The aim of this work is to preliminary model a hybrid propulsion system that integrates fuel cells and a turbo-generator. The model is used to predict the performance of the propulsion system where parameters such as fuel consumption, and component efficiencies are monitored throughout a given eVTOL mission. Based on the analysed performance, the maximum payload the eVTOL can carry is estimated. With a fuel cell voltage efficiency of 43%, an eVTOL of MTOW of 3175 kg and a structural weight of 1905 can carry a maximum of 174 kg as a payload. The eVTOL propulsion system weights approximately 1041 kg, to which the fuel cell and its balance of plant components contributes the highest with 819 kg, where the turbogenerator contributes with 222 kg. According to the models prediction, the payload can be increased to approximately 200 kg , if a compressor efficiency of 85% was used.

The Environmental Control System (ECS) is the largest consumer of non-propulsive energy, accounting for 3-5% of total power consumption. This significant energy demand necessitates the investigation of new ECS architectures, seeking more efficient solutions. A novel electrically driven ECS is presented that combines features of the Air Cycle Machine and Vapor Compression Cycle. The system design is optimized to minimize weight and power consumption for a critical operating condition, i.e., the aircraft is on the ground during a hot and humid day. The optimization framework integrates the thermodynamic cycle, component sizing and detailed high-speed centrifugal compressor design for the refrigerant. A steady-state model of the ECS has been developed using the acausal language Modelica acausal modelling language, and the optimization framework relies on a Python-Modelica interface. The outcome of the simulation proves that the design of a hybrid ECS is feasible. The results show a trade-off between system efficiency and weight. An optimal system design has been identified to minimize the specific fuel consumption for a typical flight mission of single-aisle aircraft, accounting for the power consumption at ground conditions and the weight of the heat exchangers. The selected design is then used to verify the system performance in off-design during standard cruise operating conditions.

Analysing and developing turbomachinery at off-design conditions requires the usage of robust and efficient Computational Fluid Dynamics (CFD) solvers. With the introduction of the computer, many advancements have been made in the field of numerical methods involving these flow problems. These numerical methods are used in order to solve these complex flow structures that are formed due to the interaction between the rotating machinery and the fluid. With the emergence of new design paradigms using computer-aided optimisation, novel solver methods are required which are able to deal with the increase in computational cost and the convergence difficulties following off-design conditions. One of the CFD solvers that is used for turbomachinery design is the open-source software SU2. SU2 is currently developed partially at the Delft University of Technology, where an increase in solver performance with respect to turbomachinery aerodynamics is greatly desired. The current work provides a numerical study of SU2's current performance with respect to turbomachinery analysis, as this is currently unknown.

The current performance of SU2 is to be analysed using steady RANS turbomachinery simulations. The research conducted by Xu et al. \cite{Xu2020} will be used as reference data in order to validate SU2's performance together with data obtained from the CFD solvers CFX and Numeca. The research conducted by Xu et al. resulted in the development of their NUTSCFD solver, which showed strong performance with respect to turbomachinery analysis. Four test cases are set up and used in order to analyse SU2. The test cases that are considered for the numerical study include: the NACA 0012 airfoil, the LS89 turbine cascade, the MTU centrifugal compressor and the 1.5 stage ETH turbine. The first three test cases are validated using the results obtained by the NUTSCFD solver, where the ETH turbine is validated using CFX and Numeca. Following these test cases, SU2's performance is analysed using the residual behaviour. Xu et al. dedicate their performance increase to be the result of the Newton-Krylov method that is implemented in their NUTSCFD solver. SU2 also includes a Newton-Krylov solver, but its performance with respect to turbomachinery is also unknown. A performance assessment with respect to SU2's Newton-Krylov method involving turbomachinery analysis is therefore conducted as well.

The results obtained using the NACA 0012 and LS89 test cases show a discrepancy in solver performance involving SU2. With respect to SU2's Newton-Krylov solver, the NACA 0012 test case shows a reduction in non-linear iterations where this is not found for the LS89 test case. Both results showed however a large difference in performance when compared to the NUTSCFD solver, where SU2's standard solver was also unable to match NUTSCFD. The results obtained following these test cases have led to the development of the MTU test case, where the MTU test case was to be used in order to provide a more accurate comparison between SU2 and NUTSCFD. Instead, SU2 was unable to run the MTU test case, where the solver showed stalling behaviour...

The need for more efficient aircraft has led to the conception of innovative engine configurations, such as the combined-cycle engine proposed by Delft University of Technology or the Water-enhanced turbofan developed by MTU and Pratt & Whitney. The evaluation of the potential benefits of these novel engine concepts requires detailed performance studies considering weight and drag penalties as figures of merit. At present, no weight estimation tools with sufficient level of accuracy and flexibility are publicly available, apart from WATE++, a tool developed by NASA. However, this software is subject to export control restrictions and cannot be used outside the USA. For this reason, the development of a new component-based preliminary engine design tool, "Weight EStimation of gas Turbine engines" (WEST), was started. The goal of WEST is to predict the weight of novel engine architectures with a reasonable level of accuracy, accounting for design parameters like turbine inlet temperature, overall pressure ratio, mass flow rate, and turbomachinery configuration, with a minimal set of geometry inputs specified by the user. A previous work demonstrated that WEST can effectively predict the weight of turbofan gas generators. As only the main components are modeled, the WEST estimates account for approximately 70-90% of the actual engine weight.

The capabilities of WEST were expanded in this study to allow for the design of small-scale turboshaft engines. To this purpose, a methodology to design radial compressor disks was implemented, and successfully verified against FEM results. Regarding the modeling of the complete turboshaft, it was found that the predictions of the tool account for only 60-70% of the actual engine weight. Such result was, however, expected, as WEST does not take into account the particle separator and the integrated gearbox, which may account for up to $30\%$ of the engine's total weight.

The objective of this thesis was to further the validation effort on the SU2 flow solver for non-ideal compressible flows. To do so, an uncertainty quantification infrastructure based on the V&V20 validation standard was developed. To determine whether a model error was present, the different sources of uncertainty were combined and then compared to the error between the SU2 simulations and the experiments. A variety of paradigmatic test cases were proposed which, together, would constitute a robust validation of the SU2 flow solver. Two paradigmatic unit test cases were analyzed; namely, a supersonic inviscid flow and a Mach 2.0 flow over a 2.5 degree wedge. The operating conditions of the experiments were as follows: an inlet total temperature and pressure of T_0=252°C and P_0=18.4 bara, and a back pressure of P_out=2.1 bara, for the first case, and T_0=180°C, P_0=3.5 bara and P_out=1.0 bara, for the second. The solver is able to predict the shock wave angle accurately. This step towards the validation was successful because the calculated total expanded uncertainty of 1.79% is higher the comparison error of 0.57%.In the second part of the thesis, the uncertainty quantification infrastructure was adapted to a test case constituted by more complicated flow features; namely, a supersonic flow through a 5-channel blade row. The computed uncertainties were on the same order of magnitude as in the supersonic inviscid flow test case. The simulations were verified with state-of-the-art CFD software for the quantities pressure and the Mach number. The positive result of the validation represents a step forward in the validation of the flow solver for non-ideal turbomachinery cases. The adaptation of the infrastructure to the cascade blade row paves the way for complex cases and for system response quantities of interest in industrial applications of CFD software, such as efficiency, to be assessed.

The shipping industry has a notable share in global greenhouse gas emissions and other pollutants such as sulphur and nitrogen oxides. Fuel cells and batteries are identified as relatively new technologies for shipping with high potential and hydrogen is also considered as one of the most promising sustainable fuels, especially for smaller vessels. This research contributes to three identified knowledge gaps: (1) the potential of hydrogen propulsion for high-speed craft, (2) the hybridisation of fuel cells and batteries for marine applications and (3) the characteristics of the response of a hybrid fuel cell/battery propulsion system under transient loads. The objective of this research is to analyse these aspects based on a series of time domain simulations of various operational conditions.
A mathematical model of a fuel cell/battery propulsion system is developed in Matlab/Simulink. The developed model is used to analyse the energy consumption for various operational conditions of a test vessel. Based on this analysis, two configurations of fuel cell power and battery energy are selected. If the vessel sails at top speed, the fuel cell power stacks operate at maximum power and the battery operates as power booster. A strong correlation was found between the endurance at top speed and the battery size which is selected. A larger battery has a positive effect on endurance, but it also increases the displacement of the vessel significantly and, hence, required power.
Fuel cells are least responsive and these should be protected against high fluctuations in a short time. A fuel cell can only follow low-frequency transient loads. The battery is required to support in high-frequency load changes. Contrary to the fuel cell, both the battery and PMSM were found to have very favourable characteristics in transient conditions.
Finally, it is concluded that it is feasible to implement fuel cell/battery propulsion on high-speed craft. It is proposed that the fuel cell and hydrogen deliver the majority of the energy and use the battery as power booster and for transient support. Novel energy management strategies can deliver high system efficiencies in both full and part load and this is one of the main advantages of hybridisation.
The implementation of a fuel cell/battery system does, however, come at significant costs in terms of endurance and top speed due to the low volumetric energy density of hydrogen. It should be acknowledged that the functionality of the vessel is reduced. In addition to this, the storage of hydrogen requires some deck space, so the cargo capacity in terms of crew and material is also reduced. Therefore, it is recommended to redefine the user profile of the vessel.

The validation of SU2 for modelling classical non-ideal compressible fluid dynamics will advance the research into efficient ORC turbomachinery design. This study determines the validity of the two-dimensional flow solver for predicting the isentropic expansion of Siloxane MM through a converging-diverging nozzle using compressible Euler equations, adiabatic flow, and the Peng-Robinson equation of state. Two flows with an inlet stagnation temperature of 525K were considered: an expansion from 18.4 bar to 2.1 bar, and an expansion from 11.1 bar to 1.3 bar.  Mach number along the centreline and static pressure along the nozzle surface were used as the direct system response quantities used in the analysis. Experimental data and uncertainty came from the ORCHID, model input uncertainty was quantified using stochastic collocation, and the numerical uncertainty was calculated using the Richardson extrapolation. The conclusions were based on a hybrid of the ASME V&V 20 and Real Space validation metrics, with a novel Engineering Response Quantity analysis based on determining the effects of system uncertainty on performance parameters. The studied SU2 model provide valid predictions for Mach number, and invalid predictions for static pressure. The largest error is in the kernel region, where E_Mach=0.111 and E_Pressure = 112 kPa. Mach number has a maximum simulation uncertainty of 2% at the transition to the reflex region. Pressure has a maximum uncertainty of 3% at the throat. In the context of turbomachinery the simulation uncertainties translate to +/-0.001 and +/-0.02 on a loss coefficient calculated across a theoretical normal shock, for Mach and pressure respectively. Considering +/-0.01 as significant for a loss coefficient the Mach uncertainty is negligible. Input uncertainty is the largest component of the pressure uncertainty, while experimental uncertainty is dominant for Mach. The input parameters which provide the highest contribution to the uncertainty are critical pressure and temperature. The developed infrastructure can be used for expanding the validation of SU2 to different flow cases.

The significant impact of airborne cabin pressurisation and cooling systems on fuel consumption requires new technologies to be investigated. In the pursuit of decreasing fuel consumption while leveraging on the benefits of electrification, a shift was initiated from conventional bleed air driven to electric powered air cycle machines based environmental control systems. The performed research goes a step further by considering an alternative configuration in the form of an electric driven vapour cycle refrigeration unit. The system to be installed onboard a technology demonstrator is integrated at aircraft level and its impact on fuel consumption is compared to that of an electrically driven air cycle machine. Fuel consumption related results show up to 1.62 % trip fuel reduction for a baseline mission of 1000 nm and 12000 kg payload for the technology demonstrator aircraft equipped with the vapour compression cycle refrigeration system as compared to the baseline model.

Prior to the detailed design of turbines, turbomachinery engineers must rely on mean-line and throughflow models to come to a preliminary design. These models are based on empirical loss correlations and are often derived from cascade experiments and numerical analyses that are confined to the subsonic and transonic regime. Axial turbines for rocket propulsion applications are characterised by a near zero degree of reaction and supersonic stator vanes that yield a complex flow field, making the prediction of losses challenging with existing correlations. The goal of this study is to investigate the variation of loss generation in supersonic axial turbine stator vanes with the isentropic exit Mach number. The profile losses will be split into components that can be attributed to different loss generation mechanisms whose relative magnitude may point to where performance improvement can be made. The investigation is performed on stator vanes that are used in the first turbine stage of a 1MN-class gas generator cycle type rocket engine. The stator vanes will be optimised for the profile losses by exploiting a novel adjoint optimisation framework for turbomachinery and the effect on the exit flow field will be investigated. The computational risk will be mitigated to ensure that the feasibility of the research is not jeopardised. The successful outcome of this research will lead to supersonic loss characteristics of axial turbine stator vanes, reduced development costs, increased efficiency levels and pave the way for future work on optimisation methods for turbomachinery applications.

The open-source SU2 suite has been subject to extensive verification and validation studies in the past few years. Through such studies, the ability of the SU2 CFD solver to produce high-fidelity results for external flows has been substantiated by data from numerous testcases. Interest in applying the suite to turbomachinery flow analysis and optimization has been on the rise in recent times. This has led to a significant extension of SU2 capabilities to deal with turbomachinery flows. Evidence of the ability of SU2 to carry out CFD analysis of ideal-gas turbomachinery flows is scarce; the suite has only been applied to a radial-inflow turbine case thus far. The present Thesis documents the first application of SU2 to radial compressor ideal-gas flow analysis. Two testcases are studied: an automotive turbocharger compressor including experimental data shared by MTEE and a mixed-flow Supercritical CO2 compressor including a baseline CFD result. SU2 capabilities are assessed via a solution verification study including a grid convergence study and through a comparison of SU2 results with those of CFX and experimental data for the turbocharger. The assessment is based on major compressor performance metrics: efficiency and pressure ratio. RANS steady-state, second-order accurate simulations are carried out for a single, voluteless compressor channel using the S-A and SST turbulence model with mixing-plane interfaces using non-reflective boundary conditions. The comparison includes an analysis featuring SU2 S-A and SST simulations as well as a three-point speedline comparison featuring SU2 S-A results. The Supercritical CO2 compressor testcase is preliminarily studied, again including results from CFX as well as SU2 for a single operating point. It is concluded that SU2 is capable of arriving to an asymptotically converged solution in the verification study while displaying a convergence rate similar to the theoretical value. In addition, SU2 SST results are in well agreement with simulation results. The speedline obtained using SU2 also matches that of CFX and experimental data to a good extent quantitatively as well as qualitatively. For the S-CO2 compressor the disparities between the solvers are notorious, which is likely due to combination of factors including near-wall mesh treatment in SU2 and the complex geometry of the testcase.

For the past fifty years, there has been a constant increase in the pressure ratio of gas turbines motivated by the need to increase the cycle efficiency. This has moved the operating pressure of gas turbine combustor to be above the critical pressure of jet fuels. This increasing trend in pressure of combustor, places the next generation gas turbines in supercritical regime of majority of jet fuels, making Supercritical Combustion a significant topic of research in the field of gas turbine. Understanding the fluid behavior at and above the critical point provides opportunity for better and efficient combustor design.

The complexity in numerical modelling of supercritical fluids, due to the dramatic property variations, solubility in gas and difficulty in tracking the vanishing interface, requires alternate modelling techniques that are well suited for treating multi-phase systems efficiently. Lattice Boltzmann Methods(LBM) is one such system gaining popularity in the recent decade due to the inherent capability to model complex multi-phase flows. LBM is a hybrid particle-continuum method based on the kinetic theory, which entails solution of the Boltzmann equation for the distribution function of particles properties on a lattice node.

Despite the advantages of LBM, there is considerable gap in effective application of this method as a solution for engineering problems. This research work is aimed to address this issue by creating a single and multi-component solver using LBM and making quantitative comparison with commercial fluid dynamic flow solver, ANSYS FLUENT. The results form created single-phase LBM solver agrees with the results from FLUENT single-phase solution in addition to showing superiority in terms of computational time and resources. In case of the multi-component model, LBM provided accurate results with coarser mesh refinement. A detailed investigation of LBM application for two simple systems has been studied and reported,bthus laying a foundation for future numerical investigation of supercritical fluid modelling.