This thesis addresses the critical issue of underestimated wake effects between neighboring windparks by developing efficient long-distance wind farm flow models using Convolutional NeuralNetworks (CNNs). The study compares three wake deficit models (Jensen, Bastankhah, andTurbOPark) and four neural network architectures (Convolutional Autoencoder (CAE), U-Net,CAE/MLP, and U-Net/MLP) to improve long-distance wake predictions.A novel method for random wind park layout generation was developed, simulating diversescenarios up to 768 rotor diameters downstream. Each wake model dataset comprised 1000simulations, split 80/20 for training and testing. Results demonstrate that all neural net-works effectively simulate wake datasets, with U-Net and U-Net/MLP consistently outperform-ing CAE approaches. Mean Absolute Errors (MAE) range from 4.75 × 10−4 m/s (Jensen) to1.44 × 10−2 m/s (TurbOPark). The U-Net/MLP model also successfully predicted turbulenceintensity, achieving MAEs between 1.30 × 10−4 (Frandsen model) and 2.21 × 10−4 (Crespo-Hernández model).Crucially, neural networks significantly outperform traditional engineering models in compu-tational efficiency. While engineering models’ computational time scales linearly with turbinecount, neural networks maintain a constant execution time of approximately 3 ms, regardlessof wind park size. This breakthrough enables rapid assessment of large-scale wind farm layoutsand performance optimization.

Numerous dynamic stall models exist to improve aerodynamic modelling. As such, they play an integral part in aeroelastic analyses. In numerous publications, their qualitative damping effect on stall-induced instabilities of wind turbine blades compared to using quasi-steady aerodynamics has been proven. However, often different dynamic stall models are used without consideration of quantitative differences between aeroelastic predictions. Thus, the goal of this thesis is to quantify the damping effect of dynamic stall models on stall-induced instabilities. A model used in HAWC2, openFAST, one developed by IAG, and one unpublished model are compared amongst each other and in comparison to predictions with quasi-steady aerodynamics. A typical blade section at 75 % span of the DTU 10 MW reference wind turbine is modelled. The blade the section belongs to is facing vertically up at a pitch angle of 90° in parked conditions. The inflow ranges from 5 m/s to 50 m/s with yaw-misalignment angles from -25° to 25°. In comparison to using quasi-steady aerodynamics, the dynamic stall model from openFAST reduces the amplitude of edgewise limit cycle oscillations from maxima of 22.5 m to 7.2 m. The model from HAWC2 further reduces the maxima to 5.4 m. No edgewise limit cycle oscillations occur using the IAG or unpublished model. Instabilities other than limit cycle oscillations are not predicted. Analyses of the time series of dynamic stall parameters, dynamic lift, drag, and moment power, as well as the unsteady force and moment coefficient loops and aeroelastic damping ratios, did not trivially explain the models' different predictions.

The purpose of this study has been to develop an aerodynamic load model for the energy harvesting (traction) phase of leading-edge inflatable (LEI) kites operating in an airborne wind energy (AWE) context. The load model stems from multivariate polynomial regression analyses expressing the airfoil lift, drag and moment coefficients as polynomial functions of the angle-of-attack and 2D non-dimensional (relative to the chord length) shape parameters: non-dimensional tube diameter, maximum camber magnitude and chordwise position of maximum camber. The regression analyses relied on numerical data attained from computational fluid dynamics (CFD) simulations of the 2D flow fields around parameterised LEI wing profiles. The RANS equations, closed by the k-ω SST turbulence model, have been used for this purpose. The parameterisation and subsequent geometric construction of LEI wing profiles has been a key aspect of this study. As such, the effects of the shape parameters on the flow field have been assessed.

In light of the energy transition to a fossil-free energy system, Europe is experiencing a colossal shift toward renewable energy generation. To facilitate the rapidly growing demand for clean energy, new technologies, and resources are being investigated. Airborne wind energy (AWE) and floating wind turbines have the potential to unlock untapped wind resource potential and contribute to the balancing of the system in unique ways. So far, the techno-economic potential of both technologies has only been investigated at small scale, while the most significant benefits will likely play out on a system scale. Demonstrating the economic feasibility and additional benefits of emerging technologies in an energy system context is vital to accelerate political traction and funding.
This research aimed to find the main system-level trade-offs involved with integrating AWE and floating wind turbines in a highly-renewable future energy system. To do so, a modelling workflow was developed that consists of future costs and performance estimation, wind resource assessment and integration into a high-resolution large-scale energy system cost-optimization model, based on the Calliope modelling framework. The investigated region contains 10 countries in the North Sea region. The wind resource and system balancing are hourly-resolved. Key findings include:
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Onshore AWE significantly outperforms onshore wind turbines due to higher wind resource availability.
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The main limiting factor in large-scale onshore AWE deployment is the spatial energy density.
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Offshore AWE shows highly identical performance compared to offshore wind alternatives.
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Deployment of offshore AWE is mainly cost driven.
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Floating wind turbines demonstrate great potential because of the high capacity factors that can be achieved in high wind resource areas where conventional offshore wind is not technically feasible.
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Offshore wind potential in general strongly depends on available onshore technical potential.
The outcomes show significant potential for both emerging technologies that could be realized in the near future. This study provides first exploratory findings that lay the foundation for future studies in the context of this research topic. Multiple directions for follow-up research have been identified to quantify this potential in more detail.

Wind turbine noise is one of the grand challenges in the public acceptance of onshore wind farm projects. The field of psychoacoustics identifies the auralisation of wind turbine noise as a link between technical design and annoyance estimation. There is currently limited work on the auralisation of wind turbine noise, and none targets an application in psychoacoustic research.

This work investigates the auralisation of the aeroacoustics output of DTU's HAWC2 for use in annoyance estimation. A Gaussian beam tracing approach propagates the frequency domain output to observer locations. The resulting spectrograms are converted into sound signals by applying random phase and the inverse short-time Fourier transform. This work includes a binaural rendering module to enable future VR applications. The methodology's implementation results in the Wind Turbine Auralisation tool, WinTAur.

The noise signal output of WinTAur is validated using the HAWC2 model of a stall-controlled NTK 500/41 wind turbine and corresponding acoustic field measurements. Psychoacoustic sound quality metrics show significant differences between the auralised and measured noise. In the overall psychoacoustic annoyance metric, these differences mainly depend on the observer's position around the turbine. All metrics show this directionality dependence, while the loudness, sharpness and tonality metrics also indicate a dependence on wind speed. Differences in fluctuation strength show a minor dependence on the simulation case but are difficult to relate to a specific simulation parameter.
Spectral analysis of the simulation output samples reflects the limitations of HAWC2, demonstrating that it is the primary source of discrepancy. The analysis especially highlights the inaccurate prediction of the directionality and stall noise of the HAWC2 code. The choice of ground type is another probable source of discrepancy, as it does not accurately represent the measurement setup.
A subjective listening experiment demonstrates the significance of these discrepancies in human perception with generally high difference ratings between the simulated and recorded noise. The results illustrate a dependence on wind speed and the position around the turbine. These dependencies match well with the findings from the numerical validation.\\

Future work should focus on a sensitivity analysis of WinTAur since the case-independent parameters may be additional sources of discrepancy. Another recommendation is to investigate the unveiled errors in the underlying methodology. Lastly, better propagation modelling concerning the wind turbine wake and turbulence should be part of future wind turbine noise modelling.

Overall, using modelled wind turbine noise for the auralisation in psychoacoustic research has shown promising results. Validation with sound quality metrics provides good insights into the discrepancies found in subjective listening experiments. Eliminating the existing discrepancies through modelling improvements will allow this work to be applied in a fully modelled approach to estimate wind turbine noise annoyance.

This thesis explores the feasibility of retrofitting ageing offshore wind farm (OWF) foundations with airborne wind energy (AWE) systems as a sustainable alternative to decommissioning or wind turbine (WT) refurbishment. These OWFs, starting their operational life between 1995 and 2003, face the challenge of reaching the end of their 20 to 25-year lifespan. Decommissioning incurs costs and environmental concerns, while refurbishment with larger WTs is increasingly expensive due to rapid technological advancements.

The study conducts a structural assessment of retrofitting offshore foundations with a 500 kW AWE system, covering the ultimate limit state (ULS) and fatigue limit state (FLS) evaluations. ULS calculations confirm that the foundations can withstand new AWE-generated wind and wave loads without exceeding design limits. Fatigue assessments demonstrate substantial expected foundation lifespans, even with a 99% initial damage assumption, suggesting AWE retrofitting preserves structural integrity.

Other AWE retrofitting scenarios are considered as well. Retaining the tower and mounting the 500 kW AWE system atop the tower is deemed possible, resulting in higher capacity factors. Calculations using a 2MW AWE system are performed as well. This is structurally possible, but the AWE technology of that size still faces technological challenges.

The economic feasibility of AWE system retrofitting is assessed through income and cost evaluations, comparing it to repowering with larger WTs. Results indicate competitive LCoE values for tower-mounted AWE compared to WT repowering, offsetting decommissioning costs and promising sustainable energy generation. Notably, 2 MW AWE systems exhibit economic potential in various scenarios.

This research contributes valuable insights into the viability of AWE retrofitting for ageing OWFs with AWE technology, offering a sustainable pathway forward and highlighting both the possibilities and challenges of this approach.

With an ever increasing demand for sustainable energy, limitations of current sustainable technologies are studied widely. In wind farms, the so-called wake effect provides the biggest limitation on wind farm total power output. Using wind from the unaffected boundary layer to re-energize the wind flow in the wake provides a method of limiting this wake effect. In this study, kites are introduced to steer the wind flow of the unaffected boundary layer into the wake through a downwash velocity. RANS (Reynolds-averaged Navier-Stokes) simulations are performed in Computational Fluid Dynamics (CFD) software OpenFOAM of the atmospheric boundary layer (1), a small four-turbine wind farm (2) and a wind farm with static kites between the turbines (3). The turbines are modelled through the actuator disc approach, and kites are introduced through the more complex actuator line method. Results of the athmospheric boundary layer (ABL) and wind farm simulations correspond well with literature. Through extensive kite parameter studies, an optimal layout of kites in the wind farm is presented yielding a wind farm efficiency increase of 2.3 %, which increases over 5% for even larger kites. Kite size and the kite’s downstream location show to impact the re-energising levels of the wake flow the most. The kites generate a downwash wake instead of a single downwash velocity, a finding that should further be studied in future research.

Wind turbines play an increasingly imporant role in the energy production of our time. In order to optimize the performance of wind turbine blades, this thesis work aims at assessing the possibility of using panel methods for gradient based optimization of the aerodynamics of wind turbine blades. Specifically, the method employed has used Dirichlet boundary condition, a fixed wake for optimization and a free wake model for validation. The panel method developed has been validated against the MIRAS software and CFD results. The results of the optimization are compared against the Glauert optimum blade. The blade is parameterized using NACA profiles and the twist and chord are used as design
variables. Two optimizations have been performed: an unconstrained optimization, which has shown to take advantage of limitations of the panel method model; a second optimization is performed applying a thrust constraint and with tighter bounds on the design variables, which is capable of achieving realistic results. The main conclusion is that realistic blade designs can be achieved using a fixed wake panel method for aerodynamic optimization, although ultimately the performance of these designs should be assessed using
higher fidelity models.

An idea was proposed to allow an autonomous drone to have indefinite flight times over the ocean by applying renewable energy technologies and theory to generate electricity in flight. This is considered less as a way to save energy, but to permit the use of such a drone from a ship not capable of safely retrieving it. One novel component of this idea is to use the wind updraft created by the motion of a ship or natural air currents as the wind source for an on-board turbine generator. The second component is to use the existing drive system as the on-board turbine in a 'hybrid rotor' design to reduce the need for extra parts and complexity. This report analyzes the potential for such a system compared to a more intuitive airborne solar system, and to the combination of both concepts. While indefinite flight time is paramount, the goal is to maximize the "mission" time to charge/idle time ratio. The process for determining fitness is a simulation of the aircraft flying on its mission and charging when needed (and if possible) for a full year for varying designs of aircraft and rotor. The results of all the tests show that the main idea is infeasible because not enough energy can be generated from the inefficient propeller and the updrafts are insufficient and inconsistent. The alternatives of solar and combined power systems function better but are still subject to high failure rates. The most promising system is to use a separate turbine and propeller and also include solar panels to achieve the most effectiveness both when in powered flight and while charging. This constitutes a compromise on the 'hybrid rotor' part of the idea. The conclusion of this report is that further improvements to the design and control of the most successful configuration are possible could result in a fully functional system.

In recent years, development of a concept from the mid- 1970's has led to the emergence of Airborne Wind Energy Systems (AWES). Currently the AWES sector encompasses dozens of companies that are developing a range of concepts of, more or less automated, flying wings attached to a tether which convert wind energy to electricity. At the time of this writing however, AWE as a technology discipline is still in early stages of development; not a single company has been capable of producing a commercially ready system. This phase, where the primary goal is to commercialise technology, is described as the 'valley of death' as here the risk of failure is high. In literature this phase has gathered attention from a policy perspective, however the perspective of the entrepreneur is scarcely researched. This research will attempt to find an answer to the problems that entrepreneurs encounter in the valley of death.

The valley of death is defined as: A phase that occurs during commercialisation of technology where a combination of long and costly development and a lack of resources cause an environment where the risk of failure is high for organisations to introduce the first commercial product.This definition, combined with a literature review on challenges that are likely to occur in this phase, forms the context that defines the strategies.In four expert interviews with private sector investors and experienced entrepreneurs, this context is discussed. The findings from these interviews are combined with insights from literature to identify three likely challenges: 1) technology uncertainty, which is caused by the inherent complexity of hardware development and production, which result in long and costly development. 2) market uncertainty, which is caused by difficulties in matching technology characteristics to market needs, hesitance by other stakeholders or competing against an incumbent regime and 3) lack of financial resources, which is the result of high costs during the commercialisation of hardware technology and a tendency to under invest by the private sector. In order to identify a possible way to deal with these answers findings from a separate literature review and from the four expert interviews are combined. From this, eight strategies emerge.The findings in this analysis show that activities belonging to all seven functions are found in the AWES TIS. Possible barriers are found in functions five and six. There is little to no market formation, only through technology push by the entrepreneurs. Resources are considered scarce for development and AWES technology development is costly and long. These barriers are similar to the challenges and characteristics of the valley of death.

Concluding on the main research question the valley of death was redefined from the perspective of the technology developer, including multiple perspectives. It is characterised by a low availability of resources and organisations that develop hardware based technology are at risk of failing to commercialise. By identifying and testing common strategies for their applicability this research was able to provide a way to reduce the risk of failure in this phase. Start-ups that develop new technologies must prioritise commercialisation of their technology by focusing on minimum development towards specific needs in order to generate revenue. However, for hardware based innovation external resources are needed to fund development. By demonstrating the ability to find value these start-ups increase the chance to appeal to investors in the private sector and secure the necessary funding.

A crosswind pumping kite power system is an Airborne Wind Energy (AWE) system that uses a flying tethered device for energy generation through a ground-based generator. The AWE research group of the TU Delft was one of the first to demonstrate the functioning of such a system. The spin-off Kitepower later on continued the technological development of this concept towards a commercial product. The system uses a leading edge inflatable (LEI) wing that operates by alternating between a traction phase and a retraction phase. Throughout these phases, the wing experiences a wide range of flow conditions with frequently changing incoming flow velocity, angle of attack and sideslip angle. As the wing is made of a flexible membrane, the shape of the wing is not fixed and will change under the aerodynamic loads applied to it. Therefore, the aerodynamic optimisation of such a wing forms a complex Fluid-Structure Interaction (FSI) problem. However, this thesis will only focus on the aerodynamic analysis of the LEI V3A wing developed by Kitepower. The analysis is done through the use of steady-state Computational Fluid Dynamics (CFD) simulations with a rigid wing geometry. Similar work that was done previously used a simplified wing geometry, which omitted the chordwise struts and only considered a limited range of flow conditions. In this study, these struts have been included in the geometry and their impact on the aerodynamic performance is assessed. In addition to this, the aerodynamic performance of the LEI wing under sideslip conditions is analysed. A hybrid meshing approach has been adopted to generate the computational domain. Simulations have been performed using a Reynolds-Averaged Navier-Stokes (RANS) solver with transition model. Comparison of the force coefficient curves showed that the impact of the struts on the total aerodynamic performance is minimal. Throughout the whole range of flow conditions considered, the force coefficient curves showed similar trends and absolute values. Locally, there are differences in the flow fields, predominantly in the tip region on the pressure side of the wing. The change in aerodynamic performance as a function of the sideslip angle was concluded to be strong. An increase in the sideslip angle led to a drop in the lift coefficient and an increase in the drag coefficient. Averaged values of the force coefficients were in line with inputs of several numerical models. Comparison of the results to available experimental data showed agreement for a limited range of flow conditions. The differences between the results of the present study and available experimental data are believed to be caused by the experimental data processing methods, in-flight deformation of the wing and steering actuation.

Airborne wind energy (AWE) is an emerging field that aims to revolutionize the wind energy sector.This work focuses on the aspects of modeling AWE kite flight behavior. Research on such modelsis important since new or improved models can potentially reduce development time and costs andprovide insight in the role of key system parameters.This research investigates the effects of the mass and drag of the kite control unit (KCU) on the kite’sflight behavior since it is hypothesized that the mass of the KCU causes an outward swing of the KCUduring turns and that KCU drag reduces the angle of attack during the retraction phase.For this investigation, the simulation of a kite and tether system is required. Existing simulation environ-ments could not be used due to legacy code, limited validity or unsuitable model complexity. Therefore,a suitable kite and tether model need to be selected for implementation in a simulation environment(SE). Two kite models have been found suitable: Fechner’s and Ruppert’s model.In the early stages of this research the aim was to use a model that has been fitted to experimental flightdata. Due to the unavailability of experimental flight data, the parameters of both models are identifiedusing simulated flight data. This approach provides Kitepower with a method to identify the modelparameters with experimental flight data in the future. Kitepower is an AWE company that facilitatedon this research.The groundstation controller and flight controller signals of Kitepower have been integrated in the SE.Two experiments have been performed in the SE. For the first experiment, flights are performed withdifferent and increasing values for the drag coefficient of the KCU. In the second experiment the massof the KCU and kite have been varied independently. Both experiments have been performed in a lowand high wind condition.The high wind condition experiment showed that and increasing drag results in a reduction of 7% ofthe average cycle power. The KCU drag force can reach up to to 5% of the kite drag force for a KCUdrag coefficient of 1.5.Increasing the combined mass of the kite and KCU results in an increase of >150% in average cyclepower output for the low wind conditions and an increase of >40% for the high wind condition. Theincrease in power is caused by a reduction in elevation angle in combination with the assumption of aflat wind profile. Additionally an outward swing of the KCU of 4.5 ∘ has been observed.It is recommended to compare Fechner’s and Ruppert’s rigid body kite models through using experi-mental flight data in order to investigate which model reproduces actual kite flight the best. Furthermoreit is recommended to investigate the optimal altitude or elevation angle at which to operate the AWEsystem for maximal power output considering a non-flat wind profile, tether drag and kite and KCUdynamics. It is suggested that these findings should then be incorporated in the flight controller ofKitepower in order to increase the system power output.

As airborne wind energy is a relatively new field, much of the current research is rapidly progressing towards the development of larger commercial systems with larger airborne components. Farms of airborne wind energy systems can provide higher power generation than a single kite system and offer a potential solution to issues that single kite systems exhibit with continuous power production. An in depth analysis of small scale kite farm systems will be conducted based on Kitepower’s single kite flight path model. This model has been further developed for improved performance, and has been verified with experimental data from the Kitepower system. From this single kite model, a kite farm simulation was developed to evaluate the effects of varied flight paths for several kite farm layout configurations, providing results for power density, power stability, and spatial requirements of the systems.

Thorough understanding of flexible wing structural and aerodynamic properties is crucial to reduce uncertainties in the design process of energy generating kite systems. A flexible leading edge inflatable (LEI) tethered kite connected to a drum-generator module is currently being developed by the Airborne Wind Energy research group at TU Delft jointly with its commercial spin-off Kitepower. During each energy generation cycle, the kite experiences persistent regions of flow separation, which combined with the bowed shape of the kite and its low aspect ratio cause multiple 3D flow phenomena. Furthermore, a kite is a lightweight and flexible structure and there exists very strong coupling between the aerodynamic loads and its structural dynamics, forming an intricate aeroelastic problem.

Due to computational limitations of today's hardware, it is difficult and expensive to numerically solve the coupled aeroelastic problem in detail. As such, the focus of this thesis is to resolve and characterise one side of the problem, which is the LEI kite aerodynamics. Kitepower LEI V3A kite, modelled as a rigid geometry, has been analysed for various Reynolds numbers and angles of attack using a steady-state Computational Fluid Dynamics solver. A high quality, hybrid mesh has been generated. The gamma-Rethetat transition model has been used to improve the accuracy of the results at low Reynolds numbers and to assess the significance of transition at high Reynolds numbers.

Obtained force coefficients for a range of angles of attack are in general agreement with the values used in existing numerical models and measurements from experiments. The results indicate that flow transition is important to take into account for Reynolds numbers at least up to 3 million in order to accurately predict the stall angle. Large amounts of cross flow have been observed over the span of the kite that may affect the integral drag coefficient. The employed methodology is only applicable to the traction phase of the pumping cycle, as the steady-state and rigid geometry assumptions do not hold during the retraction phase, where the kite experiences severe deformation.

Offshore wind energy is a fast-growing sector and it is quickly increasing its share in the European electricity mix. However, the costs are still high and the economic feasibility of offshore wind turbines is limited to shallow waters. This limitation plays a relevant role in the development of the sector and limits the offshore wind exploitation area to a small percentage of the potential one. In this scenario, floating support structures may represent a solution. Nevertheless, these type of support structures are not yet economically feasible as their design is challenging. In fact, with respect to bottom fixed structures, they present more complex dynamics and more degree of freedom. In order to cut the cost of floating support structures, it is necessary to be able to predict the wave- and wind-induced loads and motions of the floater and understand the coupling between them.
The aim of this project is to develop a three-dimensional numerical model of a floating cylinder in order to study the Fluid-Structure Interaction (FSI) of a spar-buoy support structure for offshore wind applications. The model is based on the coupled use of the CFD solver fluidity, to resolve the fluid dynamics, and an in-house python-developed code, to numerically solve the equations of motion of a rigid body in three dimensions. To achieve this goal, firstly, the python code is developed. Secondly, a Numerical Wave Tank (NWT) containing both air and water is generated and validated with both linear and nonlinear waves. Here, both an unstructured adaptive mesh and a simplex structured mesh are used to describe the domain. Finally, a free heave decay test of a floating cylinder is performed to investigate the accuracy of the model in computing the hydrodynamic coefficients of the floater. Here, the immersed-body method is used to model the presence of the body in the fluid domain.
The numerical wave tank developed in this work resulted to be quite accurate and capable of correctly describing both the linear and nonlinear waves propagation. The final model is developed with the use of a simplex structured mesh. In fact, mesh adaptivity resulted to be very challenging and the cost of its implementation exceeded the benefits. Also, a finite element based scheme including a Sweby slope limiter is used to limit advective fluxes in the setup of the NWT. Thanks to this, a less computationally demanding mesh could be used. Finally, the FSI analysis showed that, with the developed setup, the CFD solver is able to accurately predict the natural period of the floater but it underestimates the hydrodynamic damping. The cause of this was attributed to the use of the slope limiter aforementioned. In fact, it smooths the velocity field by means of numerical diffusion and this affects the resulting damping.

The design of sails has always been done experimentally, and only recently simulations are starting to be used in the design process. This thesis is a first attempt in creating a solver that couples CFD and FEM in order to compute the deformed sail shape (flying shape) and the thrust it can provide. Such solvers already exist but are not available to the public, or if they are they come with a very high license price. The complexity of the problem is both in the flow, which is fully turbulent and detached, and in the structure, which is deformable and free to move in all directions. Moreover, the coupling of the solvers has to be performed in a way that minimizes loss of information and accuracy.
First the CFD simulations have been run and validated with two softwares, OpenFOAM and FINE/Open. The results were very satisfying for FINE/Open, while quite poor for OpenFOAM. Consequently, the FEM solver has been successfully validated for some cases of which the analytical solution is known, due to lack of reference data for this specific case.
Finally, the interpolation techniques have been implemented in Matlab and the fluid structure interaction solver has been run. The solver has been validated on a given testcase with satisfying results; however there is still room for improvement in terms of run times and automatization of the solver. From the results it can be argued that the design and flying shape of the sail are quite different and provide different thrusts. That is an indication of the significance of this type of analysis in the sail design process.

The trailing edge of wind turbine blades are commonly manufactured as an adhesive joint of the pressure-side and suction-side composite panels of the blade. Under some conditions, a lead-to-trailing (LTT) edgewise bending moment can induce buckling at the trailing edge adhesive joint, which may lead to early failure of the blade due to delamination. As a structural instability, buckling in wind turbines has been the focus of much research especially in full-scale tests and more recently at the sub-component level. These higher-level tests, however, are done on pre-manufactured wind turbine blades and require extensive preparation in order to adapt the testing rig to each blade section, as well as incurring into elevated costs.
An additional test level has been suggested for elements and details of wind turbine blades. It has been suggested that this level can fulfill many purposes: New concepts, modifications, material combinations and orientations can be tested, partial safety factors of larger scale tests can be reduced or even certifying minor details of the blade can be done at the element and detail level. As such, the focus of this project is to develop a testing method for a simplified trailing edge bonded joint with a custom designed hinged clamping system upon which a compressive moment can be imposed to induce buckling.
The design of this test will initially be based on a semi-analytical buckling plate model, where in-plane and out-of-plane displacements are coupled through the Von Karman strain-displacement relations. This semi-analytical tool is employed to quickly estimate the buckling loads for plates of varying dimensions. Strain-free imperfections can be included in the model for twisted/pre-bent plates in order to estimate their effect on reducing the load-bearing capacity of the structure. The semi-analytical tool is complemented with FE models for all the design parameters.
The semi-analytical and numerical results are compared to demonstrate the agreement of both approaches aimed to provide a sturdy base for the research. Next, the experimental buckling loads and force-displacement curves are shown against the predictions from the previous approaches with good agreement. Nevertheless, the observable discrepancies between the experimental and numerical results showed that the desired joint-fixity at the boundaries was not fully realized, therefore leading to a slightly different post-buckling behavior. In the end, suggestions are given to improve on the experimental clamping system in order to improve and expand the scope of this research.

Airborne Wind Energy (AWE) is a field of engineering that utilizes tethered aircraft for the generation of electrical power. The potential for the application of AWE in deep-water offshore environments on top of floating foundations is enormous. Where conventional wind turbines would require a very stable platform to reduce motions at the nacelle, AWE requires just enough stability to survive extreme conditions, take-off and land horizontally, and not negatively affect cross-wind performance. The requirements scale well with increasing capacity of AWE systems, which mostly influences the mooring configuration instead of the steel structure. That is why Ampyx Power started an investigative study into the floating offshore application of AWE in collaboration with Mocean Offshore, MARIN and ECN.
A driving factor in the design of the floating foundations is the maximum allowed motions in different sea states. The objective of this research is to determine the relative magnitude of the effect of platform motions on the landing performance. This will result in more clearly defined design requirements for both the floating platform and the aircraft. The method used in this research can be extended to more advanced numerical models at a later stage of the design to obtain quantified motion constraints or operational limits.
It is assumed that standard deviations of several parameters at the end of the landing approach serve as good indicators of successful landings. A numerical model of a tethered aircraft (RPA) making a horizontal landing in time domain is developed to determine these parameters in a multitude of wind conditions. By performing a Monte-Carlo analysis, the standard deviations of these parameters can be acquired. Especially symmetric motions (X, Z and RY) are expected to affect landing performance, which is why a 3DOF model is used. Then harmonic platform motions are included in the model in order to investigate what type of platform motions are most critical. Finally, the platform designed by Mocean Offshore is examined. By combining the motion response of this platform with metocean data at a reference location, the standard deviation of critical parameters is obtained in comparison to an onshore application. The motion response of the platform is determined using a numerical model that combines potential theory with semi-empirical drag formulations. This model is validated with basin tests at MARIN.
Simulations with harmonic platform motions indicate that both frequency and amplitude of platform motions are critical for the landing performance. The landing performance appear to be mainly related to the platform motion velocities. Therefore, increasing damping and added mass of the platform will both have a positive effect on the landing of the RPA.
When looking further at the results of the simulations with platform motions based on metocean data and the hydrodynamic, numerical model, it was found that the current design of the floating platform by Mocean Offshore leads to an expected decrease in landing performance compared to the onshore application. The performance decrease is not insurmountable, and multiple methods of reducing the negative effects on landing performance are presented.