Space exploration depends on materials that can withstand extreme conditions, particularly for rocket thrusters. Ceramic matrix composites (CMCs) like carbon-carbon (C/C) and carbon-silicon carbide (C/SiC) have been widely used for rocket nozzle applications ,due to their thermal and mechanical properties. However, the demand for materials capable of higher temperature tolerance and reusability has shifted focus to ultra-high temperature ceramics (UHTCs) and UHTC matrix composites (UHTCMCs). Among UHTCs, ZrB₂ stands out for its excellent mechanical properties, oxidation resistance, and lower cost compared to HfB₂. To overcome ZrB₂'s inherent brittleness and enhance properties like densification and oxidation resistance, additives such as SiC and carbon fibers are introduced. SiC enhances densification, controls grain growth, and improves oxidation resistance via the formation of a SiO₂ protective layer, while carbon fibers improve mechanical strength, oxidation resistance, and reduce density. Spark Plasma Sintering (SPS) is a preferred fabrication method for its ability to rapidly densify materials while maintaining fine microstructures.
Although ZrB₂-SiC composites are extensively studied for high-temperature applications, the relationships between sintering parameters (e.g., temperature, pressure, and dwell time) and densification, microstructure, and mechanical properties remain underexplored. This study investigates these correlations using SPS and examines the impact of milling methods—high-energy milling with WC balls versus regular milling with ZrO₂ balls—on final material properties. The feasibility of incorporating short carbon fibers into the ZrB₂-SiC matrix is also assessed, focusing on the effects of preparation techniques and fiber length.
Fabrication insights revealed that increased sintering temperature generally improved densification due to enhanced atomic diffusion, grain boundary migration, and mass transport. High-energy WC milling achieved superior densification compared to ZrO₂ milling, with ZSW samples reaching a maximum relative density of 99.2%, versus 96.5% for ZSZ samples under similar conditions. ZSW samples, however, developed a secondary ZrO₂ phase due to more intense abrasion and oxygen diffusion during milling, while ZSZ samples maintained a finer microstructure, with an average grain size of 2.65 μm compared to 2.91 μm for ZSW. Attempts to incorporate 35 vol% short carbon fibers were unsuccessful under current sintering conditions, but improvements in fiber distribution were achieved with a rotary evaporator. Shorter fibers showed better structural integrity by reducing stress concentrations.
Mechanical properties were strongly influenced by sintering temperature. Higher temperatures caused grain coarsening, leading to reductions in hardness, flexural strength, and fracture toughness. For instance, ZSW hardness decreased from 14.33 GPa at 1950°C to 13.92 GPa at 2050°C, flexural strength declined from 407 MPa to 384 MPa, and fracture toughness dropped from 3.71 MPa·m¹/² to 3.58 MPa·m¹/². Milling methods also played a critical role; ZSW samples showed lower hardness and toughness due to the softer ZrO₂ phase and coarser grain sizes, with a maximum fracture toughness of 3.76 MPa·m¹/² compared to 3.97 MPa·m¹/² for ZSZ samples. However, ZSW samples exhibited comparable or higher flexural strength (384–516 MPa) due to ZrO₂’s transformation toughening effect, while ZSZ samples ranged from 317 to 476 MPa.

The thermal analysis of small satellites (SmallSats) is often given a low priority compared to other sub-systems, due to the short timelines and small budgets associated with SmallSats. However, the satellite's temperature is crucial for preventing mission failures. In this thesis, a new, open-source, modular software for thermal analysis of SmallSats is created with the Python coding language, to simplify and speed up the thermal analysis process. This modularity is achieved by: ensuring that any thermal model can be connected to any other thermal model with a single connect function, allowing a hierarchical model structure that is easily mutable and re-usable; integrating a material database into the software, allowing frequent re-use of common materials, coatings, and contact connections; and including a dedicated sensitivity analysis tool in the software to allow the user to assess the sensitivity of the model's temperatures on various input parameters. To assess the quality of the software's computations, they were verified with the commercial ESATAN-TMS software, and validated with flight data from the FUNcube-1 CubeSat. The validation showed Root-Mean-Square Errors ranging from 1.4 degrees C to 7.1 degrees C for the outside panels of the satellite. With a sensitivity analysis performed on FUNcube-1, it was found that the solar absorptivity of the spacecraft demonstrates the greatest influence on simulation outputs: the largest risk may be its degradation throughout time, due to ultra-violet and atomic oxygen exposure. If the satellite would have had white paint, a year-long degradation could lead to a 17.1 degrees C temperature increase of the maximum achieved temperature in the satellite, depending on the type of paint used. Further development into this software should aim to validate the model even further with different satellites, which will be an important step towards making this tool a standard for SmallSat thermal analysis.

The rapidly increasing utilization of small satellites has led to a growing demand for improved solar array technologies. Traditional solar arrays are limited by their mass and volume constraints, and thus are struggling to meet the increased demands. This feasibility study explores the potential of roll-out solar arrays as a solution to enhance the power generation capabilities of small satellites. These innovative systems are characterised by their unfurling method of deployment, and have demonstrated improved performance compared to traditional solar arrays. By analysing the feasibility of designing a roll-out solar array for small satellites, it is hoped that the operational capabilities of small satellites can be enhanced.

A comprehensive literature study revealed a significant performance gap in high power-to-mass ratios for satellites with a power range of 300 − 1000 W , leading to the development of a roll-out solar array design specifically for this power range. The study combined an analytical model with the non- dominated sorting genetic algorithm (NSGA-II), an efficient multi-objective optimisation algorithm, to generate a set of optimal designs by maximising the power-to-mass ratio and stowed power density, with the latter parameter being another key performance indicator for roll-out solar arrays. The analytical model incorporated the core design elements of a roll-out solar array like deployment mode, deployment mechanism, solar cell type, and stiffening method. A multitude of constraints ensured the feasibility of the designs, while several verification and validation tests were conducted to confirm the accuracy of the analytical model.

The optimisation results revealed that a variety of design combinations exist that could outperform the state of the art solar array capabilities. Optimal designs demonstrated power-to-mass ratios exceeding 145 W /kg and stowed power densities over 55 kW /m3. These designs would deliver over double the power-to-mass ratio of traditional solar arrays in the 300 − 1000 W range, while remaining comparable to the 120 − 140 W /kg state of the art performance of arrays outside of this range. Furthermore, optimal designs offer up to 40% increases in stowed power density compared to the 40 kW /m3 state of the art benchmark. Despite the promising gains, the study reveals some key limitations to roll-out solar arrays. These are the increased development costs, the higher risks, and their bulky geometry being potentially inefficient for smallsats. Ultimately, the study provides for a strong foundation for the development of a roll-out solar array. The results confirm the potential of such a system, and future research is recommended to solidify the feasibility of this innovative technology.

Future Mars exploration missions require safe and controlled landing on the planet’s surface. Conventional entry, descent and landing (EDL) technologies, such as parachutes and rigid aeroshells, face limitations in meeting increasing demands for heavier payloads, harsher entry conditions, and desired landing locations due to their limited deployment windows or geometry constraints set by current launchers. The stacked-toroid inflatable aerodynamic decelerator (IAD) has emerged as a promising EDL technology which has the potential to enable new and ambitious applications. Unlike conventional aeroshells, it utilizes flexible, high-temperature resistant materials that can be folded during orbital injection and transportation, and subsequently deployed before entering the Martian atmosphere. To address the complex interdependence of design variables and the multidisciplinary nature of stacked-toroid analysis, this research proposes a novel Multidisciplinary Design Analysis and Optimization (MDAO) framework. The framework integrates aerodynamics, aerothermodynamics, structural analysis, mass estimation, and Flexible-Thermal Protection System (F-TPS) sizing with trajectory simulations for a parametrized stacked-toroid. The major design variables are parameterized to trace model responses back to the design space. An additional novel contribution is the inclusion of a smaller torus on the IAD’s shoulder. For aerodynamics and aerothermodynamics modelling, the local-inclination panel method is implemented, separately addressing the continuum, rarefied, and transitional flow regimes using well-established analytical methods and bridging functions. The scalloping phenomenon of the deflected surface is accounted for through semi-empirical expressions and experimentally-fitted correlations, capturing the additional aerodynamic and aerothermal contribution. F-TPS sizing employs a 1D Finite Difference Method (FDM) with harmonic weighted averaging of material characteristics to accommodate abrupt thickness variations. Results from each discipline are compared to experimental, flight, and high-fidelity numerical data, showing consistent agreement under various conditions. All disciplines present mean percentage errors in the order of 10-20% which are deemed acceptable for early design stages. The framework is applied to the ESA MiniPINS study, to demonstrate its applicability to a novel EDL architecture for a penetrating probe. The proposed environment efficiently evaluates the stacked-toroid optimum design for minimum mass, weighing only 3.72 kg whilst complying with mission requirements and optimisation constraints. The design remains robust against variations in entry parameters and atmospheric density, requiring minor adjustments for the penetrator impact speed. The framework enables design space exploration, revealing trends favoring stacked-toroids with low inner torus radii and large numbers of tori to minimize aerothermal loads while ensuring sufficient aerobraking. The inflated radius remarkably results in a global variable that can further simplify the design space to a single input for near-optimum rapid evaluations. The feasible parameter ranges identified through the design space search expedite the evaluation and optimization of stacked-toroids’ multidisciplinary performance, aiding decision-making in early design stages of future Mars missions.

Interplanetary CubeSat missions enable low-cost exploration missions, in which the design of a primary propulsion system becomes crucial. Emphasis is put on an autonomous Mars mission starting from a parking orbit around Earth: chemical propulsion systems are characterized by high thrust levels and allow fast Earth escape manoeuvres. In recent years, new green propellant options have been analysed and are available for CubeSat propulsion.
A preliminary mission analysis is performed considering the performance parameters of state-of-the-art CubeSat chemical propulsion systems. Afterwards, a trade-off leads to the choice of propulsion system type and propellant. The propulsion system challenge is to fit in a CubeSat standardized volume, which can range up to 24U: a final design is produced, showing the feasibility of the mission adopting multiple COTS components.

KNO3-Sugar propellants, also known as rocket candy, form a group of simple, cheap and safe solid propellants that are used extensively in student and amateur rocketry communities. One of the most frequently used compositions is KNO3-sorbitol (KNSB) with a typical 65/35 ratio by mass. This composition is used extensively by Delft Aerospace Rocket Engineering (DARE) for small experimental launches including the record-breaking flight of Stratos I in 2009 to 12.3 km altitude. However, KNSB propellant quality has been inconsistent: propellant density is occasionally below 85% in combination with large surface defects. Besides a very high grain rejection rate this has resulted in several explosive failures of new experimental motors in recent years.

In the field of combustion systems, methods and tools are under development to fulfill the need for fast and accurate prediction of emissions such as NO and CO. CFD-CRN is a hybrid approach that utilizes a combination of computational fluid dynamics (CFD) and a chemical reactor network (CRN) to simulate the flow field and chemical kinetics of a combustion system in detail. This thesis describes the research into the effect of applying the energy equation to update the temperature whilst solving the CRN. The objective is to quantify the effect of the common assumption that the temperature generated by CFD is sufficiently accurate and can be kept fixed to reduce the nonlinearity of the system of equations to be solved in the CRN. This research uses and modifies the computational tool AGNES, that was developed at the Delft University of Technology and is able to automatically cluster, solve and visualise the results of a CRN based on results form CFD. The test cases used are the Sandia Flame D, which is a piloted methane-air jet flame with a Reynolds number of 22400, and the Verissimo et al. test case, which is a flameless combustion burner. The CRN was clustered with the zones and tolerances set by Monaghan et al. The results were validated using experimental data of temperature and species mass fractions and the sensitivity of the clustering method was studied.
The results of CFD-CRN simulations were used to evaluate the effect of updating the temperature using the energy equation. The results show that solving the energy equation leads to a progressive overprediction of temperature in the far field of the computational domain, which consequently results in the overprediction of NO and CO concentrations. A potential cause for the overprediction is identified as the heat transfer in the form of conduction and radiation not being accounted for in the solving of the CRN. Unless the diffusion of heat is accurately modeled, the application of the energy equation is not recommended.