Within the context of hydrogen combustion, the trapped vortex combustor (TVC) combined with a Rich-Quench-Lean (RQL) combustion strategy holds great promise for achieving ultra-low emissions and advancing sustainable combustion technologies. However, ensuring thorough and sufficient fuel-air mixing before the completion of the chemical reactions currently remains a critical challenge. This study focused on addressing this problem by exploring hydrogen’s injection temperature as the potential solution. Therefore, a combination of 1D simulations and Large-Eddy simulations were conducted. Subsequently, the role of this temperature modification on the chemical reactivity was evaluated, and the overall impact on the RQL's effectiveness was assessed. The results indicated that lowering hydrogen injection temperature from 300 K to 150 K reduced chemical reactivity by 15% to 25%. However, this reduction was insufficient to suppress or alter the combustion mode within the cavity significantly. Nevertheless, the overall temperature reduction within the TVC led to a significant decrease in NOx emissions of about 25%

This thesis explores the dynamics of hydrogen-enriched methane flames in a swirl-stabilized combustor with axial air injection, a configuration crucial for advancing low-emission combustion technologies. The study focuses on enhancing the understanding of flame behaviour under varying hydrogen enrichment levels, with particular attention to the effects of heat loss and strain on flame shape, mixing, and emissions. Utilizing computational methods, the research investigates key operating scenarios from the APPU project, refining thermal boundary predictions through an improved Heat Resistance Tuning approach. Additionally, it assesses the performance of a necessary flashback-prevention method, Axial Air Injection, quantifying its impact on mixing and flame shape, including their effects on temperature and pollutant formation, with varying results based on the level of hydrogen enrichment in the fuel. The results offer valuable insights that could inform control strategies for the stable and efficient operation of hydrogen-enriched combustion systems, supporting the development of fuel-flexible and environmentally sustainable propulsion technologies.

The motion of liquid metals is described by the equations of magnetohydrodynamics (MHD), that com bine the Maxwell equations and the Navier-Stokes equations. In these type of flows, the magnetic field interacting with the conductive metal induces large pressure losses and unconventional turbulence states such as quasi 2D turbulence, turbulence suppression and flow anisotropy. Currently this turbu lence behaviour can be captured in higher fidelity Computational Fluid Dynamics (CFD) simulations such as Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS), but the high computa tional cost of these simulations make them impractical for industrial applications compared to Reynolds AveragedNavier-Stokes(RANS).However, theeddyviscositymodelswhicharetypicallyusedinRANS are not able to capture anisotropic turbulence states occurring in MHD flows, which results in sig nificant discrepancies in the mean velocity field. Hence, this work presents a data-driven approach to model MHD turbulence. To achieve this time-averaged LES data of annular pipe flow cases at differ ent Hartmann numbers are used to derive corrections for the k − ω SST model. Two correction fields are obtained through a frozen RANS simulation in which the mean LES fields are inserted into the RANS equations. The Reynolds stress anisotropy term is approximated with a modified Tensor Basis Neural Network (TBNN). Moreover, for modelling the turbulence production correction a Scalar Basis Neural Network (SBNN) is proposed and compared to a Sparse Algebraic Regression using the SpaRTA approach. The resulting data driven models are able to reduce the error of the Reynolds stress anisotropy values and the mean flow velocity fields, and can generalise to annular flow cases with different Hartmann numbers from those of the training cases.

With climate change posing increasing risks, the Advisory Council for Aviation Research and Innovation in Europe (ACARE) aims to reduce CO2 emissions by 75% and NOx emissions by 90% per passenger kilometer by 2050, compared to a baseline aircraft from 2000. The ARENA project addresses this by developing a waste heat recovery system using aircraft engine exhaust gases, improving fuel efficiency. This thesis focuses on integrating the condenser of such a system into the propulsion unit, aiming to minimize drag from the ram air cooling duct by evaluating different heat exchanger topologies and duct designs.

The study uses the IMOTHEP Distributed fans Research Aircraft with electric Generators by ONERA (DRAGON) concept, a hybrid electric aircraft with two tail-mounted turbogenerators. The research proceeds in several stages. Initially, a multipass-condenser's potential to reduce pressure drop was examined by adjusting the heat exchanger blockage factor per pass, but results showed no reduction in pressure drop.

Next, a lumped parameter model was developed to analyze drag, pressure drop, temperature increase, and ram air duct length. This model evaluated the sensitivity of duct geometrical parameters on the drag recovery factor—a dimensionless number indicating net thrust. Findings revealed that inclining the heat exchanger efficiently increases the drag recovery factor, while the diffuser area ratio has a similar effect but is less space-efficient. The mass flow rate ratio showed less sensitivity, and fin height or pitch had the smallest effect on drag recovery.

Using the lumped parameter model, an optimal preliminary ram air duct design was identified for different spatial constraints. The study found that inline plain tube bundle and flat tube offset strip fin heat exchangers provided more compact solutions with higher drag recovery factors. For large diffuser-blocked area fractions, optimal duct geometry remained independent of heat exchanger type, characterized by a 70-degree maximum inclination angle, a 0.7 mass flow rate ratio, and maximized diffuser area ratio within spatial constraints.

A verification study of the lumped parameter model was conducted using a two-dimensional Reynolds Averaging Navier Stokes (RANS) computational fluid dynamics (CFD) analysis with k-ω SST turbulence and a porous zone to mimic the heat exchanger. The CFD analysis confirmed the lumped parameter model's predictions, with a 0.8% difference in drag recovery factor for optimal duct geometry. Across various geometries, the mean absolute difference in drag recovery factor between models was 1.082%, with a standard deviation of 0.584%.

In conclusion, integrating the condenser in the propulsion unit within spatial constraints results in positive thrust, thus supporting Meredith's 1935[2] claim. This integration reduces net drag and improves overall efficiency, contributing to significant emission reductions in line with ACARE's targets.

This thesis introduces a newly-developed turbulent combustion model, as a next step towards modelling hydrogen combustion in aircraft engines. The proposed model (FGM-ESF) merges the Flamelet Generated Manifold approach's tabulated chemistry with the Eulerian Stochastic Field method's statistical treatment of flame-turbulence interactions at the subgrid scales, which are not resolved in LES. This hybrid model excels in managing complex combustor dynamics, high turbulence, and both premixed and non-premixed combustion modes, all while maintaining computational efficiency. Validated with a lifted turbulent H2/N2 jet flame in vitiated coflow, reflecting typical combustor conditions, the FGM-ESF model produces accurate predictions of mean velocity, temperature, and mixture in close agreement with the experiments. Comparatively, its performance matches the more costly, fully transported chemistry ESF model, showing limited sensitivity to the number of stochastic fields. The balance between computational efficiency and precision in the FGM-ESF model highlights its importance in the advancement of hydrogen-powered aircraft engines.

This study investigated the effect of tangential strain on the stability of perturbed laminar lean premixed hydrogen flames in a counterflow reactants-to-products configuration. Laminar premixed flames are highly susceptible to intrinsic instabilities, including hydrodynamic and thermodiffusive instabilities, which can cause perturbations in the flame front to grow. However, the impact of tangential strain, introduced by velocity gradients along the flame front in a counterflow setup, had not been fully explored in the context of flame stability. The present work bridged this gap by combining the counterflow setup used in previous studies of NOx reduction with the perturbation analysis commonly employed in flame stability research.

Direct Numerical Simulations were performed to study the behaviour of sinusoidal perturbations imposed on the flame front, focusing on the growth rates of these perturbations under two different strain rates (2000 1/s and 4000 1/s). The results indicated that the tangential strain improved the stability of the flame front, as the strain rate led to a reduction in both the maximum observed growth rate and the growth rate after the perturbation reached its peak. The growth rates observed were in the non-linear regime, characterised by continual variation over time. At higher strain rates, the flame front stabilised more quickly, suggesting a strong correlation between strain rate and perturbation growth dynamics. The strain-induced velocity gradients displaced the flame front, reducing its effective curvature and wavelength, further contributing to the stabilisation process.

In addition to the strain rate, the study investigated the effects of varying the amplitude and wavelength of initial perturbations. It was found that the amplitude of the initial perturbation had little impact on the maximum growth rate, but variations in the initial wavelength significantly influenced both the growth dynamics and the maximum growth rate of the perturbations.

Overall, the results provided a comprehensive understanding of how tangential strain affected flame stability and highlighted the importance of wavelength variations in determining perturbation growth rates. These findings provide insights into potential strategies to improve flame stability in practical combustion systems aimed at reducing emissions, such as in lean hydrogen combustion.

TOP contoured nozzles, with large area-ratios, are commonly employed in rocket propulsion systems as they feature an excellent thrust-to-weight ratio. A significant shortcoming to this design is that, during the startup and shutdown transients of a LRE, the internal nozzle flow progresses through a series of overexpanded flow states - Free Shock Separation (FSS) and Restricted Shock Separation (RSS), which produce critical loads associated with SWBLI and asymmetric flow separation. Exacerbated by FSI, this operational phase is known to generate the highest vibroacoustic loads at which payload and vehicle structures are subjected to when the engine is operated at off-design conditions.

Motivated by the importance of understanding how the interaction between the developing flow and the vibrating nozzle walls has an effect on supersonic noise generation and propagation, this work has studied the effect that wall compliancy has on the vibroacoustic loading of TOP contoured nozzles. This is demonstrated by means of cold flow tests carried out in the High Speed Laboratories of the Delft University of Technology on a stiff-walled aluminum nozzle, which serves as a baseline test case, and on a urethane-based compliant walled nozzle. Tests are conducted under comparable flow conditions and test parameters are measured by means of acoustic and optical techniques. Simultaneous recordings are performed and include the nozzle-wall deformation, by means of stereoscopic tracking of tracers on the nozzle lip, the imprint of the near-field acoustic signature, by means of arrays of pressure-microphones, and Schlieren imaging of the jet plume.

Measurement data allows for a Fourier decomposition of the nozzle lip displacement and of the acoustic pressure field in azimuth. Reconstruction of the instantaneous plume development enables the identification of the main flow structures responsible for noise generation.

Comparison of results between the two test articles highlights a different spectral content and directivity pattern. Correlation between the structural displacements and the acoustic signal, together with the use of DMD, quantitatively aids the investigation of how FSI has an impact on the generation of an aeroelastic tone at 180 Hz. Findings suggest that its production is the result of the periodic thickening and thinning of the shear layer owing to the heightened flapping motion of the nozzle lip preceding RSS transition, driven by an intensified shock foot instability.

Recent years have seen an increase in studies focusing on data-driven techniques to enhance modelling approaches like the two-equation turbulence models of Reynolds-averaged Navier-Stokes (RANS). Different techniques have been implemented to improve the results from these simulations. In particular, the main focus has been on overcoming the limitations implied by the Boussinesq assumption. This has been approached by using machine learning techniques as a way of discovering new formulations that could overperform when compared to traditional models.
Despite promising results for steady RANS simulations, little has yet been investigated in URANS applications. In this dissertation, this lack of research will be addressed. The main ideas are then, first, to see how the available information in URANS simulations can be used to improve the anisotropic Reynolds stress tensor prediction, and second if and how this can be done by using a sparse regression technique, whose framework is known as SpaRTA. A procedure involving the triple decomposition of High-Fidelity velocity fields is applied, aiming at finding a model exclusively for the stochastic component of the anisotropy. The test case which is considered is the flow around a cylinder at Re=3900. The High-Fidelity data was collected by running Large Eddy Simulations in OpenFOAM, after which the velocity was split into its different components through Proper Orthogonal Decomposition.
A priori results have shown good performance of the trained models, outperforming the Boussinesq assumption both in the prediction of turbulence componentiality and also on the values of the single anisotropy components.

Large eddy simulation paradigm is employed to analyse the internal flow field of a lean premixed swirlstabilized combustor with axial air injection at both non-reacting and reacting conditions for a methane and a methane-hydrogen fuel mixture. The Thickened Flame combustion model with the kinetic mechanism GRI 3.0 and the detailed chemical kinetics solver SAGE available in ConvergeCFD is employed to simulate the flow. An adaptive mesh strategy is used to maximise the mesh resolution in the flame and boundary layer regions. The numerical results are first validated against in-house experimental velocity measurements obtained via particle image velocimetry, and then leveraged to provide further insights on the flow behaviour. Significant reductions in CO2, CO and NOx emissions are observed when changing the fuel to the CH4/H2 mixture. From a POD analysis is observed that a Precessing Vortex Core is present in both the reacting and non-reacting conditions. Flashback and severe local extinctions are not observed during the simulated time.