The viability of hydrogen as a sustainable energy carrier is significantly affected by the costs linked to its transportation and storage. Transporting and storing hydrogen in its liquid form offers remarkable advantages, as liquid hydrogen has unique characteristics, including lower weight and volume, as well as a higher energy content compared to gaseous hydrogen. However, current industrial hydrogen liquefaction processes face significant challenges related to efficiency and cost, with a second-law efficiency of less than 25% and costs ranging from 2.5-3.0 US$/kgLH2.

Large energy storage systems can address the issue of energy demand fluctuations in renewable energy grids by storing excess energy produced and compensating for any energy shortfalls. The development of hydrogen energy storage systems will thus support the advancement and increased utilization of renewable energy sources. The demand for liquid hydrogen is expected to rise in the near future, driven by environmentally friendly applications and use in mobility sector. As a result, large-scale hydrogen liquefaction (LHL) plants will become increasingly important in the clean energy efficient hydrogen supply chain.

This thesis aims to develop a Large-scale Hydrogen Liquefaction (LHL) plant based on the Brayton cycle concept of 86 TPD. The plant is modeled using Aspen HYSYS, with preliminary designs for key equipment—such as compressors, turbines, and plate-fin heat exchangers, ensuring compatibility with current technological constraints. State properties of the fluid used in the design of compressors and turbine equipment were obtained from REFPROP software, utilizing the Peng-Robinson Equation of State (EOS). For the design of plate-fin heat exchangers, Aspen Exchanger Design and Rating (EDR) was employed. Subsequently, a techno-economic analysis was conducted using the Aspen Process Economic Analyzer (APEA) to estimate both capital and operating expenditures, based on the process simulation model and preliminary equipment designs.

The specific energy consumption (SEC) of the plant, accounting for power recovery from turbine shafts, is determined to be 6.9025 kWh/kgLH2. The plant’s exergy efficiency is calculated at 43.665%, and the specific liquefaction power is found to be 3.014 kWh/kgLH2. Assuming an electricity price of 0.1 €/kWh, modelled 86 TPD Brayton-cycle concept yielded specific liquefaction cost (SLC) of 1.57 €/kgLH2.

A sensitivity analysis was conducted to identify the parameters that influence the specific liquefaction cost (SLC) of the plant. The analysis focused on two key parameters: 1) electricity price and 2) feed pressure. The results reveal that fluctuations in electricity prices have a substantial impact on the plant’s economic performance. Additionally, the analysis indicates that the plant’s efficiency and economic viability are significantly sensitive to decreases in feed hydrogen pressure.

Recent advancements in the field of nanotechnology have proven to offer viable alternatives for energy production, transport, and storage. As far as thermal energy is concerned, nanofluids have emerged as a novel method to enhance heat transfer. Indeed, nanofluids exhibit superior thermal capabilities, which may be able to meet the requirement of high heat dissipation rate in limited space advanced by various high-tech industries.
In particular, boiling heat transfer is an efficient heat removal mechanism that may be further improved by using nanofluids. Indeed, it has been reported that nanoparticles play a crucial role in affecting the parameters which have major impact on the boiling process (i.e. thermophysical properties of the fluid, heating surface morphology, near-surface hydrodynamics). Being boiling very sensitive to surface characteristics, the latter factors have been found to have a significant influence on the boiling heat transfer coefficient. Hence, the aim of the present research is to elucidate the physical mechanisms underlying pool boiling of nanofluids.
Based on this framework, a pool boiling test facility has been designed and validated, thus enabling to conduct a comparative study on boiling of a pure fluid (water) and a water-alumina 0.1% da nanofluid. The pool boiling experiments were performed on six aluminium samples, which were characterized by SEM (scanning electron microscopy) and WLI (white light interferometry) before and after boiling in order to highlight the change in surface topography.
The research efforts were targeted at correlating the trend of the boiling curves and the surface parameters of the corresponding sample. Nonetheless, due to the limited dataset and the inconsistencies in the behaviour of the tested nanofluid, further investigation is required to assess the potential of nanofluids as more efficient heat transfer media.

The Nuclear Research and consultancy Group (NRG) performs CFD simulations to improve the safety of nuclear installations and conducts research leading to new computational methods. One of the problems encountered in nuclear installations is that vital parts of the reactor, such as the fuel rod bundle, corrode over time. Corrosion leads to roughness elements on the surface which affect the heat transfer. To increase safety and reduce costs, it is of paramount importance to predict the heat transfer accurately when the surface is rough. The effect of roughness on a flow is an increase in both skin friction and heat transfer. Current models rely on the Reynolds analogy to calculate the heat transfer. Because in most applications pressure has no effect on heat transfer, it is often overestimated. In this thesis the accuracy of RANS modelling with respect to predicting heat transfer rates from or to a rough wall has been investigated.

It was found that a model for Low Reynolds Number meshes showed promising results. A downside of a RANS simulation on a Low Reynolds Number mesh is the increased amount of computational time due to fully resolving the velocity and temperature profiles compared to one on a High Reynolds Number mesh where wall functions are used. Therefore the model has been applied on several High Reynolds Number meshes and was compared to DNS results from literature. The results clearly showed that the mesh size was of influence on the predictions. However, a possibility was identified to reduce the mesh size dependency. The damping function was found to be responsible for this dependency and was reformulated using DNS data, resulting in a fitted equation for two different Prandtl numbers. The calibrated damping function which was made for a Prandtl number of 0.7 was validated with experimental results. It was found that the adjusted model could predict the Stanton number accurately and that the mesh size dependency was greatly reduced.

For future research it is recommended that the damping function should be calibrated for other Prandtl numbers as well, so the different damping functions could be combined in a single Prandtl dependent equation.

The energy transition from fossil fuels to renewable energy sources is crucial for climate resilience. In particular, hydrogen combustion in gas turbine combustors is expected to play an essential role in the energy transition. Hence, a fuel-flexible gas turbine combustor operating with a wide range of natural gas and hydrogen fuels is necessary. Low Swirl Burner(LSB), developed at Lawrence Berkeley National Laboratory (LBNL), is one of the promising solutions for fuel-flexible gas turbine combustors. However, hydrogen combustion in LSB at lean conditions is accompanied by several challenges, especially flame flashback. Flashback results in damage and shutdown of gas turbines. Recent experimental studies performed on LSB revealed the occurrence of flame flashback at a high volume percentage of hydrogen, but the exact cause of the flashback in LSB is yet to be discovered.

In this study, numerical modelling of low swirl premixed burner with turbulent flow and high hydrogen content is performed. RANS simulations are performed initially for the non-reacting flow and are validated with the experimental measurements. Flamelet combustion model with Zimont Turbulent Flame speed correlation is employed to model the reacting flow. The flame front position obtained from the Zimont correlation closely agrees with the experiments.
Further, Algebraic Flame Surface Wrinkling (AFSW) correlation is compared with the Zimont correlation for hydrogen-enriched flames. Based on the comparison, it is concluded that the AFSW correlation did not lead to a significant difference. However, both the correlations failed to model the flashback process. Therefore, the potential mechanism responsible for the flame flashback in LSB is examined. It has been found that none of the standard flashback mechanisms is accountable for the flame flashback in LSB. Furthermore, the effect of different flame shapes reported in the experiments is evaluated. It has been observed that ’M’ shape flame has more propensity to flashback than ’V’ shape flame. Then, a shear layer and turbulent wakes in the premix nozzle of the LSB were noticed. Hence, an increase in flame speed due to the local enrichment of thermo-diffusive unstable hydrogen flame and all the aforementioned effects might lead to a sudden flashback in LSB.

In this thesis a method of combined PIV and LIF experiments on the Turbulent/Non-Turbulent interface (TNTI) of a round jet is presented.
By varying the distance from the nozzle in the measurements, the Kolmogorov scale of a large range of Reynolds number (2×10³ ≤ Re ≤ 48×10³) is kept constant, allowing for a constant resolution. The large range in Reynolds number is needed to identify a difference in scaling of the TNTI, which is difficult to capture due to the weak dependency of the separation of Kolmogorov and Taylor scales on the Reynolds number (λ/η ∼ Re^1/4). A factor of over 2.5 is achieved in the current work.
An experimental setup for these measurements is presented, as well as the design of experiments for seven Reynolds numbers based on the boundary and initial conditions of the setup. A design for measurements with a camera moving with the flow is presented as well.
Conditional statistics are used on the jet to look at the change of span-wise vorticity over the interface. For the detection of the interface scalar images from LIF are used, where the interface is detected using a threshold of dye concentration (Rhodamine B).
All Reynolds numbers show self-similarity within the measured range, comparable to literature and with a spatial resolution better than 4η. Some small differences between the low and high Reynolds number measurements can be seen. They are not expected to have significant impact on the results and can likely be solved by slight changes in the experimental setup.
The influence of the threshold on the shape and width measurements of the mean conditional vorticity profile is examined, indicating a significant dependency on chosen threshold. Current results indicate a scaling of the interface thickness with the Taylor length scale, around a value of 0.5-0.6λ, or 10-15η This is in accordance to the literature for low Reynolds numbers. Due to this significant influence of the threshold on the outcome, these results cannot be seen conclusive. For this, further investigation is needed on the dependency of the width on the threshold, and validation of the jet contour.
Universal ways to compute the threshold, jet contour and mean conditional vorticity profiles are currently missing, while they have shown to be potentially of significance on the outcome. Another method of studying TNTI scaling is via the local velocity scales, which can be found via current data, which could provide a comparison of methods. The measurements with the moving camera could help identifying the link between physical processes and the scaling of the interface.

The spaceplane vehicle is a promising concept for the future of spaceflight. What makes the spaceplane attractive is the possibility to reuse the transport system for multiple missions. This will lower the costs and satisfies the demands for more frequent transportation to space. For such a vehicle it is necessary to fulfil the flying qualities for a safe, stable and controlled flight. But, this is easier said than done, because the spaceplane vehicle has to endure many different flight conditions. While re-entering the atmosphere, the speeds and therefore the temperatures become so high that the vehicle design has to be devoted to this hypersonic flight phase. This phase results in the distinctive spaceplane design that contains a blunt nosecone and blunt wing leading edges, which detaches the shockwaves and therefore lowers the wall temperatures for materials to withstand. The downside of these design features is that when the operating speeds are lower, the reduced streamlined shape creates instability in the flow, which results in flight instability. This especially occurs in the range of Mach 2.5 until 0.8, what is called the terminal area energy management (TAEM) phase of the re-entry. Improving the flying qualities in this flight phase is important to make sure that the spaceplane is operating safely. This subject is leading to the main research question:

Which HORUS-2B shape modifications can improve the flying qualities in the supersonic till subsonic flow regime of the re-entry trajectory, without exceeding the thermo-mechanical loads of higher flow regimes?

To investigate the flying qualities of a spaceplane, the equations of motion are derived and linearized. These equations contain many input variables including the aerodynamic characteristics of the spaceplane. The linearized equations are converted to a state-space form, which creates the opportunity to derive the eigenmotions of the spaceplane. These eigenmotions are showing the dynamic stability of the spaceplane for certain manoeuvres, among of which the longitudinal short period oscillation, the phugoid and the lateral short period oscillation. For these eigenmodes there are military requirements to make sure that the flight is safe and controllable.

To optimise the shape for these eigenmodes a model is created which is able to generate shapes depending on input parameters which are dimensions of the spaceplane. The generated shape is used in an aerodynamic simulation, that requires a mesh grid around the spaceplane which defines points representing the air, where the flow properties can be determined. To reduce computational time there is looked into the efficiency and accuracy performance of the mesh and computational fluid dynamic (CFD) simulations. The fluid model and mesh quality combination is optimised to stay within 60 seconds of simulation time for one simulation and resulted into an average deviation of approximately 20\%. The aerodynamic characteristics of each spaceplane are determined by adjusting the attitude or velocity with flow conditions along the reference trajectory. The whole process is automated and driven by the program Matlab which determines the eigenmodes and visualizes the results.

The most unstable eigenmotion is the phugoid manoeuvre, which can be improved by: lowering the fuselage height, increasing the fuselage width, increasing the wing span, enlarging the winglets upwards and make the wingspan larger. Hereby the phugoid motion becomes less unstable with the downside that the longitudinal short period oscillation becomes a little less stable. Overall, the phugoid eigenmode is difficult to make stable with the available parameters and there scopes. The lateral short period oscillation is within the level 3 military requirement and is slightly improved in the supersonic regime as well as in the hypersonic regime. With a more advanced optimising method it is likely that a level 2 requirement will be achieved. The other eigenmodes are negligible small and are mostly stable. The static stability of the yaw moment affected of the side-slip-angle, which is also unstable for the original spaceplane shape, is improved (but still unstable) by the same shape modifications used for improving the eigenmodes. Other smaller modifications such as: the wing thickness or changing the corner of the wing did not influence the results much.

For further research a better optimisation algorithm would increase the performance capabilities of each modification parameter. And more computational capacity would likely increase the accuracy of the aerodynamic characteristics. For a full investigation of the flying qualities, the controllability performance should be investigated, to show the capability to artificially stabilize the spaceplane for a safe and controllable flight back from space.

At present, there is a worldwide awareness and concern about how global warming could impact daily lives and the need to switch to renewable sources of energy. Commercially, various green energy technologies such as hydro, wind, solar, nuclear fission, etc. are being used to harness their stored energy and convert it into electricity. However, amongst these, the natural sources of energy are limited in the operation by their intermittent nature. This potentially leads to the instability of the power grid system. Hence, it is difficult to replace the existing conventional fossil-fired energy generation systems with their renewable counterparts, unless and until, flexibility is introduced to damp the intermittency
of renewable sources of energy.

A Pumped Thermal Energy Storage (PTES) system, which uses a combination of a heat pump and heat engine to store electricity in form of heat and convert the heat back to electricity, could efficiently provide intraday to multiday flexibility. However, the literature reveals that this technology is not mature enough and requires enhanced research and experimental work.

The scope of this thesis includes a conceptual design, steady-state modelling, and optimization of a waste heat integrated PTES, alternatively called Compressed Heat Energy Storage (CHEST) system. Two configurations of the CHEST system were analysed: (i) CHEST with latent heat storage, and (ii) CHEST with sensible heat storage. A combination of R1233zD as a working fluid and sunflower oil
as a sensible thermal energy storage medium was selected and a Phase Change Material (PCM) as a latent heat storage medium. Towards this end, a sensitivity analysis is performed to examine the effect of various design parameters on the performance of the system. It is found that CHEST systems are not suitable for high-temperature storage applications (> 200°𝐶). Further, the effect of superheating in a heat pump, and the effect of waste heat source temperature on system performance is investigated.

An optimization study is conducted on CHEST with a sensible storage configuration to use a single heat exchanger for the charging and discharging cycle during sensible heat transfer with a storage medium. A
detailed comparison between the two configurations have been performed. Most notably a trade-off has to be set between the performance and economic viability of the system.

Finally, the integration of the optimised sensible heat storage configuration with a solar-powered alkaline electrolyser is evaluated. A 30 MW of heat from the electrolyser unit is considered to be recovered with the help of the CHEST system. Towards the end, a preliminary design of the CHEST components (heat exchangers and turbomachinery) is provided to estimate the overall sizing and performance characteristics of the components.

In order to reach the goals of the Paris Agreement, global emissions must decrease at a high rate. Looking at the industrial sector, the largest share of energy is used for process heating, with fossil fuels as its primary source. A way to improve the energy efficiency and reduce the emissions of process heating is by the integration of heat pump technology.

However, operational costs are still a limiting factor in the widespread uptake of this technology. A potential of industrial heat pumps that will have a positive effect on the operational costs, as well as its general applicability, is the possibility to operate the equipment in a flexible manner. At this point, the potential to respond with high temperature industrial heat pumps to heat demand, the electricity market or to grid congestion, is not yet unlocked.

The focus in this study is on gaining more insight into the dynamic characteristics of industrial heat pump operation. The approach is based on the modeling of a 2 MW high temperature industrial heat pump in the Dymola simulation environment. Based on the system dynamics, a suitable control method is selected and the controller settings are optimized. With this control system in place, the dynamic limitations are studied.

The limiting factor in the considered economizer based heat pump cycle is the ability of the control system to keep the superheat at the screw compressor injection port within acceptable limits during load level changes. The heat pump is found to be able to ramp up and down at a maximum rate of approximately 20%/min. This level of flexibility allows use of the heat pump for both heat demand and electricity price response, as well as for participation in grid load balancing pools. On a higher level, based on these results flexible heat pump operation can be considered possible.

Since the introduction of Hydrazine to the list of substances of very high concern, REACH (Registration, Evaluation, Authorisation and Restriction of Chemicals), there has been an increase in the investigation of “green” propellant alternatives. At the DLR Institute of Space Propulsion, a mixture of Nitrous Oxide
and Hydrocarbons (Ethylene or Ethane), called HyNOx, has been under development since 2014. These monopropellants offer bipropellant-like performance, the ability to be used in a self-pressurised propulsion system, and are non-toxic. HyNOx propellants have the drawback of high combustion temperatures (up to 3400 K). Therefore, it is necessary to study what cooling methods can be applied to rocket engines using HyNOx propellants.
During this project, the test setup, HTMS (Heat Transfer Measurement Section), has been designed, built and tested in the M11.2 test bench at the DLR Lampoldshausen to study heat transfer in regeneratively cooled channels. The design was based on what was learned from studying past experimental
setups. A test campaign was performed to study the use of Nitrous Oxide and Ethane as coolant in stainless steel, copper and aluminium alloy pipes of different diameters. The setup diagnostics system was improved by procuring new measurement instrumentation. Additionally the instruments were
installed in different ways in order to understand which method would provide the most accurate and reliable results. The results of the thesis show that Ethane has better coolant properties than Nitrous Oxide due to its higher specific heat. However, the carbon present in Ethane leads to the formation of carbon deposits at high temperatures which can lead to clogging of the pipes and therefore Nitrous Oxide could be a the preferred coolant for situations where the temperatures are high enough for carbon deposition to occur. Additionally, it was determined that pure copper and the aluminium alloy AlMgSi 0.5 are not adequate materials for the construction of cooling channels. In the course of this project and to complement the experimental testing, a Matlab-based numerical simulation tool was developed that simulates the temperature profile in the HTMS setup using empirical Nusselt correlations to determine the heat transfer coefficient.

 Distributed surface roughness elements characterise Thermal Protection Systems (TPS) typical of supersonic and hypersonic flows. The presence of these distributed roughness elements cause an increase in drag and heat transfer.  As opposed to incompressible flow over roughness elements, there are very few experimental and numerical studies on supersonic flow over roughness. The most fundamental computational technique wherein, all scales of turbulence is resolved is Direct Numerical Simulation (DNS). The cost of performing DNS of fully resolved roughness is even higher than canonical DNS because of the refined mesh needed to solve the roughness elements.  To overcome this limitation, the current thesis aims at exploring low cost alternatives to DNS of fully resolved roughness for studying the effect of drag and heat transfer in supersonic flow over rough walls. DNS results from fully resolved full channel cube roughness for Mach 2 and Mach 4 at friction Reynolds number Re_τ = 500,1000  are analyzed. The results from the low cost models are compared against the fully resolved roughness simulated using full channels. Three lower-cost alternative, namely DNS of minimal channel flow of fully resolved roughness, DNS of modelled roughness and resolved RANS are considered. As for the DNS of minimal channel flow, it is found that the velocity shift ΔU⁺ is predicted accurately and therefore the added drag. However, it cannot be used to predict the temperature field because of lack of outer layer similarity for the thermodynamic statistics. As for the modeled roughness, an extension of the model by Busse and Sandham originally developed for incompressible flows is considered. In this case the roughness geometry is substituted by the additional drag and heat transfer that it induces on the flow, which take the form of source terms in the momentum and energy equations. We perform 17 DNS simulations with modeled roughness and compare the results to the fully resolved simulation. We find that the parametric forcing method is able to predict the velocity shift with good accuracy, although recovering the equivalent roughness height from the model parameters can only be done a posteriori. The model is able to qualitatively reproduce the temperature field, but thermodynamic statistics are inaccurate when compared to DNS of the fully resolved geometry. The final computational technique is RANS. In real case applications, RANS require the use of wall functions, and in the case of rough walls knowledge of the equivalent roughness height k_s⁺ is necessary. We attempt to see if RANS of fully resolved roughness can be used to estimate the velocity shift ΔU⁺ and therefore  k_s⁺ by limiting ourself to the  linear Spalart-Allmaras (SA) model. It is found to be inaccurate in computing the mean velocity profile at  k_s⁺≈ 40 with improvements in accuracy observed for k_s⁺≈ 80 when compared with the results from DNS for cube roughness element. However, the accuracy is still low to be used for estimating k_s⁺. 

Although usually neglected in aerodynamics, radiation can present the main heat transfer mechanism in some aerodynamic applications and cause significant changes in the behaviour of the flow. Such applications typically include very high-temperature conditions such as hypersonic flow during reentry and hot gas in combustion systems. In these cases, radiative heat transfer must be properly accounted for and the divergence of the radiative heat flux must be added as a source term to the energy budget of the flow. To solve the radiative transfer equation, in this thesis work, use is made of the emission reciprocity based Monte Carlo formulation. To generate spectra, for combustion problems, a routine utilising the High-Resolution Transmission Molecular Absorption database was written. For hypersonic problems, NASA’s NEQAIR was adjusted and implemented. The radiation solver was further coupled with INCA CFD and validated using 14 different simulation cases. Several techniques of solution acceleration were also proposed and tested to reduce the computational requirements of the developed solver, including smart spectral discretisation methods and the use of a multilayered grid separating the radiative and spectral solutions.

Organic Rankine Cycle (ORC) Power Plants can be of greatimportance in the energy transition as they are suitable for converting wasteheat to power and can utilize renewable energy for their operation. To improvethe efficiency of ORC Power Plants, the physical phenomena inside thesemachines must be understood. Understanding the boundary layer of complexorganic fluid flows in these systems is crucial, as it is estimated to beresponsible for one-third of the losses in turbomachinery. n this thesis, two-dimensional steady state boundarylayer flows of nonideal gas have been investigated numerically. The objectivewas to find the influence of complex fluid nonideality, characterized by idealgas departure, on boundary layer flows. In particular, a high-speed densevapour expansion of organic fluid Hexamethyldisiloxane (MM) inside a de Lavalnozzle test section has been studied. The nozzle is part of a measurementcampaign to collect experimental data with the purpose of validation andcalibration of Non-Ideal Compressible Fluid Dynamics (NICFD) software.  MATLAB program was developed for solving thetwo-dimensional steady state boundary layer equations including generalthermophysical properties. Transition prediction methods, the algebraicCebeci-Smith turbulence model (CS-model), and state-of-the-art thermophysicalmodels were implemented. The program was verified and validated for air withliterature. The turbulence model was validated with experimental data oflarge-scale zero pressure gradient adiabatic flows. The results match for theentire Mach-number range from 0.2 up to 2.8. The program also proved to becapable of predicting the turbulent boundary layer along a flat wall inside ade Laval nozzle expanding air. Deterministic simulations of the boundary layer along thecurved wall surface of the aforementioned nozzle expanding MM were performed.The results showed a larger decrease in the newly defined property C_e inthe core flow along expansion compared to air. In contrast, the propertygradients; namely density ratio c and Chapman-Rubesin parameter C,inside the boundary layer were found to be negligible. Furthermore, the resultsshow that the influence of the pressure history upstream of the nozzle throatis relatively small or even negligible in the diverging nozzle section. Theboundary layer displacement thickness for both laminar and turbulent flow wasfound to be negligible compared to the nozzle cross section, which results in anegligible effect on the nozzle core flow. The program needs further validation for flows departingfrom ideal gas. First, the flow condition in de Laval nozzles, laminar orturbulent, needs to be obtained by conducting experiments. Then, sensitivitystudies need to prove if the inviscid nozzle design is a robust design forviscous flows too; namely, being insensitive to changes in total inputconditions, uncertainties in closure coefficients, and variations in upstreampressure history.

High-fidelity optimisation studies are a useful asset in the design of critical components for large gas turbines. These studies require the computation of numerous computationally expensive CFD simulations and result in predominantly optimisation graphs of design objectives (e.g. Pareto-front figure). The quantity of generated data is intractable and therefore in practice not stored. All the physical insight into the flow-fields is lost and no data can be accessed nor any adjustments can be made. This work researches the combination of CFD simulations and Machine Learning (ML) algorithms to simultaneously: 1) reduce computational cost and time, 2) retain physical insight by focusing on the prediction of flow-fields and 3) keep the ability to access information or to make adjustments. This research starts with the identification of 19 potential holding ML-algorithms. A suitable algorithm is chosen with the help of 4 criteria, that is referred to as the Proper-Orthogonal Decomposition (POD) - Interpolation algorithm. In studied literature it reportedly provided very high speed-up times, good accuracy, additional learning benefit and is relative simple. The POD-Interpolation algorithm is implemented on two test cases: the Von Karman Vortex Street and a Shear Mixing Layer. The results are summarised for both as unphysical and highly inaccurate. Two root-causes are identified: the first is an invalid assumption in the methodology and the second dominant root-cause is a fundamental flaw. Interpolation can never accurately predict dominant frequencies in a flow-field. With the inability of the POD-Interpolation algorithm to predict physical accurate flow-fields, a new proposed algorithm is implemented. This is referred to as the Sparse-Dynamic-Mode-Decomposition (sDMD) - Scaling method. This method relies on accurate scaling relations to predict flow-fields. However, almost no application cases have known scaling relations. The sDMD-Scaling algorithm is capable of discovering and using these newly discovered scaling relations to predict flow-fields. This is proven for the Von Karman Vortex Street case with self-made scaling relations: the Mean Residual Error of the predicted flow-fields rarely exceeds 7%. An error reduction factor of ≈ 10 is achieved when compared to the POD-Interpolation approach. The design space from the test case is computed ≈ 5.6 times faster with the CFD and sDMD-Scaling combination than with the conventional CFD approach. Furthermore, any new design point can be computed ≈ 309 times faster with the trained sDMD-Scaling algorithm than with a CFD simulation. The sDMD-Scaling algorithm proves that it is possible to combine CFD and ML to achieve the 3 aforementioned goals for a canonical fluid dynamic test case. Several recommendations are presented to improve the sDMD-Scaling algorithm for more complex cases. However, given the difficulties and efforts that went into the relative straightforward test cases, it is difficult to foresee any large-scale implementation of any CFD and ML combination for predicting flow-fields.

Heat transfer in multiphase flow plays an important role in nature and in numerous industries such as petrochemical, automotive, food processing, ocean engineering etc. It is becoming increasingly crucial to design more efficient industrial systems to reduce the environmental impact of industrial activities because of global warming and growing awareness about sustainability. To design these efficient systems it is important to thoroughly understand the details of heat transfer in multiphase flow.

This thesis follows the method of Direct Numerical Simulation (DNS) to provide a detailed physical insight of the fluid motion and heat transfer in the model. To accurately model the two phase flow the Coupled Level Set Volume Of Fluid (CLSVOF) method is used. The main advantage of using the CLSVOF method is that it can accurately capture the interface geometry and it has excellent volume conservation capability. The work presented here is an extension to an in-house code developed at TU Delft for Direct Numerical Simulation of two-phase flows using the CLSVOF method. The existing code has been thoroughly validated for the fluid and interface motion but the validation of the heat transfer model remains an unaccomplished task till now. Therefore, the main objective of this thesis is to validate the heat transfer model and then to study the heat transfer in droplets coalescence using this model.

The validation of the heat transfer model was accomplished by calculating the Nusselt number distribution over a bubble surface and comparing it to the available literature. Both the model results and the information from the literature showed very good agreement with each other. After completing the model validation, this model was used to study the heat transfer phenomenon between two coalescing droplets and the surrounding fluid. The results of the droplets coalescence are as per the expectations and are discussed in detail in this thesis. In the process of doing these analyses different ways of calculating the local Nusselt number and the global Nusselt number have been discussed. The validation of the heat transfer model and the analysis done for the case of coalescing droplets paves the way for conducting more complex heat transfer analysis in two-phase flows using this model.

Hydrothermal flames have become a very important field of study, especially for supercritical water oxidation. In supercritical water oxidation hazardous, toxic or non-biodegradable aqueous organic waste water streams can be efficiently destructed. Supercritical water oxidation takes place in a aqueous environment above the supercritical point.

In the case of turbulent flow, micromixing models are needed.
In this work, three different mixing models are analysed in a hydrothermal flame environment. These models are Interaction by Exchange with the Mean, Coalescence/Dispersion and the Mapping Closure model. When the mixing is done around temperatures far below or far above the pseudocritical temperature all models gave the same evolution of average temperature. However when the mixing is done around the pseudocritical temperature the differences are large. The Mapping Closure model is best in agreement with the Navier-Stokes equations so it is advised to use that model when simulating mixing around the pseudocritical temperature.

The time a naval combatant can be deployed for a mission is limited by its dependency on supplies. At a certain point the ship needs to leave the area of operations to be replenished in a harbour or by a support ship. Moreover, the Royal Netherlands Navy has a societal obligation to reduce its environmental impact, in particular on global warming. Therefore, the Royal Netherlands Navy (RNLN) wants to reduce the fossil fuel dependency of its fleet significantly [50]. One of the methods to reduce fossil fuel dependency of ships is to reduce their energy requirement.
The operational profile of fast naval combatants for the RNLN requires that the ships operate on the diesel engines for 90 percent of the time, often in part load. In part load, the turbocharger cannot supply the engine with the right amount of charge air. This results in a limited operating envelope for the diesel engine, and a decreased efficiency in part load. This is caused by the matching of a turbocharger, which is a compromise between high efficiency in the design point, and off design performance. However, in part load, advanced charge air configurations can potentially resolve this and improve the results as shown by Grimmelius et al. [15] and Zhang et al. [56]
This study investigates the effect of advanced charge air configurations on the efficiency and acceleration performance of diesel engines in hybrid configurations aboard fast naval combatants. First, two mean value first principle diesel engine models based on the work of Geertsma et al. [12] were used to model the diesel engine. Next, the models were partly validated with ship data. We found that an approach using compressor maps and a motion based turbocharger model was most accurate. Then, a parallel-sequential turbocharger and a hybrid electric turbocharger were incorporated into the model. A hybrid turbocharger is a turbocharger with an electric machine coupled to the turbocharger shaft. The electric machine can increase the turbocharger speed to boost the charge air pressure in motor mode. Also, in generator mode excessive power from the turbocharger shaft can be taken out and utilized elsewhere. It was concluded that the application of advanced charge air configurations can significantly improve the engine efficiency in part load. For example, in a diesel hybrid propulsion configuration with power take-off this can lead to an efficiency increase of almost 10% at 20% load in comparison with a single charged engine. Furthermore, hybrid turbocharging enables extending the operating envelope of a parallel-sequential turbocharged engine with up to 25% at 60% engine speed. This enables the engine to deliver constant torque from 600 to 1000 rpm. With these concepts therefore, both improved efficiency and improved acceleration performance can be achieved.

Zero Emission Fuels B.V. develops a standalone System that produces renewable methanol from air and sunlight. In this thesis the steady-state model of this System is replaced with a Simulation Tool that can predict its behaviour for every minute of a year. The goal is to verify how technical design parameters influence methanol production and to determine if the business case target of 6.7 mole methanol per day is achievable. This thesis will contribute to the understanding of the System, speeds-up the design process and makes it possible to see the impact of fluctuating weather conditions throughout the year at different locations on earth. The System as it was at January 1, 2018 is implemented in the Simulation Tool and its production determined for Tucson, Arizona in the year 2005. The result is an average daily production of 3.0 mole methanol with fluctuations from 1.0 mole during a cloudy winter day to 4.2 mole during a sunny summer day. The minute by minute production is found to be influenced by all System design parameters. They must thus be designed together to make sure the System performs optimally. The Alkaline Electrolysis uses the most energy of all subsystems. Four options to improve the System are identified. These are 1) improving the power the Solar Panel produces, 2) improving the efficiency of each subsystem, 3) improving how the System is controlled and 4) integrating heat. A selection of these improvements shows that it is possible to produce 4.8 mole methanol per day. The observed seasonal and daily fluctuating methanol production demonstrates the importance of the dynamic model developed in this thesis. Compared to the steady-state model it gives a more realistic view of methanol production and can be used to improve System design. However, to reach the business case target more technical improvements are needed. It should be realised that the design decisions will be based on technical, economical and political arguments.

Increasing concerns about the effects of freeing large quantities of greenhouse gases into the atmosphere have sparked interest in organic Rankine cycle for renewable power systems. Single-stage radial inflow turbines appear as suitable expansion devices for this type of application. However, supersonic conditions can be reached in the stator of these devices, causing non-ideal fluid-dynamic behavior. This makes it necessary to explore unconventional architectures, for which only a limited number of design methods have been proposed.
In this context, the principal activity of this study was to formulate guidelines, and thereby reduce the preliminary design space, of supersonic radial stator vanes. This was done by first identifying the relevant loss mechanism and design parameters through an examination of the available literature. This led to the formulation of a research hypothesis, which was studied by means of two-dimensional, steady computational fluid dynamic simulations.
To this end, a parametric study was devised, in which any design parameter can be varied to study its effect on the blade performance. This is done analyzing the trends resulting from the post-processing of simulation generated data. The data production is based on a workflow consisting of finding a condition-specific convergent-divergent nozzle, which is used to build a mean-line radial vane, for which a mesh grid is generated and utilized by a previously validated numerical solver to perform the simulations. The complete process was overseen by a semi-automated design chain constructed to manage and execute the necessary steps.
It was assumed that profile losses would be the most influential loss characteristic, given that two-dimensional flow is predominant in mean-line geometries. According to the literature, both its major components, viscous dissipation and mixing losses should have an impact on the stator’s efficiency. Likewise, the degree of expansion along the embedded nozzle present between adjacent blades, was identified as the main design specifications to be analyzed. A trade-off between the contribution of the main loss mechanisms based on the variation of this parameter was predicted to exist.
Applying the generalized research method on a candidate test case resulted in the generation of data from almost 500 different simulations. This led to several findings, including that it is not possible to vary the nozzle design Mach number without causing simultaneous changes to other relevant geometrical features, such as the throat width. This rendered invalid some of the initial assumptions used to set up the experiments.
Similarly, this finding was expected to be the reason behind large differences between the calculated and imposed pressure ratio on the boundary conditions, as well as large variations in the mass flow of each set of blades. Additional simulations were required to analyze these deviations, based on varying other relevant parameters, including the imposed pressure ratio and outflow boundary location. The results seem to suggest that, due to the supersonic nature of the flow, an additional geometrical constraint influences the expansion process.
Performance analyzes were then possible by adapting the definition of valid designs to blade configurations matching or exceeding the imposed pressure ratio. Based on these results, the relevance of the post-expansion ratio (defined as the ratio between the pressure level at the nozzle exit and the stator outflow) became apparent. This was also the case when this ratio was manipulated by changing the imposed back pressure on the system. Moreover, when quantified with respect to this parameter, the flow deviation showed a linear behavior and the losses exhibited a plateau of higher performance.
Finally, this project provides a foundation for this line of research, both in a theoretical and practical sense. Future studies should focus on validating claims made regarding the supersonic expansion process and extending the data to determine the generality of the found performance trends. Only then will it be possible to conclusively establish the dependence between design parameters and performance for this unconventional type of blade.

Vehicle dynamics models are important tools for research and development within the automotive industry. The need for such models is steadily rising due to the rapid development of automated driving, as these models allow efficient design and development of the control algorithms and functions. Chalmers Revere Lab supplements research in the field of automated driving and collision avoidance. The lab maintains two test vehicles, a passenger car (Volvo XC90) and a heavy duty truck (6x4 Volvo FH16). The models provided by Volvo are confidential, complicated for implementation as reference models and do not share the same control interface as the test vehicles. The objective of this work is to develop well documented generic and complete open-source models that represent Revere's test vehicles.
The thesis aims to develop three model units per test vehicle. The three model units are a control interface model, a quick simulation model for online prediction and an advanced model for offline simulation prior to track testing. In addition to model development, an investigation has been made on the level of modelling details suitable for automated driving for non-critical highway and city driving on dry asphalt. For instance, a clutch model was implemented to capture the behaviour of starting from a standstill for the test vehicle equipped with an automated manual transmission. The models were developed using Modelica, an object-oriented modelling tool, and Matlab/Simulink. Furthermore, a suitable model architecture was proposed for simulation of automated driving functions.
To assess the validity of the models, the simulation results were compared against experimental data. Data was collected using open-loop test maneuvers and manual driving tests. The simulation results highlight the differences between the simple and advanced model and their accuracy with respect to experimental data. As a use-case, the XC90 advanced model was simulated with a GPS-based autonomous navigation controller. Validation with experimental data showed that the vehicle model is suitable for the development of control algorithms. The simple model is faster than real-time making it suitable for online prediction and the advanced model is real-time capable which was verified with real-time toolbox on Simulink. As a suggestion for future work, the tire model can be improved to handle low-speed parking scenario and a trailer-dolly combination can be added to the tractor model for studies on combination vehicles.