simulink. 

The calculation of the guidance relies on a location of the target in the future. Therefore, a trajectory prediction must be performed, for which the states of the BM must be determined. There are however only position measurements of the BM available, from which a more extended set of states of the BM must be derived. This is performed using an Extended Kalman Filter (EKF), which was developed during an earlier study. The filter initiates with a guess of the states of the BM, and continuously updates those as new readings of the BM become available. Using the Kalman states, a trajectory prediction is performed. The Kalman states require a certain tracking period to converge to the correct values, to be able to calculate usable trajectory predictions. The quality of the tracking prediction is quantified by a score, which is forwarded to the guidance algorithm to be able to take the significant uncertainties in the trajectory prediction into account. The certainty score improves when the tracking duration increases and when the trajectory prediction is nearby in the future. The certainty results are forwarded to the guidance algorithm by means of coefficients of a polynomial.
Due to the complexity of the control system of the NCADE and the uncertain target trajectory, trajectory optimisation is applied in the guidance algorithm. Trajectory optimisation aims to decrease the defined performance index, which is in this case the divert cone minus the uncertainty ellipse of the trajectory prediction, to maximise the probability for interception. The divert cone of the NCADE is a volume which the missile is able to reach on a certain time, given its states and reserve fuel. The divert cone is calculated using a separate shooting optimisation algorithm, which maximises the distance in three ENU frame directions. To maximise the probability of interception, a shooting method is applied, which uses candidate solutions in the form of functions describing the control input, to calculate the performance index. Using constraints, the missile is directed towards an interception point. Constraints are also applied to bound the magnitude of the controls, and at the trajectory itself to remain physical feasible.
To investigate the behaviour of the guidance algorithm, simulations of interceptions of the NCADE have been performed on a modelled Scud BM, using a range of launch locations and tracking settings. The optimum results are presented in control deflection functions of the NCADE, which achieve the flight with the minimised performance index. When only the tracking uncertainty is minimised, flight time is minimised, as the prediction becomes less reliable when a longer trajectory prediction is performed. When only the size of the divert cone is to be maximised, the propellant of the sustainer, used for control and propulsion, is saved to increase the divert cone. Because of this, the altitude of the flight is increased, and $t_{f}$ must become larger, because less monopropellant is applied to increase the velocity at the beginning of the sustain phase. The optimum solution is a compromise between the divert cone size and time to flight. As the duration of the tracking time increases, the target trajectory prediction becomes more reliable, so the maximisation of the divert cone becomes more prominent. However, this results in the maximum range to decrease, since there is less time for interception, and the altitude of the target has increased. When the launch location is positioned further from the target, the reduction of time to flight becomes more prominent and the divert cone decreases. In conclusion, the optimisation routine performs the compromise between the amount of reserve propellant available, and the uncertainty of the trajectory prediction. 

With increasing fuel prices, airlines are searching for means to reduce fuel consumption. Due to the limited variables that operators can influence of an aircraft, they are left with only operational changes, such as center of gravity positioning. By shifting the center of gravity aft, achieved by loading heavy cargo and baggage in the rear, trim drag will decrease. Despite the relation between the center of gravity and the trim drag, and therefore fuel consumption being known, no literature exists on its quantification in practice. As such, at the request of KLM Loadcontrol, a numerical model was developed to investigate the effect of the center of gravity on fuel burn. Due to the complexity, the results were used to derive a function per aircraft, route and season. Defining the zero fuel weight and the center of gravity location for that condition will enable users to determine the effect.

The flow field subjected to the influence of the helicopter rotor is characterized by its three-dimensional pattern and unsteadiness. The accurate modeling of the flow around the rotor blades addressed by Computational Fluid Dynamics (CFD) simulations is associated with high computational costs. The complexity of the analysis can be reduced by means of simplified methods such as the actuator disk approach, where the rotor is modeled as a zero-thickness porous surface.

The CFD solver TAU developed at the German Aerospace Center (DLR) includes among its features an actuator disk module which transmits to the flow field prescribed time-averaged load distributions both in axial and tangential directions by means of pressure and tangential velocity jumps. The computation of these loads can be achieved by using the Blade Element Analysis Tool (BEAT), a developed rotor code based on the blade element theory. In addition, since it is considered that changes in blade motion about the feathering bearing and flapping hinge induce variations in the aerodynamic loads acting on the blades and vice versa, the loads need to be calculated under trimmed or equilibrium conditions.

The coupling between BEAT and the TAU actuator disk is defined in a way that the velocity captured at the grid points of the actuator disk surface after each simulation performed in TAU is transferred to BEAT, which computes an updated aerodynamic load distribution. The performance of this approach is tested for an isolated rotor configuration in hovering and forward flight conditions. In hovering flight, the convergence of the CFD flow simulations towards the steady state solution is not satisfactory due to the stiffness of the compressible Navier-Stokes equations at low Mach numbers. Furthermore, reverse flow regions are determined by TAU at the inner and outer boundaries of the actuator disk. The recirculation flow entails high gradients in angle of attack between neighboring blade sectional elements, which yields to the unstable formation of new reverse flow regions. Nevertheless, in forward flight conditions the performance of the flow solver is robust and convergent solutions can be obtained. Moreover, as the flight speed is increased, the shed vorticity is displaced more quickly outside the rotor disk and, hence, its associated effects on the performance of the rotor are diminished.

The accuracy of the coupling approach is validated by comparing the computed results with those measured in a wind tunnel test campaign. The found differences in pitch control angles are assigned to the fact that the blade elastic deformations are neglected in the developed method. This statement constitutes the baseline to be developed for future work.

Finally, the reduction in computation time required by the coupling approach with respect to other more accurate methods enhances the idea of further developments. Therefore, the developed method can be regarded as a suitable strategy to tackle the problem in forward flight conditions in cases where high fidelity results are not needed, such as in the preliminary design stages.

Helicopters are complex and expensive aircraft with a level of technology that is immature compared to fixed- wing counterparts. Helicopters suffer from vibratory loads stemming from the main rotor and exhibit control and stability problems in the low-speed flight regime. Operating a helicopter near the limits of its flight envelope may result in unacceptable high structural loads which adversely affects wear and tear of drive train components. Conservative safety regulations lead to high operating cost where a significant part can be attributed to maintenance. Manufacturers and operators therefore strive to make helicopters more capable and reliable in an effort to reduce operating cost. Structural load alleviation offers an attractive option to achieve this goal by reducing component damage accumulation and subsequent required maintenance.

This thesis investigates structural load alleviation in the tail rotor drive train of the UH-60 Black Hawk. The Black Hawk provides a compelling case for load alleviation research because of its ever growing operational weight and resulting increase of drive train load levels. Furthermore, the lifetime of the UH-60 is to be extended so that it will fly for many years to come. Current research and applications of rotorcraft structural load alleviation focus on the main rotor but less attention is given to tail rotor drive train components. This project seeks to address this knowledge gap by investigating manoeuvres that result in critical dynamic loads in the UH-60 tail rotor drive train. A survey of pertinent literature and interviews with helicopter pilots indicate that pedal inputs for left-hand turns in hover lead to high dynamic loads in the UH-60 tail rotor drive train.

A flight simulation model is constructed that offers the novel capability to predict dynamic loads in tail rotor drive shafts. This model consists of an available high fidelity engine model and existing rotor models coupled by a multi body dynamics tail rotor drive train model with properties that are based on component measurements and CAD drawings. Experiments are conducted to determine the relation between manoeuvre aggressiveness and dynamic loads in tail rotor drive shafts. Based on the results a manoeuvre load alleviation control strategy is devised to reduce dynamic loads while ensuring applicable Level 1 handling quality requirements. Application of this control strategy will decrease dynamic loads during left-hand yaw manoeuvres in hover. Furthermore, the results highlight what reduction in loads can be achieved for varying levels of manoeuvre aggressiveness. These findings may aid in the design of flight control systems that incorporate tail rotor drive train load alleviation objectives.

Looking at performance prediction of small coaxial rotorcraft, it was found that there are no fast methods available for designers. This research was aimed at using a blade element method in combination with the momentum theory to quickly predict the performance at small coaxial rotorcraft. These methods are successfully applied in larger rotorcraft. It will therefore be of interest to see how these methods perform when the aerodynamics changes due to scaling. Especially the Reynolds number effects are expected to influence and potentially limit the application of the modelling methods.

The new developed model was tested on the full-scale Kamov 32 helicopter as well as two small Unmanned Aerial Vehicles. These are the commercial available Walkera Lama and the Guardian Angle, which was developed by undergraduate students during a design synthesis exercise. The results show a successful implementation of the calculation methods, with some interesting insight in the limits imposed by them.

During aircraft design,multiple tools are utilised to inspect the performance of the configuration. As the design matures, higher fidelity analyses are conducted to predict the flight dynamics of the aircraft. These analyses are conducted by using semi-empirical relations, numerically analysing flow behaviour, conducting wind-tunnel tests and performing scaled test flights. However, Semi-empirical relations might not hold for next generation aircraft and wind tunnel testing and scaled test flights are extensive and are also prone to accuracy issues. A best of both worlds can be found in numerical analysis. However, an increase in flow fidelity modelling comes with an increase in computational cost. Besides, complete analysis of all possible manoeuvres of a design increases the number of computations significantly. Current methods cope with this issue by using flight dynamics models based on so called stability derivatives, instantaneous values which couple flight state parameters to aerodynamic loads to predict aircraft flight dynamics. However, these models do not take into account time dependency. Therefore, these methods do not accurately predict the flight dynamics of agile aircraft, such as unmanned combat aerial vehicles, undergoing rapid manoeuvres where unsteadiness dominates flow behaviour. This conventional reduced-order modelling method, in which samples of the full-order model are taken in the form of stability derivatives, causes design iterations to be analysed inaccurately. The objective of this report is to investigate reduced-order modelling for flight dynamics prediction, thereby comparing conventional techniques to a method which does take into account unsteadiness in flow behaviour.
The method investigated is based on indicial step response functions, which are samples in the form of unsteady aerodynamic flow behaviour functions of the full-order model. The idea is that once these samples are known, any flight manoeuvre can be analysed within minutes. Research found in literature has assessed some of the capabilities and limitations of this method, but not yet applied this to flight dynamics prediction. The research described within this report will address this gap by using two test cases. The first testcase is used to assess the assumptions made in literature, on aerodynamics loads modelling, by applying the method on a two-dimensional airfoil in subsonic flow conditions. It was found that the indicial step response functions are indeed representing the full-order model, thereby taking into account unsteady flow behaviour in aerodynamic loads prediction. In longitudinal motions, the angle of attack and pitch rate effect need to be taken into account to predict lift, drag and pitching moments. Multiple frequencies of the same manoeuvre can be analysed within minutes once the samples are calculated. Results show that the accuracy of the predictions becomes a trade-off issue between samples calculated and accuracy required. The second testcase is used to apply the indicial response functions to flight dynamics prediction of an agile
unmanned bomber aircraft undergoing fast manoeuvres. A longitudinal-directional climbing manoeuvre was calculated by developing a flight dynamics model based on stability derivatives. The flow behaviour encountered during this manoeuvre was analysed to include highly unsteady and non-linear phenomena (e.g. vortices and flow separation) at higher angles of attack. By comparing the results of themethod under investigation to the full-order solutions, it was shown that aerodynamic flight dynamics predictions were accurate in capturing unsteady behaviour and weak non-linear flow behaviour. However, the samples proved to be inaccurate in representing behaviour in highly non-linear regions. Concluding, this means that indicial step response functions provide more accurate flight dynamics predictions than conventional stability derivatives in representing unsteady flow behaviour. The accuracy of the predictions are highly dependent on the samples chosen. Several samples suffice to predict the unsteady behaviour for linear and weak non-linear flow regions of the flightmanoeuvre. If surrogate modelling is applied, the method can become more computational efficient than conducting multiple full-order time-marching numerical calculations. It is recommended that more research is performed on indicial step response functions
in capturing highly non-linear flow behaviour, as the research showed that the size of the samples affects the flow behaviour representation.

Aircraft design methodologies have been significantly developing from the past few years with the advancements in knowledge based techniques. These methods enable the storage of design knowledge and rules, and reuse them to create different types of designs, thus preventing the designer to perform repetitive tasks. Tasks such as parametric modelling of components, such as the aircraft wing can be automated by storing the modelling processes and the design rules in a knowledge base. With this process, variants of the wing with different geometric parameters can then be generated in a short duration by simply varying certain top-level requirements. It is necessary to extend these design techniques to model aircraft systems in the conceptual design stage. This, not only decreases the time of design realisation but also presents a scope to assess the effects of various inter-dependencies due to systems and make appropriate changes, in the early stages of aircraft design. Developing and demonstrating a framework which aids to assess the influence of the wing subsystems, namely the flight control actuators, fuel tanks and anti-ice elements; on the aircraft design and performance in the conceptual design stage is the aim of the thesis.

This thesis presents a combination of physics based and knowledge based design methodologies to size the wing subsystems and position them in the airframe. Consequently, the methods are integrated into the conceptual aircraft design process to enable multidisciplinary design with supporting domains. The methods are aimed to aid the design of conventional systems architectures and More Electric Aircraft (MEA) systems architectures as well. With these methodologies, the Systems Model Generator (SMG) application is developed in Python to facilitate semi-automatic wing subsystems sizing and orientation in the airframe based on top-level aircraft requirements, initial aircraft design parameters and system specific parameters. The subsystem models generated with the proposed methodology for short-medium range civil transport aircraft are verified and validated as well. Knowledge based systems and subsystems selection are implemented to facilitate semi-automated systems, subsystems and architecture selection, based on the aircraft configuration and systems specific requirements. Methods for automatic iterative fuel tanks sizing and intersection detection are implemented to further reduce the overall design time and make the tool more suitable for integrated sizing.

With the multidisciplinary design framework, the conceptual parametric models, volume, mass, power consumption and position of the subsystems in the airframe are generated and propagated in the conceptual aircraft design stage; thus bridging the conceptual and the preliminary design stages. In the proposed framework, the domains of aircraft design generation, systems selection and sizing, subsystems selection and sizing, engine sizing and mission simulation are considered for the multidisciplinary design process. The domains are integrated with the DLR CPACS-RCE framework.

A case study to demonstrate the process of integrated parametric subsystems sizing of the aircraft, with the proposed framework is presented. The aim of this case study is to assess the influence of the MEA systems architecture relative to the conventional systems architecture for a short-medium range transport aircraft, similar to the Airbus A320-200. In this case study, the quantitative influence of the subsystems' parameters on the aircraft design and performance parameters is determined and analysed. The subsystems' parameters constitute the mass, power consumption, volume and location of the subsystems in the airframe and the aircraft design parameters constitute the aircraft masses such as the overall empty mass and the fuel mass for the mission. The generation and propagation of the design and performance parameters of the aircraft through each domain of the framework are presented and analysed as well with the case study. In this case study, it is observed that the MEA systems architecture results in a lower mission fuel mass relative to the conventional systems architecture by nearly 2.3\%. Furthermore, these results are compared with literature and observed to be in the similar range of 2-7\%. Thus, the validated aircraft design framework presented in this thesis enables to substantially increases and propagate the design knowledge of aircraft systems, in the early design stages.

The solution space for conflicts between aircraft consists of velocity, heading and altitude changes. In the current design of the air traffic controller workspace the instantaneous values for velocity, heading and altitude can all be found in the aircraft labels on the radar, however the heading and velocity can also be derived from the direction and speed of the aircraft on the radar display. Since the radar is a top view of the traffic situation, no means of deriving the altitude other than the aircraft labels can be found. Previous attempts to present the altitude domain in the radar display showed room for improvement. These display designs have been analysed and information gathered from them is used to create a new ecological user interface. The aim of this interface is to improve the support in conflict detection and resolution for air traffic controllers by representing the situation in the altitude domain. A preliminary feasibility test was performed from which it can be concluded that the altitude display has potential to improve safety in air traffic control and to reduce the complexity within the sector, but that some more attention should be put on making sure the aircraft leave the sector within the constraints linked to their exit waypoint. The subjective data from the questionnaire at the end of the feasibility test showed that the users felt that generally the display was easy to use.

Parashuttle is a project started by Lodewijk-Jan Doensen, a general practitioner and aerospace
enthusiast. Inspired by his own vision of improved powered parachutes he built a closed-cockpit
paraplane for one person, which unfortunately never flew.