Nasal airway obstruction (NAO) is one of the most common symptoms in the human respiratory system and causes a considerable financial burden to both individuals and society. Currently, NAO detection is troublesome to achieve, which can influence the accuracy and effectiveness of clinical surgery. Although several objective measurement techniques are currently available, they are found to be inconsistent with patients’ sensations. In recent years, computational fluid dynamics (CFD) has become a novel technique to objectively assess nasal airflow by simulating the nasal airflow of NAO patients. Existing literature has also shown the potential to correlate relevant CFD parameters with patients’ sensations. Nevertheless, there is still debate on the numerical setup for an accurate solution and the CFD parameter to correlate with the subjective measurement. Based on these existing issues, we mainly investigated the boundary configuration (with and without the external nose), the usage of turbulence/laminar models, the usage of steady-state/transient solvers, and briefly discussed the potential of using unilateral pressure drop ratio as a parameter for NAO detection.  To begin with, including the external nose in the nasal airflow simulation is recommended in the nasal airflow simulations. The external nose configuration can affect the flow direction through the nostrils and downstream flow distributions. However, the static (and total) pressure drop only shows a 4% difference compared to the commonly-used plane-truncated boundary configuration. Furthermore, using the laminar model is sufficient for the nasal airflow simulations concerning the static pressure drop prediction. The laminar model shows a difference lower than 15% in static pressure drop compared to the experimental values on 3D-printed nasal airway models. We stress the caution of using the 𝑘 − 𝜔 model in the nasal airflow simulations because it tends to overpredict the turbulent viscosity ratio near the inlet unphysically. Moreover, steady-state simulations can also reasonably predict nasal airflow. We observed unsteady effects when comparing the steady-state simulation with the transient simulation with a constant flow rate and the transient simulation with a sinusoidal flow-rate-versus-time profile representing the real-life breathing cycle. Nevertheless, the steady-state simulation achieves an accurate prediction in static pressure drop, with a difference lower than 6% compared to the tested transient simulations. The steady-state simulation can also perfectly match transient simulations in the velocity profile of the recirculation zones and require a much lower computational cost. Last but not least, we also tested the possibility of using the unilateral static pressure drop ratio for NAO detection using CFD. However, we note that future studies should make corrections to account for the nasal cycle effect for NAO detection.  Overall, we conclude that including the external nose and using the laminar simulations with the steady-state solver can give an acceptable prediction for the nasal airflow, especially concerning the static pressure drop prediction. We also state that applying CFD in the nasal airflow shows the potential for NAO detection, although future studies may consider making some corrections to include the nasal cycle effect.

With increasing discussion and legislation around emissions, gas turbines have evolved to limit their emissions, especially NOx emissions. The way of operating the gas turbine, with lean premixed combustion reduces the flame temperature in the combustion chamber which results in low NOx emissions. The downside of this way of operating is the increased sensitivity of the combustion system to thermo-acoustic instabilities. These instabilities arise due to an interaction between unsteady heat release at the flame and the acoustics of the combustion system. At lean premixed conditions, a fluctuation in equivalence ratio results in a large fluctuation in flame speed which is related to the heat release. This makes the lean premixed combustion very susceptible to acoustic pressure waves travelling through and reflecting inside the combustion system, as these pressure waves can influence the mass flow of gas and air in the premixing duct and thus changing the composition of the fuel mixture that is convected towards the flame. An additional effect to the unsteady heat release are fluctuations of the total mass flow at the burner outlet, which are convected towards the flame front, an increase in combusted fuel will result in an increase in heat release.To analyze the sensitivities of the combustion system, a thermo-acoustic model will be constructed. The model will be a one-dimensional and linearised system, where conservation equations across the (thermo-)acoustic elements of the combustion system are rewritten into transfer matrix form. Validation will be done by analyzing operational data from the HW09 power plant and comparing this with the model response. The combustion dynamics are analysed for frequencies in the range 0 - 300 Hz.It was found that the HW09 is susceptible to combustion instabilities when the pressure drop across the premix gas nozzles is low, which results in a decrease in fuel supply impedance. This increases the pressure amplitude in the 90 Hz range, this behaviour corresponds to the modelled results when changes to the gas preheating temperature or fuel nozzle compositions are made in the thermo-acoustic model, which influence the pressure drop over the gas nozzles. This is accompanied with a decreased amplification at the critical 120 Hz range. This is a known side-effect, as the 90 Hz needs to remain dominant for a stable combustion system. This means the pressure drop over the gas nozzles balances on a fine line, too low will result in high 90 Hz pressure waves and too high will result in a more unstable 120 Hz frequency. Several of the hybrid burners in the annular combustion chamber are fitted with a cylindrical burner outlet. This changes the flow field out of the burner and is used to allow a higher maximum load for the gas turbine. The inclusion of this burner ring makes the combustion system upstream of the burner outlet more resistant to acoustic pressure fluctuations in the frequency range up to 120 Hz. The burner system does become more sensitive to acoustic pressure fluctuations for frequencies higher than 120 Hz. Fuel composition influences the combustion behaviour of a fuel mixture. Low-calorific fuel shows to be inherently more unstable in this gas turbine configuration as opposed to high-calorific fuel. If hydrogen is added to high-calorific fuel, the flame speed is increased as is the influence of both equivalence ratio perturbations and velocity perturbations on unsteady heat release.The increase in flame speed results in a reduction of flame length, which changes the convective time delay and shifts the instability of the combustion system from the 120 Hz area towards the 180 Hz area.The thermo-acoustic model responds to changes of operational parameters in an equal manner as was found from data analysis. The results are comparable up to 200 Hz, after which the flame can no longer be assumed to be compact, which means compressibility, 2D and 3D effects have to be taken into account. Fuel composition analysis shows the importance of flame length and convective time delay on combustion stability. For hydrogen addition it can shift the critical frequency towards the second harmonic frequency of the combustion chamber, this will result in rapidly increasing pressure waves and high accelerations. With increased knowledge of the effects of hydrogen addition or low-calorific fuel on the flame dynamics, the model can be a predictive tool to investigate the combustion behaviour when the change to this fuel mixture will be made. The ability to predict the influence of different operational parameters or changes to burner geometry on the stability of the combustion system can be very beneficial for analysis of future changes to the gas turbine and its operation.

Due to the global energy crisis, there is a growing need to make industrial processes more efficient and clean. One such method is to use effective and renewable working fluids in power and refrigeration cycles. Research in this field during the past decade has placed supercritical CO2 (SCO2) in the forefront due to its non-ideal properties and abundance in nature but, to fully understand their heat transfer properties, insight into boundary layer flow and hydrodynamic instabilities are crucial. Experimental setups such as closed loop wind tunnel contraction facilities are needed which provide a laminar steady flow to take boundary layer measurements. However, using a contraction causes various problems such as formation of secondary flows like boundary layer separation, Gortler vortices, cross-flows and non-uniformity’s. In this study a novel 1D contraction shape with curvature on only one side is pro- posed. This will completely eliminate the risk of Gortler vortices on the bottom plate and make it a suitable candidate for boundary layer experiments. Nevertheless, the risk of the other secondary flows and Gortler vortices on the top wall disturbing this laminar flow remains. Hence, the present research aims to optimise this 1D contraction to reduce the risk of such secondary flows and analyse the growth of Gortler vortices on the top wall using numerical simulations. Steady state laminar simulations were performed to optimise the design of the 1D wind tunnel contraction. Optimum contraction and settling chamber lengths were found by identifying the risk of flow separation and boundary condition effects respectively. For the optimisation of the contraction wall shape, a family of transformed fifth order polynomial curves with varying inflection point distances were selected. To identify the curve with least risk of boundary layer separation and lowest flow non-uniformity, a multi- objective optimisation procedure was implemented. The procedure found that a curve with inflection point of 101mm downstream of contraction inlet gives the best performance. To analyse the effect of Gortler vortices on outlet uniformity, unsteady laminar simulations were performed on the contraction by forcing sinusoidal perturbations of different wavenumbers. This study found that perturbations form symmetrical steady steam-wise Gortler vortices in the contraction. The most unstable wavenumber was found to be 𝜆=83.33 𝑚-1 which formed secondary vortices of high vorticity. However it was also seen that for all wavenumbers, the vortices lose energy as they exit the contraction and do not affect the bottom boundary layer. Further, the effects of a side wall on the formation of Gortler vortices were also investigated. The results showed that the Gortler vortex closest to the wall is absorbed into high vorticity corner vortices, while those close to the centreline develop into steady Gortler vortices. No effect on the centreline velocity profile was seen due to the vortices making the 1D contraction suitable for boundary layer experiments. Finally, it was also seen that the 1D contraction shape produces asymmetrical Gortler vortices due to alternative perturbation methods such as random inlet perturbations.

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% 𝑤𝑡 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.

Stratified turbulent flows abound in environmental and industrial settings. Examples are atmospheric boundary layer flows, the transport of nutrients and organisms and the mixing of heat and salinity in the oceans, fluid flow in heat exchangers, and the transport of reactants and products in chemical reactions. These examples and many others consider stratified wall-bounded turbulence, in which the creation of turbulence by mechanical processes contends with its dissipation due to buoyancy effects. These flows are said to be stably stratified as these are inherently stable flows and are averse to mixing. The buoyancy effects alter the structure of the flow, and consequently the dynamics of mass, heat, and momentum transport. As density fluctuations become more severe, the Oberbeck-Boussinesq approximation becomes inaccurate and the resulting dynamics are not correctly predicted. In the current work, we developed and validated a numerical solver for direct numerical simulations (DNS) of turbulent flows featuring strong property variations. More precisely, we solve the Navier-Stokes equations in the limit of vanishing Mach number (so-called low-Mach number limit), with the fluid density given by the ideal gas law, and the dynamic viscosity and thermal conductivity also expressed as functions of temperature. Our numerical solver is used to study stably-stratified turbulent channel flow under non-Oberbeck-Boussinesq conditions. The simulations are carried out at friction Reynolds number of  180, Prandtl number of 0.71, and friction Richardson number of the O(10). These non-dimensional numbers are the governing parameters and are defined based on the prescribed pressure drop and properties of the fluid at the reference temperature. Stratification is achieved by imposing constant temperature boundary conditions, with a high upper-to-lower wall temperature ratio (larger than 2), resulting in strong density variations in the flow. We will vary the temperature ratios and adjust gravity to maintain a similar Richardson number between cases, thereby isolating the effects of strong property variations in the flow dynamics. We will analyze the dynamics of heat and momentum transport under strong stratification for these conditions, also in light of DNS data of the same system under the Oberbeck-Boussinesq regime.

Supercritical CO2 (SCO2) is a promising alternative to traditional working fluids in heat pumps and power cycles due to its high density, thermal efficiency, and stability. These properties allow for the design of more compact and efficient equipment. However, accurately modeling supercritical heat transfer, especially near its pseudocritical point, is challenging, because of extreme variations in its thermophysical properties. As a result of these inaccuracies in modeling, large fault margins must be taken into account, leading to overdesign of equipment. Current methods for estimating heat transfer in such systems include empirical measurements, computational fluid dynamics (CFD), and Nusselt correlations. Although measurements provide accurate data, it is not a scalable solution. CFD methods offer this scalability. However, CFD cannot be applied in complex scenarios such as modeling of SCO2 due to the trade-off between computational cost and accuracy. Nusselt correlations have low computational demand and are a scalable solution but come with low accuracy. Therefore, Nusselt correlations are not suitable for the design of equipment. To overcome these limitations, this research applies a new model to predict heat transfer to SCO2 flowing upward in a heated vertical tube. Current prediction methods use artificial neural networks (ANN). This research applies a convolutional neural network (CNN) for its ability to capture spatial context from the heat transfer trajectory. This property enables CNN to capture global and local patterns important for accurate prediction in SCO2 heat transfer. In addition, the multiple kernels per layer enables the model to extract a large range of features from the heat transfer trajectory allowing for higher accuracy. The developed CNN model has shown superior performance, achieving an R2 score of 0.970 and an MSE of 1477, outperforming existing ANNs and Nusselt correlations. Furthermore, a feature importance study is done, to identify the nondimensional parameters that are important for heat transfer prediction The feature importance study highlighted the importance of parameters such as the Reynolds number and the Froude number in improving the model predictions. In addition, the feature importance study led to the development and identification of a new nondimensional parameter, (qwk)/(T d), as one of the most important features influencing heat transfer. Furthermore, the experiments show that normalization is vital to enhance model stability and performance, countering issues such as exploding or vanishing gradients. The findings in this research suggest great potential for using machine learning models to design more effective and compact heat transfer equipment. Future work will focus on a feature importance study for normalized, dimensional and nondimensional parameters for improved predictions. In addition, more synthetic data should be generated in the heat transfer detoriation and heat transfer enhancement areas for better prediction of those parts. Finally, a study into the application of machine learning models for designing heat transfer equipment should be done to show the benefits of such models.

The CFD modeling based on the two-fluid model (TFM) was used on studying the novel indirectly heated bubbling fluidized bed steam reformer (IHBFB-SR). This is a collaborative project between Petrogas and TU Delft for testing the advance’s reactor configuration, which indirectly supplies the heat via radiant burner on the center toward the surrounding bed, thereby improving heat transfer efficiency and reduced the losses. The present work aimed to observe the hydrodynamic and heat transfer of the reactor by first employing air as the fluidizing gas and corundum (Geldart B size) as the bed material. The minimum fluidization condition, bubbles development, and voidage profile are the main objectives for the hydrodynamic simulation. In the heat transfer study, the effect of radiative heat transfer, bubbles and voidage profiles, and different radiative models (P1 and DO) on the heat transfer mechanism were examined. The 2D and 3D models were built, and three drag models: Gidaspow, adjusted Syamlal, and EMMS/Bubbling was employed. The simulation results were then compared to the experimental data obtained, such as minimum fluidization flowrate, pressure drop, bed expansion, and temperature profile on a specific flow rate. Initially, a grid independency test was conducted using five different grid sizes. It is concluded that the appropriate grid size for simulating the IHBFB-SR with a bed material particle size of 0.496 mm should be at least 7.5 mm or 15 times the corundum particle size. The present research used 2.5 mm or five times dp. The minimum fluidization obtained was in the range of 14-16 kg/h based on both 2D and 3D simulation. Nonetheless, if primarily refers to the 3D model results, the minimum fluidization condition should lie around 14 kg/h. Three drag models have also been compared. It was found that the adjusted Syamlal gives the closest result compared to the experimental data. Nevertheless, the drag modification, based only on minimum fluidization conditions like modified Syamlal, tends to overpredict the drag coefficient on the entire range of solid volume fraction. There are also no significant differences in the bubbles or voidage profiles among those three drag models. Adjusted Syamlal has a slightly larger bubble while Gidaspow and EMMS bubbling has a bit smaller one. The expected better result of using the EMMS bubbling drag model does not appear to have a considerable impact on the case of Geldart B or larger particles. There was also an underprediction of pressure drop and bed expansion on the simulation. Two major factors were the absence of proper particle shape representation through a sphericity factor and the lack of precise simulation of particle size distribution. Only a perfect rounded sphere of corundum with a sphericity factor of one and one uniform size of the particle was assumed. In the case of heat transfer simulation, bubbles and voidage effect firstly studied. It was found that the increase of the bubbles frequency and size, as represented on the voidage profile, would improve the heat transfer process indicated by the increase of the heat flux. The bubbles’ occurrence on the bed plays a critical role in the mass transfer’s improvement from and to the vicinity of the radiant burner wall, thus increasing heat transfer. In contrast with the voidage, the increase of superficial gas velocity does not directly influence the heat flux. It was also proved that the radiative heat transfer improved the overall heat flux in this bubbling fluidized bed reactor by about 16.11 %. Though it appears small, this contribution fits the range of other proven works, with a similar operating environment and particle size used. There are two different radiative models performed in the simulation: first-order spherical harmonics method (P1) and discrete ordinate method (DO). Both models presented a similar trend, with P1, has a slightly higher magnitude. However, the P1 model shows a peculiar result of having a strange lower temperature lower on the bottom part of the bed. On the contrary, that is not the case for the DO, which is well known for its accuracy but a higher computational cost demand. It is then concluded that for the present setup, the DO model could perform better. Lastly, the overall heat transfer process was investigated. Since no specific experimental data available for validating the heat transfer properties, only the final steady temperature values of five different thermocouples were used. Comparing these two, it was found that the present model did not give satisfactory results due to overprediction of air temperature above the bed and underprediction of bed temperature at the same time. Some improvements are required, as will be presented in the recommendations section.

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.

Mobile electronics or remote devices like sensors for the Internet of Things (IoT) require energy storage with increasing energy densities, approaching the limits of the widespread lithium batteries. At the same time, lithium batteries are subject to growing criticism about their environmental impact due to their raw materials and their mining methods. Chemical energy seems to be a promising alternative and the development of micro combustion to make use of it is already for almost 30 years the topic of ongoing research. Recent studies show that compliant combustion engines are a good solution to mitigate some problems like leakage and friction and thus, achieve higher efficiencies. However, the most prevalent problem is heat losses through the walls because of the high surface-to-volume ratio in small-scale combustion. In this work, a design concept was proposed that not only insulates the compliant combustion chamber of the actuator for Flapping Wing Micro Air Vehicles (FWMAV) but also uses the waste heat to generate electricity. That was done by attaching Thermoelectric (TE) modules to a support structure and thermally connecting them with porous media to the oscillating combustor wall. The actuator uses the heat and pressure generated by the catalytic reaction of hydrogen peroxide and therewith, only emits steam and oxygen. With the help of a one-dimensional steady-state heat resistance model and a one-dimensional transient heat resistance-capacitance model, an optimum design was found. With that, it is possible to create a temperature difference sufficient enough to enable energy harvesting by TE modules. That was achieved by implementing an exhaust gas recirculation which transfers heat to the modules and simultaneously serves as a heating blanket for the combustor. A downside of the design is the relatively long time it takes to reach its steady state and especially for FWMAV, the increase in weight.

To reduce greenhouse gas emissions and to limit global warming, fossil fuel based energy technologies need to be replaced by clean energy technologies. Renewable energy sources are dependent on weather conditions therefore security of energy supply is not ensured and the need for energy storage is growing. Hydrogen is considered a clean energy carrier that can be used for energy storage. Water electrolysis that uses renewable energy is a sustainable method for the production of green hydrogen. Water electrolysis is a process by which water is split into hydrogen and oxygen by using direct current to drive the reaction. During the production of green hydrogen heat is released to the environment. Little research has been conducted on the amount of heat released during green hydrogen production and on the temperature of the released heat. It is unclear if the released heat could be used. This research serves to answer the question "Is it possible to use the heat released during the production of green hydrogen using alkaline water electrolysis?". To answer this question a model has been developed in ASPEN Plus. This model represents an alkaline electrolyser, consisting of an electrochemical model, a thermal model and a cooling system. To validate the output of the model, the hydrogen production output has been compared with an alkaline electrolyser developed by the company Nel hydrogen. The thermal efficiency of the model has been calculated with and without using the waste heat. To use the waste heat the system first needs to be cooled. To determine which heat exchanger is best to use for recovering the heat of the alkaline electrolyser, three different designs have been implemented in the ASPEN model. The designs have been analyzed and the best option is implemented in the model. The amount of heat that can be recovered has been investigated as well as the options for the use of the recovered heat. The results are discussed and recommendations are made for follow-up research.

In recent years, a considerable amount of research has been directed towards making energy generation more efficient to combat global warming. To aid this goal, the use of supercritical fluids (SCFs) is gaining a lot of traction. SCFs have only one phase and experience a sharp variation of thermophysical properties when heated sufficiently. These facts can be exploited to gain several advantages over conventionally used sub-critical fluids. However, the strong property variation in heated SCFs also complicates the flow Physics considerably if the wall heating is strong enough. Further, the flows in such settings are often turbulent and spatially developing. For these flows, a strong variation of properties can lead to a modulation of turbulence, which the conventional turbulence models can not predict well. This thesis is an attempt to better understand how spatially developing heated supercritical turbulent flows behave and use this understanding to improve turbulence model predictions. In this thesis, we investigate two supercritical heated developing turbulent flows from Nemati et al. (2015). One case is oriented horizontally and the other is oriented vertically. The latter has an additional effect of buoyancy resulting from its vertical orientation and strong density variation near the wall. We analyze how the strong property variation modulates the turbulence in both cases. Then, we assess if Semi-Local Scaling (SLS) and Apparent Reynolds Number (ARN) theories can characterize the modulated turbulence. Further, we propose a methodology to make use of ARN by itself, and in combination with SLS to improve turbulence model predictions. The results indicate that ARN theory provides a robust way to sensitize conventional turbulence models to the additional effects arising in supercritical heated developing turbulent flows due to property variation. Additional research in turbulent heat flux modeling is deemed necessary to improve the model performance further.

Convective heat transfer finds applications in several domains of industry like heat exchangers, gas turbine blades, IC engine surfaces etc. The surfaces of these heat transfer applications are either naturally rough owing to manufacturing techniques or become rough over a period of time during operation. These rough surfaces usually contain multiple length scales and exhibit random and heterogenous properties. Fractal roughness, in principal, is characterized by self-similar detail on smaller and smaller length scales and hence fractal dimension which is independent of any length scale can become a very viable option to characterize these multi-scale random surfaces. Therefore in the current thesis, rough surfaces characterized by fractal dimensions were designed and their role in the heat transfer enhancement relative to the pressure drop was studied using DNS. The fractal surfaces were designed by randomly placing five generations of self-similar cuboids with decreasing sizes from higher to lower generations. The quantity of cuboids sprinkled randomly for each generation followed a fractal dimension. Two principal fractal dimensions were selected, i.e 퐷 = 1 and 퐷 = 2 and eight random realizations of each were generated in order to study the averaged effect of the heat transfer performance. Since the cuboids were randomly placed, different realizations within the same fractal dimension experienced varied sheltering effects by larger generation cuboids. This ultimately produced a fluctuation in the ”sheltered” solidity of the fractal surface for different realizations whose effect was also studied. The cuboids were resolved in the simulation using an immersed boundary method. To quantify the heat transfer performance of the rough surfaces, two performance factors namely the aero-thermal efficiency and Reynolds analogy factor were defined. It was found that the two types of fractal surfaces performed approximately similarly with a slight higher mean for 퐷 = 2 based on the above heat performance parameters even though the two surfaces looked very different. However, the above performance factors showed a very strong correlation with the ”sheltered” solidity of the fluctuating realizations displaying an increasing trend.

The current global environmental crisis has resulted in increased efforts towards more efficient and sustainable industrial processes. High-temperature heat between 150 ◦C & 400 ◦C accounts for a major part of the energy demand in industrial processes. At the same time, large quantities of waste heat are unutilised at temperatures up to 200 ◦C. A heat pump could upgrade this waste heat to cover a part of the demand, resulting in considerable savings both for the planet and the operator. Nevertheless, heat pumps have seen little development in heat delivery temperatures above about 150 ◦C. This research aims to assess the current technological potential and limitations of high-temperature heat pumps. Subsequently, solutions and recommendations are developed. Focussing on mechanical vapour compression heat pumps, a thorough understanding of such cycles is gained first. The performance of a heat pump is highly dependent on the choice of cycle setup and working fluid, with the compressor posing the largest limitations for higher temperatures. To assess these, this project develops a heat pump model which simulates many different working fluids for different component configurations. The model was subjected to two temperature domains, covering waste heats of 100 ◦C & 200 ◦C and process heat temperatures in the range of 150 ◦C to 400 ◦C. Results were obtained for all fluids incorporated in RefProp 9.0 and showed that multistage compression with intercooling and superheating considerably improved the performance of nearly all fluids. By comparing fluids based on efficiencies, capacities, temperatures and pressures, benzene and propylcyclohexane showed the best performance for the lower and higher part of process heat temperatures, respectively. The results however also showed the potential superiority of water as it has the best efficiencies and the largest applicability range, which combines with the hazard-free & environmentally friendly nature, low cost and wide availability. The main downside of water appeared to be the persistent, unacceptably high compression temperatures, combined with large pressures and pressure ratios. It was subsequently investigated how the disadvantages of water could be handled. A solution was found in the usage of Liquid Piston Gas Compression (LPGC), in which a rising liquid column, supplied by a pump, acts as a reciprocating piston in a compression chamber. This setup conveniently allows for liquid spray injection to cool the steam upon compression and alleviates limitations on the pressure ratio. By using the same water as the liquid in the LPGC, any temperature rise is compensated by the evaporation of liquid, resulting in more steam with a lower temperature. A numerical model of this type of compressor was made in which dynamics were modelled down to individual droplets. This simplified approach provided insight into the compression path with such liquid injection and allowed the approximate determination of the required amount of spray. Results showed that the injection could cool the vapour adequately even for high temperature lifts. The LPGC was subsequently incorporated into a single-stage heat pump cycle and compared the results for other fluids using ordinary compressors. These results showed large CoP improvements of 15-25 % CoP and low discharge temperature. With that, it was shown that an environmentally friendly fluid could be used in a simple single-stage configuration and still provide the best performance compared to any other fluid.

Flat plate heat exchangers are widely used in industrial and domestic applications. Industrial plate type heat exchangers generally operate in the turbulent flow regime. Although, increase in flow speeds leads to higher transport of heat, it also causes a rise in the pressure loss which is undesirable. Therefore, to combat the problem of high pressure drop, this thesis explores the use of a passive enhancement technique to improve heat transfer. The aim of this thesis is to experimentally investigate the effect of dimple-protrusion surfaces in a counter flow type heat exchanger. The flow behavior is studied using Laser Doppler Anemometry and the local heat transfer characteristics are investigated with the help of Infrared thermography. The average Nusselt number and friction factor data is compared with those of a flat plate and it is found that the use of dimple-protrusion surfaces provide maximum improvement in the performance of the heat exchanger by 21% in the laminar-to-turbulent transition regime, at Reynolds number of approximately 2900.

Currently, the energy transition is a topic for discussion and many organizations are taking measures to reduce the effects of climate change. Armed forces are exempt of these new regulations on the grounds of national security, but some have already started taking steps to reduce the amount of harmful emissions. Due to the high efficiency and advantages that fuel cells present, the aim of this master's thesis is to study their feasibility on board of a naval surface vessel, testing it in a concept design. This report consists of two main parts. The first part tries to find the most suitable combination of naval surface vessel, type of fuel cell, and type of hydrogen carrier. It is concluded that the types of naval surface vessels that could benefit the most from the use of fuel cells are frigates and mine warfare vessels, in order to reduce their acoustic signatures; and offshore patrol vessels (OPVs), due to their constant base load, because it is a type of ship that is mostly cruising or patrolling. Solid oxide fuel cells (SOFCs) are here considered to be the most promising type of fuel cells for naval surface vessels. This is not only because of their high efficiency, but also due to their ability to internally reform hydrogen carriers, making them more versatile. Other fuels than pure hydrogen can therefore be selected, which leads to the choice of ethanol and methanol as best candidates. The latter has already shown good performance when combined with SOFCs and is largely available worldwide. Next, in the second part of this report, the concept design of an OPV using SOFCs fuelled by methanol is tested. On a systems level, the integration of SOFCs adds multiple elements and complexity to the power plant of the concept design. Moreover, since the SOFCs are only used to generate the base load needed to reach cruising speed and its auxiliary power, a peak power source is needed to reach higher speeds. After having considered batteries, diesel engines, and methanol engines, it was concluded that methanol engines provide the highest operational flexibility, on top of being the lightest combination. When comparing the concept design to the reference design, they both score similarly in terms of redundancy and they both fulfil the same design requirements. In terms of operational capabilities, the concept design can sprint for less time due to the difference in efficiency of the power source used to cruise (fuel cells) and to sprint (methanol engines) and does not have the ability to extend its range above the design requirement, opposite to what the reference design can. The use of a SOFC-based power plant shows a reduction in CO2 emissions between 13-23% depending on the type of mission, a 100% reduction of SOx and PM due to the use of methanol as a fuel, and a reduction of at least 68% in NOx emissions.

The continued development of improved algorithms and architecture for numerical simulations is at the core of increased computational performance and, therefore, the ability to perform more complex and precise numerical simulations in less time in areas such as Computational Fluid Dynamics. Employing faster algorithms on more efficient processing units, such as Graphics Processing Units (GPUs), can reduce not only the time spend per simulation but also the energy required to perform these computations as well. This will be of significant benefit to different areas of research and engineering and through improvement achieved in these to society at large as well. As simulations grow in dimensions and accuracy the wall clock time is bound to increase substantially, reaching days and potentially months depending on the parameters and geometry of the chosen simulation. The performance of different finite difference solvers with different degrees of optimization on different types of compute hardware was investigated and the achieved speedups assessed. Specifically, one serial CPU-based solver was presented as a baseline, which was then transitioned to a GPU-based solver. This in turn was then optimized further with regards to improved memory redundancy. To make comparisons fairer all of the solvers used the same temporal and spatial discretization techniques. Further, a benchmarking scenario was proposed to be used for the different solvers across used hardware, including the relevant geometry, gird, and initial and boundary conditions. The speedups between the different solvers were observed and contextualized with regard to the effort that went into implementing the solvers and the capability and cost of the used hardware. The speedups at different problem sizes were investigated with the aim to establish how the performance gain from parallelizing and optimizing solvers scales with the chosen number of grid points and therefore the computational load. Very significant speedups were achieved between the regular CPU solver and its GPU implementation, clearly showing the possible performance gains when moving from a serial to a parallel implementation running on an accelerator. The speedups between the two GPU-based solvers were more modest but still significant when considering the possible time spend on one simulation, depending on the chosen number of grid points. Finally, an additional performance analysis was performed on two Navier-Stokes, one of which was the optimized version of the other, to investigate whether the performance increases were in line with prior findings and what magnitude of a reduction of wall clock time was possible for a state-of-the-art finite difference Navier-Stokes solver.

The optimization of heat transfer in turbulent upward pipe flows is a very common problem in engineering, due to the wide range of applications. However, this set-up is usually categorised as mixed convection flow, which means that gravity plays an important role. Sometimes, it might lead to heat transfer deterioration. This research will simulated three different physical flow conditions gained by Shehata et Al. [3]: turbulent, sub-turbulent and laminarizing. The model will be constructed with Open FOAM using two different approaches: RANS and LES. The former is applied to a two-dimensional geometry, whereas the latter is employed for a 3D cylinder mesh. For both of them air physical properties are implemented as function of temperature and the Boussinesq approximation is selected to forecast density variations. Results is an assessment of RANS and LES differences and which one is more accurate, comparing normalized temperatures at axial locations to real experimental data. In the end, the role of gravity is studied, showing laminarization and using the sub-turbulent case to demonstrate how the presence or the absence of buoyancy forces influences heat transfer.

An energy transition is needed in order to combat climate change. With the rise of intermittent renewable energy, a need for energy storage is also inevitable. Carbon dioxide electrolysis is a potential solution as CO2 emissions can be recycled and subsequently converted for energy storage. However, the technology is rather new and research has yet to be conducted in this field. An important aspect is the temperature within an electrochemical cell, especially when scaling up. An increase in temperature can benefit the performance of the cell, but it also has downsides. Hot-spot formation with non-uniform reaction kinetics and thermal sensible components can have a great influence on the life-time of the cell. For that reason, a modeling study on the heat generation within carbon dioxide electrolysis systems is done. Different volumetric gas flow rates of carbon dioxide have been considered for two geometries: the membrane electrode assembly (MEA) and the gas diffusion electrode (GDE). The model considers three separate models: a mass model, electrochemical model and thermal model, and operates at a fixed current. The finite difference method is applied using Python 3.0 to solve the relevant conservation equations. Furthermore, the model includes different material layers, where the materials and dimensions are based on recently done experiments. The model showed that irreversible losses caused by the activation overpotentials are the biggest contributor to the total heat generation. Reversible heat also contributes to the heat generation, where heat is required in the anode and heat is generated in the cathode. Furthermore, within the cathodic catalyst layer most heat is generated. Joule heating caused by ohmic losses has proven to have negligibly impact on the total heat generation. As a result, the hot-spot is located within the cathodic catalyst layer for both geometries. Due to the additional electrolyte in the GDE, the hot-spot does not reach the membrane, in contrast to the MEA. Besides, different results in the y-direction are observed for the volumetric flow rates. For both geometries, the hot-spot is located at the inlet for 10 ml/min and in the middle for 100 ml/min. From the analysis, the GDE is more favorable as less heat is expected and the hot-spot does not reach the membrane. The sensitivity analysis showed that the thermal conductivity is of great importance.

Nowadays, climate change and global warming phenomena are becoming more and more serious issues. In order to sustain the enormous worldwide energy demand, society consumes a high amount of fuel, resulting into the steep increase of the level of CO extsubscript{2} in the environment. Therefore, the massive greenhouse gases emissions in the atmosphere, generated by burning fossil at a great pace, are the main reason behind the previously mentioned phenomena. Heat transfer augmentation methods can considerably contribute to the decrease of fuel consumption, resulting into a reduction of the greenhouse gases emissions. Therefore, this can be an effective approach to tackle the climate change and global warming phenomena. Particularly, rough surfaces are a well known heat transfer augmentation technique. Such surfaces induce turbulence and thereby the flow is well mixed. This mechanism assists convective heat transfer and as a result, heat transfer is augmented. In addition, buoyancy-influenced turbulent flows frequently occur in many engineering applications. These flows combine natural and forced convection which are due to buoyancy and the bulk flow respectively and contribute both to heat transfer. Particularly, buoyancy-aided flows can promote laminarization and therefore heat transfer deterioration. The main focus of this study is to examine the impact of surface roughness and buoyancy effects on turbulent heat transfer. Initially, a 3D rectangular channel is considered with the streamwise, wall normal and spanwise dimensions being 5.63 $ imes$ 2 $ imes$ 2.815. Subsequently, two different wall roughness geometries are constructed. Both of them have a sinusoidal shape, however the direction of travel is in the streamwise direction for the one and in the spanwise for the other. Moreover, the surface roughness is placed on the top and bottom isothermal walls of the geometry. Regarding the space and time discretization, central differences are used for the former one and second order Adams-Bashforth for the latter one. Finally, the immersed boundary method is utilized in order to incorporate the surface roughness. A series of direct numerical simulations is performed to gain an insight on how surface roughness and buoyancy forces affect the heat transfer. The results display that both roughness schemes enhance heat transfer. Particularly, the Reynolds stresses show an increase in both rough wall cases, signifying that mixing is improved. In addition, the turbulent heat flux as well as the Nusselt numbers also exhibit a growth for both streamwise and spanwise orientation, implying that heat transfer is augmented. Comparing the streamwise and spanwise orientations with each other, both Reynolds stresses and turbulent heat flux graphs are significantly higher in the streamwise roughness case. Moreover, the streamwise roughness is enhancing the Nusselt number approximately 1.8 times more than the spanwise roughness for the zero-buoyancy case and approximately 1.4 times more for the buoyancy-aided scenario. Noteworthy is the fact that, the results show that the buoyancy-aided case predicts larger Reynolds stresses, turbulent heat flux and Nusselt numbers for all of the surfaces.

By placing multiple Peltier elements in a linear arrangement while two water flows run past the elements, a temperature increase can be realised in one flow while the other flow is cooled down. In this study the heating of domestic hot water with Peltier elements as solid state heat pumps, and a heating network was investigated. A numerical model that solves the thermal energy balance within the Peltier elements was derived to describe the internal temperature distribution of the Peltier element, and its interaction with the domestic hot water and the heating network. The model was used to simulate the performance of 40 Peltier elements in a custom designed Peltier Heat Exchanger. Experiments were run to validate the numerical model. The numerical simulation of the temperature distribution within a Peltier Heat Exchanger and the temperature distributions observed in the experiments were not in agreement. The model input parameters Seebeck coefficient, resistance, thermal conductivity and a relation for the Nusselt number were re-evaluated using the experimental results. After the adjustment of the model input parameters, the new simulation results were able to accurately describe the temperature distribution with the Peltier Heat Exchanger. The Peltier Heat Exchanger was able to deliver domestic hot water with a COP between 1.2 and 1.8 depending on the flow speed of the domestic hot water and the heating network. The COP can potentially be increased by using Peltier elements with a higher Seebeck coefficient.