With the adoption of the Paris Agreement, 196 countries worldwide committed to the limitation of the global temperature rise. In order to achieve this goal more energy needs to be produced in a sustainable way. However, the industrial sector is still mainly fossil driven and therefore has to adapt to be able to utilize sustainable produced power, which most often is in the form of electricity. More than a quarter of the total heating demand is in the 100 ◦C to 200 ◦C range. In this temperature range heat pumps are a strong alternative to fossil fuels. Heat pumps can absorb energy from a low temperature heat source and deliver it at a higher, usable temperature. Various technologies for waste heat recovery were investigated in this thesis. It was identified that existing heat pump technologies are suitable to upgrade waste heat, but are limited to lower temperatures of around 120 ◦C. This limitation is mostly due to the high compressor discharge temperatures, which degrade the lubrication oil. Compression resorption heat pumps utilizing wet compression (CRHP’s) limit the superheating during compression and are able to operate oil free, because the working fluid acts as a lubricant. This increases the achievable compressor discharge temperature. The wet compression however is not yet a mature technique and an isentropic efficiency of 70% is required to be competitive with existing technologies. Absorption cycles show promising results for upgrading waste heat due to their non-isothermal heat source and sink, which can be matched to the waste heat temperature. At the Process and Energy lab experiments have been performed on a wet compressor using an ammonia water mixture. This thesis proposes a new method of analysing existing experimental data through a cycle energy balance model. In order to create a model of the experimental setup, four limitations of the setup were identified. First the influence of the gap seal flow, which is the flow from the high pressure to the lower pressure side of the compressor. Second, the mixture inside the compressor can not be assumed homogeneous, which means that both phases are not in equilibrium. Third, there is cooling oil flowing through the compressor housing which cools the process side, this results in a non-adiabatic compression. Finally the pressure drop on the high pressure side is not measured, resulting in an error when calculating the composition of the working fluid. In order to model these limitations a model of the experimental setup was created in Aspen Plus. This model was supplemented with Matlab code to account for the non-equilibrium compression as well as the pressure drop and gap seal flow. Empirical relations were used to determine the heat and mass transfer between the phases during compression. The isentropic efficiency of the modelled compressor was varied until the output matches the input indicating that the steady state solution has been found. The influence of the non-adiabatic compression and the gap seal flow seem to have a significant impact on compressor performance. It was found that the compressor has the highest volumetric and isentropic efficiency when the inlet vapor quality is around 0.85 and the performance decreases with higher vapor qualities. Isentropic efficiencies of up to 0.88 were calculated. The results were compared against previous analysis of the same experimental data which used different assumptions and did not consider the whole cycle. Finally, a case study was performed to analyse the applicability of heat pump technology to upgrade waste heat in a paper recycling plant. A conventional vapor compression heat pump (VCHP) and an electric boiler were compared to a CRHP. To deal with the uncertainty of wet compression performance a range of isentropic efficiencies were considered as well as different ammonia concentrations. The CRHP proved to be energetically and economically viable and outperformed both the VCHP and electric boiler in this case study.

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.

Driven by the need to reduce the destructive and irreversible effects of global warming caused by greenhouse gas emissions, the world is transitioning away from fossil fuels towards renewable alternatives. This transition brings the growing challenge of intermittency, as the availability of renewable energy from wind and solar fluctuates. This creates a big challenge for the chemical industry, which still relies on a continuous supply of energy and materials. Therefore, the chemical industry must adapt by using flexible processes capable of handling these fluctuations.

One application of flexible chemical processes is blue hydrogen production. Hydrogen is essential for decarbonizing hard-to-abate sectors such as heavy transport, steel, and chemical industries. While green hydrogen, produced from renewable electricity, offers a zero-emission solution, its supply is typically variable due to the intermittency of renewables. Flexible blue hydrogen production, made from natural gas with carbon capture and storage, can provide a reliable back-up supply, ensuring a stable supply of hydrogen for industrial processes with steady demand. By integrating flexibility into blue hydrogen production, the chemical industry can enhance system stability and support the transition to a sustainable hydrogen economy.

The aim of this research is to evaluate the potential of flexible natural gas reforming with carbon capture and storage to stabilize the intermittent supply of green hydrogen, ensuring a stable supply of hydrogen for downstream processes. This is done through a case study where blue hydrogen production compensates for fluctuations in green hydrogen generated from offshore wind energy, with limited hydrogen storage capacity. Using a hypothetical large scale ammonia synthesis plant in the port of Rotterdam as the downstream process. This research identifies process uncertainties, uses strategies to enhance flexibility, and quantifies their effects on process efficiency, costs and emissions.

To evaluate the potential of flexible blue hydrogen production, three case studies were simulated using Aspen Plus V12. The first case modeled a blue hydrogen plant operating continuously at maximum capacity (22.9 tons/h). This was used to clearly define the process steps needed for blue hydrogen production, serving as a benchmark for comparing continuous and flexible operations. In the second case study, an uncertainty is introduced to which the plant needs to adapt to. This uncertainty is modeled using hourly data from the Hollandse Kust Noord offshore wind farm, which supplies electricity to electrolysers with limited hydrogen storage capacity. The fluctuating green hydrogen output (0-11.3 tons/h) and steady hydrogen demand for ammonia synthesis (22.9 tons/h) determined the hourly blue hydrogen production. Multiple steady-state simulations were made in Aspen to model the plant at varying throughputs. In the last case, increased wind power output required the blue hydrogen plant to adapt with higher volume flexibility. An operating envelope of the blue hydrogen plant was developed to find the bottlenecks, and design strategies were applied to increase volume flexibility.

Results show that flexible blue hydrogen, using autothermal reforming with a gas heated pre-reformer, can effectively stabilize fluctuating green hydrogen production. The plants volume flexibility can be increased through design strategies such as selecting inherently flexible equipment, storage for intermediate production and using techniques like inert gas for load regulation. But there is a trade-off between flexibility and cost. The plant produces hydrogen at the lowest cost when operating continuously at maximum capacity, with a levelised cost of hydrogen (LCOH) at 3.19 €/kg. Increasing the volume flexibility of the blue hydrogen plant too much resulted in a LCOH of at least 4.02 €/kg, making alternatives like hydrogen storage a cheaper option for balancing out the intermittent supply of green hydrogen. However, when operating flexibly within its base volume flexibility the LCOH is cost effective compared to some alternatives as it increases only slightly to 3.47-3.57 €/kg. Mainly due to underused CAPEX, but also because of transient state losses and reduced efficiency at lower capacities.

This research shows the potential of flexibility in natural gas reforming processes and how it can play a key role in future energy systems. While there is still much to learn, integrating flexibility into the chemical industry enables it to adapt to the ever growing intermittently available feedstock and energy.

Ocean Thermal Energy Conversion (OTEC) is a renewable energy technology (RET), that harnesses energy from the temperature differences between warm surface and cold deep-sea water. OTEC can generate a continuous stream of renewable electricity, functioning as a baseload energy source. To achieve this the ocean water temperature difference must be at least 20°C, favouring locations close to the equator where surface water temperatures are typically higher. Small Island Developing States (SIDS) such as Aruba have been identified as potential markets for OTEC, as many of them are located within such regions and exhibit favourable conditions for OTEC.

OTEC has the highest ocean energy resource potential of all ocean energy technologies. However, of the 44PWh/year in global resource potential very little is being harnessed. With OTEC currently in a pre-commercial phase it has faced challenges advancing to the commercial phase. A large contributing factor to this is a lack of financing and government support for the technology. The technology has a high capital cost with a relatively modest amount of operational plants built to date, providing a limited track record. Furthermore, on smaller scales the technology is generally not economically viable as it experiences considerable economies of scale, becoming substantially more economic with larger plant capacities. This results in a phenomenon known as the “valley of death” where smaller pre-commercial OTEC plants are not commercially attractive but results from such facilities are needed to convince financiers that the risk of building such plants is manageable.
To overcome this “valley of death” research exploring the technological and economic feasibility of implementing OTEC is vital to bolster confidence among investors and governmental bodies. This thesis project aims to contribute to this by conducting a techno-economic, power system model and stakeholder and institutional analysis exploring OTEC’s implementation in Aruba with the main research question:

Is it technically and economically feasible to implement OTEC in Aruba’s energy system and if so what technical, economic and social factors play a role?

The research is conducted using power system modelling as well as qualitative analysis. A concep- tual model of Aruba’s power system based on fully renewable technologies has been developed in a modelling and simulation tool. In this work on and offshore wind, land-based utility scale and floating PV and OTEC are analysed with Battery Energy Storage System (BESS) for storage capacity. The model has been formulated as an optimisation of a generation problem to assess cost-optimal solu- tions for generation investments to meet demand while satisfying all constraints. This is firstly done for a reference scenario in 2030, 2040 and 2050 and subsequently for alternative scenarios in 2050. Based on these optimisation and stakeholder and institutional analysis results, the feasibility of OTEC’s implementation in Aruba is evaluated and recommendations are provided on whether and how OTEC could be implemented...

Variable green energy sources were sought to supply the growing demand for energy without impacting the environment. Wind and solar energy are at the forefront of the energy transition. However, their intermittent nature poses a challenge that necessitates the development of energy storage technologies.
Several technologies were studied over the years including pumped hydro energy storage, compressed air energy storage, electrochemical energy storage, and pumped thermal energy storage.
Pumped thermal energy storage provides a mean to store excess electrical energy in the form of heat by employing a heat pump cycle during the charging process and a heat engine cycle during the discharging process. There are multiple variations of pumped thermal energy storage cycles of which Rankine and transcritical cycles. Unlike Brayton cycles, Rankine and transcritical cycles typically operate at low-temperature levels < 200o𝐶 which facilitate their
integration with low-temperature waste heat in order to boost their round trip efficiencies even beyond 100%. Therefore, the focus of this thesis was to model and optimize Rankine and transcritical thermally integrated small scale pumped thermal energy storage.
Critical to the storage system’s efficacy are the performances of its key components: the compressor and expander. Geometric models were developed and validated for these components, facilitating the determination of their isentropic efficiencies and their variation with pressure ratio and rotation speed.
Additionally, a small-scale pumped thermal energy storage system model was developed to study the system performance. The choice of working fluid and operating parameters were guided by both a simplified optimization scheme and a multi-objective approach utilizing the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II). This yielded 𝑅13𝐼1 as the optimum working fluid with source temperature 𝑇𝑠𝑜𝑢𝑟𝑐𝑒 = 80o𝐶 and storage temperature 𝑇𝑠𝑡𝑜𝑟𝑎𝑔𝑒 =140o𝐶. This configuration led to a transcritical heat pump charging cycle and a subcritical heat engine discharging cycle employing pressurized water as the storage medium.
Consequently, the compressor and expander geometric models were integrated into the pumped thermal energy storage system model working with 𝑅13𝐼1 at the source and storage
temperature mentioned earlier which yielded a round trip efficiency of 𝜂𝑟𝑡 = 93%, energy density 𝜌𝑒𝑛 = 12𝑘𝑊ℎ𝑟/𝑚3, and exergy efficiency 𝜓𝑒𝑥 = 29%.
Finally, a case study was demonstrated with the integrated cycle employed in a Dutch household solar system where dual electric and thermal panels are employed for the electrical and heat energy input in the pumped thermal energy storage. The system was developed for a 1𝑘𝑊 electrical input from the solar system to be stored for further use during off peak hours.

Currently, there are optimization models that are able of modeling building renovation, but their scope is limited only to the heating system. There are also models that consider interactions between different energy subsystems, but they lack the ability to simulate building renovation. Having those two things combined would be beneficial as the impact of renovation on the power system might be significant.
The goal of this thesis is to assess the impact of building renovation on the energy system. It was done with the use of Euro-calliope model, which is capable of minimizing the cost of the whole energy system. In the current state, Euro-calliope model does not offer the chance to renovate the building stock. Therefore, the aim of this work is to introduce the building renovation option subject to the software objective function and reshape, when necessary, the heating sector.
The main outcome is that the heating sector significantly affects the distribution of power generation sources as most of heat is supplied via heat pumps. The penetration of renovation increases the fraction of energy generated by photovoltaics in the energy mix. However, when it comes to absolute values, in all scenarios wind farms are dominating.
The cost-optimal renovation always results in a higher renovation level than the currently present renovation levels. However, those levels are usually lower than the currently imposed local renovation standards. Moreover, the renovation has a positive impact on decreasing the variability of the system costs for scenarios with low renewable supply.

Industrial refrigeration systems are known to consume approximately 17% of electrical energy, a figure that is projected to rise in the future. This high energy consumption contributes to global warming and environmental degradation since conventional sources of energy are typically utilized for electricity generation. Moreover, the energy-intensive nature of industrial refrigeration systems leads to increased costs for major food and beverage industries. Consequently, optimizing the energy efficiency of these systems becomes crucial.
In this research, the application of Digital Twin (DT) technologies was explored, which have demonstrated effectiveness in various areas such as supply chain streamlining and system optimization. By combining physical and virtual spaces, DT and big data analytics can facilitate energy performance evaluation and optimization. The literature review identified three categories of DT models: physics-based, empirical, and data-driven. Considering their accuracy and efficiency, empirical models were recommended for developing DT models, while data-driven models proved useful for performance prediction applications. It was recommended to establish empirical equations based on correlation analysis by adjusting higher degree terms for accuracy. Additionally, input-output parameters for the DT should be tailored to the specific application and equipment. The literature study showed the possible identification of energy performance deviations, their root causes, and potential optimizations, including equipment optimization, load sharing among parallel equipment, and optimization of condenser set points and defrosting time.
This thesis research focuses on three industrial refrigeration plants: the Verkade Plant, the LST Plant, and the GIST Plant. For the Verkade Plant, empirical models were developed and validated for the screw compressor, evaporator, and evaporative condenser. An algorithm for condenser optimization was proposed and tested, while deviations in evaporator performance were analyzed. Similar models were developed and validated for the LST and GIST Plants, enabling the prediction of equipment performance. The predicted results were compared to actual plant performance, and deviations were carefully examined. Furthermore, optimization techniques were applied to improve equipment efficiency.
The thesis research findings indicate that the empirical models for each equipment piece at the Verkade Plant achieved an accuracy within a 5% error range, suggesting their suitability for analyzing the other two plants. The proposed condenser optimization algorithm has the potential to annually save 7% of energy, resulting in savings of 32 MWh of electrical energy and 11 tonnes of CO2 emissions. The application of the proposed optimization techniques to the LST and GIST Plant resulted in a significant reduction in energy consumption. It was determined that these techniques can achieve savings of approximately 13% and 14% in total energy consumption, corresponding to 200 MWh and 170 MWh of electrical energy, as well as 70 tonnes and 60 tonnes of CO2 emissions, respectively. These energy savings contribute to the reduction of CO2 released into the atmosphere, aligning with the goals of the Paris Agreement. Consequently, this research offers valuable insights into mitigating global warming through the optimization of industrial refrigeration systems using DT technology.

Energy efficiency is a key goal for the Quooker system. To further increase the energy efficiency of the Quooker system, this study investigates a possible heat integration system where the waste heat from the refrigeration cycle for chilled drinking water is implemented to preheat water before entering the boiling water reservoir.
Due to the intermittent nature of both the supply of heat, which is coupled to the control scheme of the chilled water reservoir and the demand for heat, which is determined by the user, a thermal storage system is required. Literature showed that the best refrigeration system for this application was a vapour compression system using a natural refrigerant such as isobutane. The most efficient heat storage could be done using organic phase change materials (PCM). Using a PCM allows the system to retain more energy in the same volume due to the latent heat in the system. To enhance the heat transfer between the fluid streams and the PCM, a fin-and-tube heat exchanger concept was designed. This concept, coupled with existing Quooker system demands, leads to a preliminary set of design requirements as well as a set of variables left to be optimised by modelling. The heat transfer from the refrigerant to the tubes was modelled using known correlations for condensation in tubes. The heat transfer between tubes and fins was modelled using a two-dimensional finite difference scheme. The heat transfer between the tubes and the water was modelled using forced convection models. The models gave dimensions for the size of the PCM container, the number of passes for each fluid stream and the thickness and spacing of the heat transfer fins. An experimental setup based on the optimal design was created to validate the models. The results showed that PCM storage is an effective manner to store thermal energy. Heat transfer was significant in the regions surrounding the tubes. Further away from the tubes, the fins did not provide enough heat transfer to utilise the whole storage capacity effectively. In its current design state, the system would have an economic payback time of around 20 years. With small design improvements, such as increasing the fin thickness and decreasing the fin distance, the payback period can be brought down significantly. The added product value from being a more efficient product makes the concept promising for future implementation.

The rise in temperature attributed to human CO2 emissions and the escalating energy needs of society necessitates the development of clean energy production. Solar and wind energy, both renewable sources, have emerged as cost-effective alternatives to conventional fossil fuel systems. They now account for a substantial portion of the world's electricity generation (IEA, 2022). However, their intermittent nature poses a challenge to their reliability. To overcome this, the implementation of grid-scale energy storage systems is crucial. Such systems can store excess energy produced during peak periods and release it during low-generation or high-demand periods, ensuring a stable and dependable power supply to the grid.

Pumped Thermal Energy Storage (PTES) is one such type of promising grid-scale storage solution based on the concept of storing electricity in the form of heat. These systems are not reliant on rare earth metals, are not restricted by geographical location, and are relatively economical over their lifetime. They employ a heat pump cycle for charging and a heat engine cycle during times of discharge. Often, in the thermodynamic modelling of PTES systems, a fixed value of turbomachinery efficiency is assumed. This approach holds well for the first estimate of performance, but for better accuracy and further analysis, meanline models could be used to arrive at the efficiency value and preliminary geometric design. Hence, this work presents a method for developing meanline models for centrifugal compressors and radial inflow turbines. Modelling techniques and guidelines from the literature are noted and presented here. The accuracy of these models is dependent mainly on the loss models used. Using suitable models selected from the literature, a fair agreement was found between the meanline model's prediction and experimental data from open literature, validating the methodology.

An essential function of energy storage is to provide load flexibility, meaning its charging and discharging cycles must adjust to match the net load curve. As a result, the turbomachinery would need to operate under off-design conditions to meet these demands. Therefore, this report introduces an approach to extend the PTES model by Radi (2023) for off-design operation based on turbomachine performance.

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.

At the moment, Tata Steel emits 12.6 Mt CO2 per year while producing 7.2 Mt steel per year. To reduce these emissions, Tata Steel has decided to replace the blast furnaces with direct reduced iron (DRI) plants in combination with reducing electrical furnaces. The DRI plants will first operate with a 100% natural gas feed. Whenever green hydrogen becomes available on the market, the natural gas will gradually be substituted with green hydrogen, reducing direct CO2 emissions. Producing steel using 100% green hydrogen as the reducing gas, called green steel, comes along with an awkward problem regarding the carbon content of the DRI. Green steel has a carbon content of 0%, while carbon is essential for multiple aspects of the production process. Furthermore, the metallization of the DRI is a critical parameter in the production process. Thus, the following research question is established: ”What is the influence of the ratio of hydrogen to natural gas inserted in the direct reduced iron plant on the performance of the reactor?”

To answer this research question, an extensive literature review is performed to gain knowledge of the reduction process, reduction technologies, and the existing mathematical models of the DRI plant. Furthermore, a multiscale mathematical model is made of the shaft furnace of the MIDREX plant. This model uses a grain-based pellet model, which incorporates the morphological structure of the pellets during the reduction process. The shaft furnace is modelled as a 1D model with multiple zones, in which the local energy, mass, and momentum equations are solved. However, due to the time restrictions of the thesis period, only the two reduction zones of the shaft furnace are incorporated. Hence, the shaft furnace model lacks the transition and cooling zones.

The shaft furnace model is compared to a real operating MIDREX plant named ”Gilmore”. The simulation results are validated against the simulation results from literature and the real plant data. The average relative error of the simulation results compared to the Gilmore plant is 14.4%. The most significant error can be attributed to the carbon weight fraction in the solid. This is the result of the missing transition and cooling zones, as most of the carburization occurs inside the transition zone. Neglecting the carbon weight fraction, the average relative error is 9.2%.

Increasing the ratio H2 / CH4 in the feed of the MIDREX plant results in an increasing H2 / CO ratio of the reducing gas entering the shaft furnace. Five cases with different H2 / CO ratios are simulated to answer the research question. The metallization of the DRI is affected by two different phenomena. First, increasing the H2 / CO ratio results in a larger gas input mole flow for the same input pressure, which is the effect of a smaller pressure drop over the shaft furnace. Subsequently, a larger gas input mole flow results in better metallization, which is the effect of more heat input and a lower gas oxidation degree in the shaft furnace. Second, as the hydrogen content increases, the temperature decreases as a result of more endothermic reduction. The thermodynamics and kinetics of reduction by hydrogen are favourable at higher temperatures, which results in a slow-down of the reduction. At lower temperatures, the thermodynamics of reduction by carbon monoxide is more favourable, realizing more reduction and increasing the temperature. This second phenomenon is predominant for equal input mole flow, resulting in worse metallization when increasing the H2 / CO ratio, as confirmed by literature. Consequently, to achieve equal metallization for a higher H2 / CO ratio, the process gas compressors of the MIDREX plant will consume more electrical energy. To conclude, substituting natural gas with hydrogen does have its disadvantages, but it is highly necessary to become CO2 neutral in the future.

For further research, the addition of transition and cooling zones to the shaft furnace model is recommended, allowing investigation of the carburization of the DRI. Furthermore, the shaft furnace model is extremely useful for implementation in a complete MIDREX plant model. Such a model could be used to investigate the total CO2, energy, and material balance of the plant for different H2 / CH4 ratios of the feed of the plant.

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.