Airborne Wind Energy (AWE) systems aim to achieve higher efficiency by minimising the power used by the generator to reel the kite back during its depowered phase. The kites designed by SkySails are designed such that the resultant force is lift force dominant. Thus, lift force (rather glide ratio) should be minimised in order to minimise the power used by the generator. However, in such cases, the kite canopy could potentially collapse. In order to understand this, one must study the flow over a ram-air kite in the depowered stage. In this thesis, a workflow was developed using Blender, Fusion 360 and Pointwise to create and mesh the deformed canopy profiles. OpenFOAM was used to simulate unsteady flow over these canopies using a k − ωSST turbulence model for various inflow angles and a parametric study of performance coefficients was done with respect to inflow angle. Values after a one way coupling of OpenFOAM simulations with an in-house Finite-Element Method (FEM) solver, were compared with flight-test data and two-way coupled (panel+FEM) solutions. A Fast Fourier Transform (FFT) on the lift coefficient fluctuations showed that the Strouhal number for all inflow angles reached near zero values. Thus, a steady simulation would be more cost effective alternative to calculate the same performance parameters, for the canopy profile used. The parametric study showed that internal and external pressure over the kite canopy is crucial for maintaining the shape of the kite. Design iterations of the kite to perform well in the depowered stage would require solving an optimisation problem by adjusting the twist of the kite such that it minimises glide ratio and maximises the force along the span-wise direction of the kite canopy.

Flow-induced vibrations (FIV) in tube bundles subjected to cross-flow pose significant risks to the safety and performance of nuclear reactor components. These vibrations, driven by mechanisms such as vortex shedding, turbulence fluctuations, and fluid-elastic instabilities, can lead to structural fatigue and failure. Accurately predicting FIV remains a challenge due to the complex interaction between fluid dynamics and structural response. This study investigates the effectiveness of hybrid turbulence models within commercial Computational Fluid Dynamics (CFD) tools to improve the accuracy and computational efficiency of FIV simulations.

Hybrid turbulence models, including Scale-Adaptive Simulation (SAS) and Delayed Detached
Eddy Simulation (DDES), were explored for their ability to balance computational efficiency with the accuracy required for FIV predictions. Simulations were conducted in ANSYS Fluent and STAR-CCM+ across various mesh configurations and flow conditions. The results indicate that DDES, particularly with fine polyhedral meshes and wall y+ < 1, provides improved predictions of flow-induced forces and vibrations. ANSYS Fluent exhibited greater robustness and reliability in this study, particularly for strongly coupled FSI problems in FIV simulations.

This research contributes to the ongoing efforts in refining FIV simulation methodologies by proposing a standardized workflow and offering insights into the applicability of hybrid turbulence modeling. The findings enhance the understanding of FIV phenomena and support the development of improved numerical approaches for the safer design of nuclear reactor components.

This research investigates the adjoint-based optimization of bare tube heat exchangers, aiming to minimize air-side pressure drop. The study focuses on optimizing tube shapes in an in-line bare tube heat exchanger configuration, selected for its inherent advantages in reducing pressure drop. The optimization targets flow conditions characterized by a Reynolds number of approximately 1000, based on the tube diameter. The accuracy of simulations was found to depend significantly on the turbulence modelling approach. Different models were benchmarked against empirical correlations to ensure accuracy, with the most accurate model used to recompute the flow fields of the optimized designs as a post-processing step. The optimized round tubes achieved a pressure drop reduction of up to 20%. For elliptical tubes, the optimization resulted in a pressure drop reduction of up to 10%. This 10% reduction adds to the notable improvement gained by replacing round tubes with elliptical ones.

Carbon capture and storage (CCS) has emerged as a cornerstone technology for mitigating climate change, as highlighted by the Intergovernmental Panel on Climate Change (IPCC) and International Energy Agency (IEA). A key component of CCS involves the safe and efficient transport of CO2 between capture sites and storage facilities, often over long distances. Pipelines can be an attractive mode of transport, with CO2 typically maintained in a liquid or supercritical state to optimize density and viscosity. However, rapid depressurization events, whether due to intentional releases or accidental pipeline ruptures, lead to complex two-phase flow dynamics. Accurately modelling these phenomena is critical to designing pipelines that are both safe and cost-effective.
This thesis investigates various one-dimensional, unsteady, compressible two-phase flow models to simulate CO2 depressurization scenarios in pipelines. All models are implemented using a finite volume method and discretization is done with the HLLC approximate Riemann solver, enabling the resolution of shocks and dis- continuities. Thermodynamic properties are computed using equations of state (EOS), with a focus on the Span-Wagner (SW) EOS, to capture the CO2 unique phase behaviour under high-pressure conditions. The models are validated against existing experimental data from SINTEF’s depressurization facility, which provided high-resolution measurements of pressure and temperature during rapid phase transitions.
Three different models are initially looked at: DF3, DF4, and TF5. Key findings demonstrate that while the DF3 model provides accurate predictions of pressure variations over time, it underestimates the initial pres- sure drop by up to 20 [bar]. In contrast, the DF4 model, through the manual adjustment of the mass transfer term (Γ) using the relaxation parameter ,θ , more accurately captures the initial transient behaviour, aligning closely with experimental data. Both models ultimately converge to approximately the same state after 20 [ms], with no more than 4 [bar] difference between the models.
Temperature predictions, however, pose a greater challenge. The DF3 model exhibits a spurious downward temperature spike immediately following pipeline rupture, while the DF4 model predicts an even greater initial temperature drop, neither of which align with experimental observations. The delayed cooling effect observed in experiments is not captured by either model, highlighting limitations in the energy equation and the need for additional source terms to account for temperature drop delays.
Limitations of the models include challenges in simulating temperature variations near the critical point and an inability to accurately model delayed temperature effects for both the DF3 and DF4 models. Recommendations for future work include developing a generalized mass transfer model, incorporating implicit numerical schemes for stability near critical conditions. Furthermore, the TF5 model shows promise for improving temperature predictions over longer timescales.

This thesis investigates the application of hybrid turbulence models for fluid-structure interaction (FSI) to evaluate phenomena such as vortex-induced vibration (VIV) in tube rods within nuclear reactors. The study aimed to identify and validate the most effective hybrid modeling approaches to improve the accuracy and efficiency of FSI simulations in this critical application. Hybrid RANS-LES models aim to use Reynolds Averaged Navier Stokes (RANS) modeling in regions where the flow is relatively steady and well-predicted by the RANS approach, while switching to Large Eddy Simulation (LES) in regions where turbulence is more dynamic and complex. This switch can either be very explicit and segregate the domain into RANS and LES zones or it can be a subtle modification in the transport equations using either RANS or LES as baseline.

The research began with a detailed literature review, leading to the selection of four promising hybrid turbulence models: Improved Delayed Detached Eddy Simulation (IDDES), Scale Adaptive Simulation (SAS), Partially Averaged Navier–Stokes (PANS), and Struct Epsilon (SE). These models were implemented and tested through numerical case setups to validate their performance against established reference data for crossflow over a circular cylinder at a Reynolds number (Re) of 3900.

A comparative analysis was conducted to assess the performance of the selected models. Based on this analysis, two models were shortlisted for further testing. These models were subjected to additional validation on a rigid body motion case to ensure their reliability and accuracy in FSI applications.

In this validation, the models were used to simulate flow over an elastically mounted rigid cylinder in crossflow to evaluate the frequency and displacement of its oscillation. They were tested at different velocities to determine the amplitude and frequency response. The SE model was observed to be more robust and efficient than IDDES.

In conclusion, the research provides validation, selection and comparison of different hybrid turbulence models for FSI applications. Recommendations for future research are also provided to further refine these modeling approaches.

This thesis introduces a new computational methodology to solve partial differential equations within cracked domains, focusing on coupling in-crack physics with the adjacent environment. The crack is represented discretely, allowing to describe explicitly the crack opening, which is a key parameter in the description of the in-crack physics. The governing equations are projected onto the tangential direction of the crack to obtain a hybrid formulation of the weak form. Because the fracture is reduced to a lower dimensional domain, this methodology leads to a discontinuity in the primal solution field. Therefore, a discontinuous Galerkin approach is employed in discretizing the equations, yielding results that align well with the analytical model across various configurations and increasing the model’s possibilities. The results obtained for the electric governing equations show potential for developing a model incorporating mechanical and chemical aspects, enabling a fully coupled model for dendrite propagation in solid-state batteries.

With an increased demand for renewable energy wind farms, their efficiency receives growing attention from both the industry and academics. Mitigating wake interaction effects in wind farms is one of the ways wind farms could increase their efficiency. Control techniques to increase wake reenergizing are currently under development, however, are being held back by a lack of available medium-fidelity wake modeling methods. To sufficiently support developments in the wind industry, the wake model should yield an axial wind profile that can be used for load calculations for the downstream wind turbine and assess its energy production. Moreover, for the model to be useful in the research effort the method must either show an increase in accuracy or a decrease in time-cost. Finally, the model is desired to include the effects of wake control techniques in later iterations outside the scope of this research. This thesis investigates medium-fidelity models for wind turbine wake control techniques, with an exploratory study into applying a semi-infinite spectral method with an adjusted Laguerre basis to wind turbine wake modeling. The wake model used in this research is an altered version of the Ainslie wake model. To model the wake model a spectral method with Laguerre functions for the basis is employed in the radial direction and a marching scheme with a piecewise linear basis for the basis in the downstream direction. The potential benefits of spectral methods are lower rank systems and spectral convergence. The adjusted Laguerre functions used for this research naturally fit the boundary conditions for the wake model. At the start of the domain, a Dirichlet boundary condition is applied with fitted Laguerre functions to the result of a blade element simulation. The results did not account for wake expansion and diffused the wake much sooner than physical. The implementation of the explicit formulation for the triple product integral hindered higher-order simulations, disabling research into simulations for domains much higher than 11 radial modes. The errors for the different conservated quantities are significantly higher than they should be. From the verification efforts, a relation can be observed between the number of radial modes in the domain with respect to the number of radial modes used for the inflow, which suggests that the model should use much higher numbers of radial modes than this implementation allowed. i

With (e-)grocery retailers striving to increase their efficiency and subsequently reduce their costs, the opportunities that lie in optimising the order picking process of the supply chain is of key importance. The complex nature of assigning articles to an optimal storage location, having efficient routing of order pickers, and optimised grouping of orders calls for an integral approach to these problems. The objective of the research is to reduce the travelled distance of order pickers and subsequently the costs of the order picking process. Next to the integral approach, a new method of Multiple Storage Locations (MSL) is introduced. Historic order data of an e-grocery retailer is used, together with information on stock keeping units (SKUs), to implement SKU allocation with MSL possibility, routing, and batching into models. This ensures that the cost saving effects of these measures can be quantified. A benchmark Mixed Integer Linear Programming model (MILP) is developed and compared to a meta-heuristic Adaptive Large Neighbourhood Search model (ALNS) to determine how much travelled distance would be saved. The ALNS has multiple destroy- and repair heuristics, some of which are novel, that are specific to the problem at hand. The ALNS is able to handle bigger instances than the MILP, whilst ensuring quality of the solution. The MILP model outperforms the ALNS for small instances, however for large instances (instances of 400 orders or more) the ALNS performs, on average, 12.5% better whilst reducing computational time by 14.8%. Finally, areas of improvement are suggested in the ALNS model as well as other effects that should be studied when introducing MSL.

The advent of global warming has brought an increased interest in non-conventional sources of energy, one of which is nuclear energy. Threatening the almost year-round functioning of nuclear power plants are Flow-Induced Vibrations (FIV). One such mechanism, Vortex-Induced Vibration (VIV), holds importance in areas of cross flow in nuclear power plants. To make fail-safe
designs, computational analysis in the domain of Fluid Structure Interactions (FSI) has been increasing over the past two decades. The thesis work aims to add to the body of knowledge by making predictions for an in-line two-cylinder configuration, set up as part of a benchmark proposed by the Organization for Economic Co-operation and Development (OECD), using the commercial code Simcenter STARCCM+ (v2020.3.1).

The main objective of this study is to test the efficacy of the URANS framework in predicting VIV which is strongly correlated with the objective of the OECD to propose recommendations for the Best Practice Guidelines. To do so, it is desired to shortlist the most appropriate turbulence model for the final application and point out gaps in the prediction of the same. The thesis work is thus carried out in three phases: code validation, turbulence model selection and final application. Key results from this study reveal the ‘Standard K-Epsilon
Low Re: Cubic’ model to be the most apt for the final application. Furthermore, gaps are also identified in the application of URANS to predict VIV resonance conditions, the primary of which is the overprediction of the vortex shedding frequency.

The aerospace engineering industry is continuously striving for faster methods to solve and optimize engineering and research problems with a higher degree of accuracy. It is therefore relevant to investigate possibilities that are expected to accelerate computational speed, such as quantum computing. For this reason, the objective of this thesis is to investigate the feasibility of optimizing 2D determinate truss structures with a quantum algorithm run on a Gate-Based Quantum Computer (GBQC). The Quantum Approximate Optimization Algorithm (QAOA) is currently expected to be the most suitable quantum algorithm candidate for optimization problems, because of its simplicity and robustness. The most important take-away from this thesis is that it is possible to map a truss structure to QAOA format to optimize it on a GBQC. The program proves to be working on quantum virtual machines. However, it is currently not possible to obtain correct results when running on real quantum hardware due to noise.

Computational fluid dynamics is nowadays one of the pillars of modern aircraft design, just as impor­tant as experimental wind tunnel testing. Very ambitious goals in regards to performance, efficiency and sustainability are being asked of the aviation industry, the kind that warrant a virtual exploration of the edges of the flight envelope. High­ order has come to be regarded as a necessary ingredient to achieve breakthrough advances in this direction. So much so, in fact, that the major aircraft manufac­turers, governmental aerospace research agencies and top universities worldwide have been acting in coordination to increase the technology readiness level of these approaches, for the last ten years. In this work, I study in significant detail the one aspect that makes high-­order methods ideal candi­dates for enabling the use of more advanced turbulence models in industry: the cost­-efficiency of their discretization—they offer minimal amounts of dispersion and dissipation errors, for a given number of degrees of freedom. I consider three research objects: discontinuous Galerkin spectral method (DGSEM), flux reconstruction (FR) and a novel B-­spline-based discontinuous Galerkin formulation stabilized via algebraic flux correc­tion (DGIGA­-AFC), and characterize their order of accuracy, linear and nonlinear stability characteristics, as well as dis­persion and dissipation errors as a function of wavenumber. Afterwards, I experimentally investigate their relative suitability towards scale­-resolving simulation of compressible and turbulent flows, by solv­ing a number of simple test cases of increasing difficulty (linear advection, inviscid Burgers and Euler equations; all in 1D) using a purpose­-made MATLAB implementation. The proposed isogeometric method (DGIGA) has been found to be at least as viable as the other two, a priori, for the resolution of high­-speed turbulent flows. Moreover, I have found that low dispersion and dissipation need not always be associated to high order, but to a high number of degrees of freedom per patch instead; these two coincide in the more conventional schemes, yet not necessarily in DGIGA. As a nonlinear stabilization mechanism, however, the proposed combination of DGIGA with AFC has turned out to be inferior to existing limiters.

The increasing importance of climate change and stricter regulations for greenhouse gas emissions raise the pressure on the automotive industry to develop more efficient products. Besides a reduction of emissions by new combustion engines, electric vehicles are being introduced to lower the fleet fuel economy. Especially this new drivetrain technology benefits from an improved driving resistance of the vehicle, as an increase in range is highly valued for current electric vehicles. The aerodynamic drag, a considerable contribution to the driving resistance, therefore plays an important role in automotive development. With a significant contribution to aerodynamic drag, the wheels and surrounding wheelhouses are considered to have potential for possible improvements and are currently one of the focuses of research. This thesis examines the aerodynamic flow in a rear wheel arch of a low drag electric sedan to identify areas of potential improvement and derive recommendations for future developments. Three major parameters of the rear wheelhouse geometry are therefore modified and their influence on the aerodynamic drag and the flow field is assessed. These include the wheelhouse radius, wheelhouse width and the wheel track. For this purpose, Reynolds Averaged Navier Stokes (RANS) simulations are used to both calculate the effect of the variations on aerodynamic drag and analyse the origin of changes in the flow field. For parameters where it is possible, tests on a detailed full scale model are carried out in a modern full scale wind tunnel.

The demand for accurate and efficient simulations in order to test the geomechanical effects is a reality for the entire geoscience community. The motivation that arises from that need is the development and the evolution of modelling methods to study these effects. Deep understanding of any problem in fine scale is crucial, especially when it extends to much coarser scales.
In this work the finite volume method (FVM) is used for mechanical modelling of deformation in elastic media. The momentum balance equation is solved as the governing equation for mechanics, assuming linear elasticity for the stress tensor. Here, displacement is mapped onto a vertex-centred grid in three dimensions (3D). A set of eight trilinear basis functions are used to locally interpolate the value of displacement within each grid cube. In the finite volume method, the discretized form of the equations are obtained by integrating the governing equation over control volume surfaces, since in 3D the control volume is a cube. Hence, discretized forms are obtained by considering 24 surfaces, which form between a displacement node and its neighbouring displacement cells. This required extensive derivation. The implementation of the numerical model was carried out by writing a code in MATLAB. Several numerical test cases are presented to demonstrate the capability of this model. In the first place, the consistency of the model is checked through comparison with synthetic analytical solutions, which are compared to the numerical solutions. Furthermore, the simple test case of uniaxial compression, has been carried out with this model, but also compared to the results with a 2D FVM model and a 3D finite element (3D FEM) one. In another test case, ground plain strain subsidence is studied in a real hydrocarbon field with a heterogeneous map for elasticity parameters. It is shown that 3D FVM is in close agreement with 3D FEM in predicting the subsidence due to field depletion. Last but not least, displacement and stresses, in a faulted reservoir in which fluids are injected, are modelled and the results are shown to coincide with a robust analytical solutions for the system. Finally, the aim of this work is to shed some more light on the finite volume method for mechanics and bring it closer to the audience of science.

Tip vortex cavitation was previously identified as a source of the broadband noise emitted by ships underwater. This leads to unwanted noise and vibrations on board, which reduces passenger comfort, and increases the underwater signature of naval ships. The influence of different cavitation regimes on propellers and boundary layer transition on wings, has led to studies that isolate the cavitating tip vortex. This is done by using a converging-diverging nozzle (Venturi tube) geometry, combined with a suitable inflow condition to simulate a cavitating line vortex. The currently available computational power allowed for a comparative study of SRS methods (i.e. the IDDES model) and RANS models (i.e. the k − ω SST and EARSM) in wetted and cavitating vortex conditions. Both the general flow field, as well as the dynamics of the cavity deformations in the vortex were analyzed in this thesis. The geometry was selected based on the available experimental validation data for the wetted flow case, whereby preliminary studies determined the inflow and outflow lengths of the domain. A Lamb-Oseen tangential velocity profile was specified at the inlet. The vortex strength and viscous core size were tuned to obtain similar inflow conditions as in the experimental measurements, which used a fixed-blade swirl generator to generate the line vortex. The flow field in the wetted vortex case demonstrated an excessive amount of viscous diffusion of the vortex for both RANS models.This was caused by the overproduction of modeled turbulent kinetic energy at the viscous core edge. EARSM resuls were verified in a grid- and time step refinement study, however the large modeling error in the viscous core prevented the validation of the results. The IDDES model results were closer to the experimental reference, but were obtained with an almost laminar flow field. Modeled turbulence was mostly dissipated and no resolved velocity fluctuations were present in the flow at the measurement section. In the cavitating vortex simulations, numerical diffusion of the EARSM led to a more diffuse vapor core interface and a more downstream development of the vortex cavity compared to IDDES, where the flow field remained predominantly laminar at the measurement section. Both EARSM and IDDES predicted a solid-body rotation of the vapor core, combined with an increase of radial velocity towards the vapor core edge. The non-negligible radial velocity resulted in a conical cavity shape. The velocity profile of the simulated line vortex therefore did not correspond to that of a cavitating Lamb-Oseen vortex (which assumes no radial velocity components), such that the simulated line vortex was not representative of a cavitating tip vortex. he sheet cavities originating from sharp edges at the front and end of the Venturi throat strongly influenced the flow field and cavity dynamics. The developed front sheet cavity determined the streamwise inception of the vapor core of the vortex. Periodic shedding and collapse of the irregular downstream sheet cavity caused axial and radial contractions of the vapor core
as well as a noncircular deformation of the cavity cross-section. No traveling or standing Kelvin waves could be identified on the cavity interface using the developed post-processing and spectral analysis tool. The identified cross-sectional deformation did not correspond to cavity deformation modes defined in previous research and none of the other deformation modes were found to occur. Grid-dependent solutions, numerical noise and large wavenumber resolution indicated that a finer grid is required and that the analyzed length of the cavity should increase to improve the quality of numerical analyses of simulated cavity dynamics.

The Kutta condition is a boundary condition applied at a wing’s trailing edge (TE), which enables the calculation of the fluid-dynamic lift produced by a wing in potential flow. This condition is actually a stable equilibrium resulting from a transient flow. The main question of this research is: how is the Kutta condition flow-field created when a wing is brought in motion from rest? This is investigated using an experimental apparatus, in which a wing model is accelerated from rest and the transient TE flow is analysed using high-speed Particle Image Velocimetry techniques. Initially, fluid moves from the airfoil’s pressure side, along the TE, towards the suction side, and a boundary layer is created. Then, boundary layer stagnation occurs, a vortex separates from the TE, and a transformation in the presence and locations of stagnation/separation occurs. The observed process confirms classical theories which describe the creation of the Kutta condition flow-field.

In recent years the awareness and the effort to reduce air pollution and global warming have increased. Many new ideas are being developed to reduce harmful emissions. Despite this, the shipping industry is still a large contributor to air pollution worldwide. To reduce the environmental impact of shipping, the use of
sustainable energy sources such as wind energy on-board ships is being explored. Wind energy is widely available at sea, the challenge is to harness this energy. The relatively unknown wind propulsion device called the Turbosail is a vertical wing shaped device which uses wind energy to provide thrust. This propulsion technology was invented in the 1980’s by the Frenchman Jacques-Yves Cousteau. This report describes the investigation into the similar wind propulsion device called the VentiFoil. Two retractable VentiFoils are fitted inside a 40 foot container, this ship propulsion device is called the eConowind unit. Multiple eConowind units can be installed on the hatch covers of general cargo vessels. If successful, this wind propulsion device can be applied on many different ships. The VentiFoil concept will be investigated and improved using Computational Fluid Dynamics (CFD) research tools. These tools are used to simulate the flow around different VentiFoil geometries. The result of this project will be a better understanding of the working principles of the VentiFoil, sensitivity information for the variation of different characteristic design parameters and an evaluation of the generated forces and performance of VentiFoil propulsion.

Prediction of emissions from combustion systems is a complex problem involving the coupling between the flow field and chemistry. CFD analysis is the most commonly employed approach. However, it has the drawback that a very high computational cost prevents the use of detailed chemistry models. This master thesis, which focuses on NOx emissions, uses a more unconventional method of emissions prediction: Chemical Reactor Network (CRN). The advantage of this method is that, as it does not use fine discretisation, closure models nor fluid dynamics equations, it allows the implementation of detailed chemistry mechanisms.

A CRN is developed first for a single-element Lean Direct Injection (LDI) combustor and then the CRN is adapted for a Multi-Point LDI (MPLDI) combustor. CFD and experimental results are used to set up the CRN. In the base case scenario, in which kerosene is the fuel choice, the NOx emissions predicted are very close to experimental measurements. This is particularly meaningful given the high uncertainties of modelling this highly complex turbulent combustion process.

The developed CRN is also used to predict NOx emissions for the same combustor when the fuel choice is varied. Namely, the alternative fuels considered are kerosene enriched with hydrogen, methane and methane enriched with hydrogen. In comparison to kerosene, higher Lower Heating Values (LHVs) of these fuels lead to lower combustor temperatures for the same power input. Consequently, the thermal NOx pathway is weakened and the NOx mass flow generated is reduced. Nevertheless, these fuels with a higher LHV come with an increased operational risk that must be overcome before their implementation in aviation becomes possible.

In this research work, the phenomenon of extreme wind events or gusts has been studied in detail and different aspects related to the nature of gusts are explored.
In order to detect wind gusts from a stochastic time series different gust detection techniques collected from previous research works and literature studies were compiled, refined, verified and compared against each other. In addition some important insight is also given regarding the setting up of appropriate values for various gust defining parameters.
The gust detection techniques are developed into computational codes and applied over different data sets. A comparison between these techniques highlights the pros and cons of each one of them. The peak to peak method and the velocity increment method provides accurate information about the maximum wind speed acceleration within a small time interval. Other methods like peak over threshold and the acceleration over threshold methods are useful to detect specific type of wind gusts above a certain threshold.
Wind data sets sampled at high frequency resolution and from different geographical locations were obtained and analyzed through these gust detections algorithms. Among these locations are the offshore wind farm at Egmond aan Zee (OWEZ), IJmuiden and the Cabauw Experimental Site for Atmospheric Research (CESAR) which are a representative of a near offshore, far offshore and an onshore location respectively. By using a uniform gust threshold criteria for peak over threshold and acceleration over threshold methods, a comparison between different locations reveal that the maximum gusts were detected for IJmuiden which generally has higher wind speeds throughout the year.
For each location, the total number of gusts detected have been combined to obtain a mean gust shape. Furthermore, the maximum wind gusts are selected from each month and compared with the standard IEC gust shapes.
The available high resolution wind data is for a duration of 1 year only which is not sufficient for the prediction of a maximum 50 year gust. However two different approaches are discussed to demonstrate the procedure. A statistical approach involving the extrapolation of data to predict the amplitude of maximum 50 year gust highlights the need for the availability of long term wind data. The analytical approach involving the calculation of the return period of different gusts is also explained and the results presented within this report are promising to continue further research within this domain.
The techniques, findings and conclusions obtained through this research work can be further tested and eventually utilized to compliment or improve upon the existing extreme load cases of the wind turbine design standards.