The Thermodiver project aims to develop a reusable space tug using Air-Breathing Electric Propulsion (ABEP), which collects atmospheric particles from the upper atmosphere to enable in-situ refuelling and extended mission durations. This propulsion method supports a range of missions, including satellite servicing, orbital transfers, and reducing orbital congestion from space debris. A key part of the design process was the use of ARISS (Air-breathing Refuelling Iterative System Solver), a solver developed by the team that encompasses the initial design, sizing, budgeting, and performance assessment of the air-breathing spacecraft. ARISS integrates various simulation tools: Direct Simulation Monte Carlo (DSMC) for intake and aerodynamic performance, the General Mission Analysis Tool (GMAT) for mission planning, and Finite Element Methods (FEM) for thermal and structural analysis. The project produced a detailed 6.2-meter-long, 800 kg spacecraft design with a parabolic intake for efficiency and the bus shielded in its wake. Capable of de-orbiting satellites such as Proba-V and refuelling within five months for continued missions, the system is being further refined in the final stages of development. Ultimately, the Thermodiver offers a sustainable solution to orbital congestion and a versatile platform for affordable in-space transportation and future interplanetary exploration.

Mars entry guidance faces a critical challenge: navigating hypersonic velocities within the thin atmospheric layers (120 – 45 𝑘𝑚 altitude) while balancing conflicting objectives of precision targeting, thermal survival, and structural integrity. This study addresses a core research question on a successive convexification algorithm that enables precise trajectory optimization for Starship’s hypersonic glide through the upper atmosphere of Mars while enforcing hard physical constraints such as heat flux, g-load, equilibrium glide and dynamic pressure. By formulating such successive convexification - based framework, the inherently non-convex entry problem is decomposed into iteratively refined convex sub-problems, enabling computational tractability under Mars’ variable CO₂-rich atmosphere. The guidance architecture integrates bank angle modulation for lift vectoring and angle-of-attack adjustments for thermal management, optimizing energy dissipation while mitigating heating spikes and aerodynamic stress.

Simulations demonstrate that the collocation discretization strategy used ensures trajectory adherence within the entry corridor, achieving terminal positioning errors below 3 𝑘𝑚 at 45 𝑘𝑚 altitude. The algorithm’s robustness is validated under ±10% dispersions in initial velocity (4.3 𝑘𝑚/𝑠) and flight-path angle (−15°) from a parking orbit around the planet, with heat flux, dynamic pressure, and g-load profiles remaining within mission-critical limits. Sensitivity analyses reveal that atmospheric density uncertainties induce predictable deviations compensated by rapid convex optimizations. These results align and improve on previous NASA mission data.

The study bridges theoretical convex optimization with operational reality, demonstrating that modern computational guidance outperforms legacy predictor-corrector methods in handling nonlinear dynamics and path constraints. By extending the convex framework with adaptive trust regions and sequential convex programming, the proposed method reduces terminal errors by 40% compared to state-of-the-art approaches (Mars 2020). This advancement not only enhances Starship’s capability to deliver crewed and cargo payloads to predefined Martian coordinates but also establishes a foundation for integrating the hypersonic glide phase with the subsequent powered descent phases. As humanity strides toward sustained Mars exploration, this work underscores the viability of successive convexification as a paradigm for achieving precise atmospheric glide through the Martian atmosphere.

Rocket Lab has recovered the first stage of its dedicated small satellite launcher Electron twice by means of splashdown. The ability to reuse the entire first stage can reduce production cost at the current launch frequency and enable a higher launch rate. To lower the launch cost further, Rocket Lab is developing Mid-Air Recovery system for the first stage of the Electron. The research objective of this thesis is to develop a simulation tool for analyzing the launch performance of the Electron rocket and its first-stage recovery, involving mid-air recovery using an air-ram parachute and splashdown recovery using an unguided circular parachute. For the ascent phase, a two-stage rocket Simulink model is developed that implements quaternion representation of six-degrees-of freedom (6-DOF) equations of motion for custom variable mass in the Earth-centered Earth-fixed (ECEF) reference frame to simulate ascent trajectories. Another Simulink model is created to simulate the ballistic trajectory of the first stage after separation using quaternion representation of 6-DOF equations of motion for constant mass in the ECEF reference frame, particularly when first stage recovery is not implemented. It was found that he additional mass, which is required to transform the Electron’s first stage into a reusable one is 100 kg, with the parafoil accounting for 74 kg, the ballute 9 kg, and the remaining mass attributed to modifications such as the parachute attachment and release mechanism and for the circular parachute 71.5 kg with 22.8 kg for canopy, 35.3 kg for suspension lines and 13.4 kg actuators. The parafoil provides superior control, whereas the circular parachute is lighter and more straightforward in design. Consequently, if refurbishment costs are identical for both, the circular parachute emerges as the more advantageous choice.

As climate change continues to drive an increase in extreme weather events, the need for reliable predictions and observational data has never been more critical. Oceans, playing a vital role in regulating the Earth’s climate, are central to understanding these changes. Specifically, accurately modeling ocean wave dynamics, i.e., how waves are generated, evolve, and interact with oceanic processes such as currents, helps track ocean circulation and predict future variations. Thanks to Earth Observation satellites, continuous global observations have been available over the past few decades. Satellite altimeters, active sensors utilizing radar’s ranging capabilities, have emerged as pioneers in space oceanography. These instruments measure critical geophysical parameters such as sea surface height, significant wave height and near-surface wind speed along satellite tracks. Recognizing the immense value of these measurements for climate studies and operational activities, continuous technological innovations are essential for optimizing the performance and use of these instruments. One major breakthrough in satellite altimetrywas the incorporation of Synthetic Aperture Radar (SAR) technology in 2010, which enhanced spatial resolution from around 7 km, provided by Low-ResolutionMode sensors, to about 300m. In 2017, the fully-focused coherent processing of pulse echoes was implemented, a concept widely used in SAR imaging, enabling meter-scale resolution. This improvement led to significant benefits in near-coast applications, improving the quality of geophysical parameters by reducing signal contamination from surrounding land features. Additionally, for the first time, offnadir signals, previously considered a nuisance, were exploited to map narrow inland water bodies and detect sea-ice leads and floes. Recognizing this imaging potential led to investigating its capabilities over open oceans. Existing challenges in conventional, or unfocused, SAR altimetry relate to the accuracy of significant wave height estimates, especially when long waves, known as swells, dominate the sea surface. Swell waves, with wavelengths exceeding 150 meters, are often too long to be fully captured within the SAR altimeter’s footprint, leading to noisy, multi-peaked waveforms. Recognizing the interference of swell signals in SAR responses, combined with the high-resolution data provided by fully-focused processing, this dissertation first investigated the feasibility of transforming what was previously considered a nuisance into valuable information about the sea surface. To achieve this, the identification of swell-induced power variations in off-nadir altimeter’s signals, representing the so-called trailing edge of the returned echo, was first confirmed. These patterns were analyzed to compute a fully-focused modulation spectrumderived from altimetry. The modulation spectrumis a commonly used Level-2 product provided by satellites designed to measure the wave field, such as Sentinel-1 and CFOSAT, and allows for the estimation of swell characteristics, including wavelength, direction and wave height. The proposed method involved normalizing the signal intensity and re-projecting the range bins to cross-track ground locations, followed by spectral analysis akin to side-looking SAR systems. The analysis revealed that fully-focused altimetrymodulation spectra display power in all four quadrants due to the inherent 180-degree SAR ambiguity, plus two additional ambiguities caused by inseparable signals received from both sides of the radar footprint. The study also identified the main modulation mechanisms, using as reference numerical and analytical models. Range bunching was found to be a dominant mechanism alongside velocity bunching, with their relative strength highly dependent on the wave propagation angle. Fully-focused altimetry modulation spectra, derived from Cryosat-2, were evaluated through comparisons with buoy-derived directional wave spectra, showing good agreement. Furthermore, applying the proposed technique to Sentinel-6A data demonstrated that exploiting its full-beamfootprint, which is partially truncated onboard for data volume efficiency, improves swell retrieval. This is particularly true for waves propagating in or near the cross-track direction, due to its extended observational window and higher resolution compared to the operational truncated data. Yet, the development of a method to invert modulation-derived spectra to real ocean wave spectra is necessary to reliably use these instruments as a new source for providing operational global swell observations. The dissertation further explored the limitations of SAR altimeters in ocean wave imaging, focusing on resolution loss. This was addressed by estimating the azimuth cutoff wavelength, which serves as a proxy for the shortest detectable waves across different sea states and wave directions. The method used to estimate this parameter involved a SAR imaging technique applied in the spatial domain, minimizing residuals between the along-track autocorrelation function of fully-focused SAR radargrams, representing successive waveforms, and a fitted Gaussian function. Sentinel-6A data were then used to evaluate the method’s performance through comparisons with model-derived values globally. The analysis revealed that the method performs well under the majority of sea states but tends to underestimate values in extreme wind wave conditions. Furthermore, sensitivity to swell presence was observed, leading to pronounced over estimations, with the magnitude of these errors influenced by the swell direction. To mitigate these errors, an alternative approach was developed in the wave number domain. Results revealed an improvement in the correlation between azimuth cutoff estimates and model-derived values by 10%. Given the strong relationship between resolution loss and sea state conditions, the azimuth cutoff was further used to derive a new sea-state parameter: the variance of wave orbital velocities. Wave orbital velocity statistics offer valuable insights into wave climate by isolating wave components associated with developing seas. Comparisons between modeled and estimated wave orbital velocity variances showed similar sensitivities to swell presence and high sea states, suggesting further refinement of the proposed methods. Despite these challenges, the ability to extract these two additional parameters from the radar signal is valuable for identifying sensors capabilities and providing a new geophysical parameter for oceanographic studies. Lastly, the dissertation assessed the impact of wave-current interactions on wave products derived from both models and satellites, focusing on the Agulhas Current region, one of the most dynamic ocean environments. In situ wave measurements, collected during the One Ocean Expedition in 2023, in which the author participated, served as a reference for this study. The study first examined ocean current products. A clear underestimation of surface current velocities exceeding 0.5 m/s was found for both the Mercator operational model and the altimetry-derived Globcurrent product, with Mercator showing greater variability. Next, wave products, both with and without these ocean current products included in their modeling, were validated. The ECMWF reanalysis v5, known as ERA5, consistently underestimated wave heights above 2.5 m, whereas the MFWAM, which is the Global Ocean Wave Analysis and Forecast system from Meteo-France, showed good agreement with in situ data. This discrepancy was attributed to the lack of ocean current forcing in ERA5, underscoring the need for refinement in areas dominated by currents. Customized MFWAM simulations, including and excluding current data, further supported this finding. MFWAM forced with Globcurrent aligned most closely with drifter measurements, outperforming the operational product that uses Mercator currents. Comparisons between satellite altimeter observations and drifters also showed good agreement in significant wave height, with clear evidence of current-induced wave height variations along satellite tracks. Additionally, a multi-mission analysis of swellinduced modulation spectra from Sentinel-1, CFOSAT and SAR altimeters demonstrated alignment with in situ data and between them, highlighting the potential for synergistic use of these instruments in operational oceanography and climate studies.

This thesis addresses the optimization of on-demand satellite servicing in Sun-Synchronous Orbits through dynamic routing and refueling strategies. Traditional satellite operations, limited by finite onboard fuel, lead to premature mission termination. This research focuses on optimizing a refueling infrastructure comprising fuel stations, a service satellite, and client satellites, specifically for SunSynchronous Orbits. The algorithm is designed to efficiently manage fuel resources by determining the most effective servicing routes to minimize mission time and fuel consumption. A multi-objective optimization framework is developed to model these operations, utilizing a custom algorithm that refines transfer trajectories through high-precision numerical simulations that account for perturbations. Robustness analysis demonstrates that the algorithm can effectively handle uncertainties, consistently converging to the same optimal solutions across varying conditions. The developed algorithm efficiently identifies optimal servicing paths and is scalable to more complex missions involving multiple satellites and refueling stations.

Final Report Design Synthesis Exercise Spring 2024. AE3200: Design Synthesis Exercise. DSE Group 22

This thesis investigates how variations in the Earth-Sun distance influence global temperatures, by comparing a simplified model of the solar system with an existing paper from V.V. Zharkova, claiming that increasing temperatures can be explained naturally. Over a 5000-year period, numerical simulations including planetary gravitational influences, solar inertial motion, and Milankovitch cycles, this study looks at distance variations and Earth hemispheric differences in solar intensity due to albedo differences, to asses this statement. The result shows that while orbital mechanics influence the global temperature, Their role is minimal. It should see a slight decrease in temperature, and thus V.V. Zharkova’s research does not represent the actual situation. This offers valuable insight into the relationship between the Earth's orbital mechanics and climate. However, further research into the accuracy of the model is required.

The design of multi-target rendezvous trajectories, which see a spacecraft approaching a sequence of objects in orbit as efficiently (by some metric) as possible, is a challenging problem of critical importance for Active Debris Removal (ADR), On-Orbit Servicing (OOS) and cis-Lunar logistics more widely. This thesis investigates two primary challenges in space Vehicle Routing Problems (VRPs): the application of Neural Combinatorial Optimization (NCO) methods for ADR missions and the integration of verifiable trajectory optimization techniques for OTV payload deployment.
The first research focus assesses the efficacy of NCO methods in designing multi-target rendezvous trajectories for ADR missions. An Attention-based routing policy, comprising a Graph Attention Network and a Pointer Network, was developed and trained using Reinforcement Learning (RL) algorithms, including REINFORCE, Advantage Actor-Critic (A2C), and Proximal Policy Optimization (PPO). Through hyperparameter analysis utilizing ANOVA, embedding dimension and the number of encoder layers were identified as critical factors influencing model performance. The trained policy was evaluated on scenarios involving 10, 30, and 50 transfers based on the Iridium 33 debris cloud. In missions with 10 transfers, the NCO policy achieved a mean optimality gap of 32%, outperforming the Dynamic RAAN Walk (DRW) heuristic in both mission cost and runtime. However, performance degraded in more complex scenarios with 30 and 50 transfers, indicating limited generalization beyond the training conditions. Grid search hyperparameter optimization revealed that while model performance improves with increased complexity, gains are marginal, and larger training datasets enhance convergence speed with only slight improvements in final performance. These findings demonstrate that NCO methods are effective for ADR missions with a limited number of targets but face scalability and generalization challenges in more complex scenarios.
The second research focus involves the design and optimization of multi-rendezvous trajectories for the UARX Space OSSIE mission using a modular framework that integrates Heuristic Combinatorial Optimization (HCO) with Sequential Convex Programming (SCP). This framework successfully determined optimal target sequences and generated near fuel-optimal trajectories for OSSIE, a translational and mass-dynamic payload delivery platform.
An Attention-based routing policy trained with RL was integrated into the combinatorial optimization process, enhancing the efficiency of mission planning. Applied to the OSSIE mission, the framework effectively explored the mission design space, optimizing 5000 mission scenarios and affirming the vehicle’s capability to fulfill advertised services. The modularity of the framework ensures adaptability to mission-specific constraints and facilitates future extensions, such as the incorporation of low-thrust propulsion profiles. Overall, this thesis confirms that NCO methods are applicable and effective for specific instances of space VRPs, particularly in optimizing ADR missions with a limited number of targets and in near-static mission scenarios where RAAN convergence is not required. The integration of verifiable trajectory optimization techniques with advanced routing policies presents a viable approach for efficient and adaptable mission planning. However, scalability and generalization remain challenges that necessitate further research. Recommendations include refining NCO model architectures to enhance scalability and generalization, exploring hybrid approaches that combine NCO with traditional heuristics, and developing automated machine learning frameworks to optimize model performance and robustness.
The project successfully achieved its primary objectives: developing and implementing heuristic and neural combinatorial optimization solvers for space VRPs, designing a modular trajectory optimization framework, and conducting comprehensive mission analyses for the OSSIE OTV. In doing so it has increased the mission design capabilities for space logistics missions at SENER Aerospace & Defence, as well as provided a strong foundation for future research and development aimed at addressing the increasing complexities of space operations.

In pursuit of cost-effective and sustainable space access, Dawn Aerospace is pioneering innovative launch systems. Their focus lies on a semi-reusable, two-stage-to-orbit launch vehicle, designed for horizontal take-off and landing. While current launch vehicles rely solely on rocket propulsion, the potential of airbreathing engines on the first stage is explored. Airbreathing engines offer increased fuel efficiency and utilize the incoming airflow as oxidiser.
This study delves into the feasibility of integrating airbreathing propulsion into Dawn Aerospace's Mk-III vehicle, with a goal to reduce gross take-off mass while meeting mission requirements. Airbreathing engine types are evaluated, with ramjets and turbine engines emerging as primary candidates. Detailed design processes, including vehicle modeling, trajectory analysis, and optimization, are employed.
The study reveals the potential of the ramjet concept which could have a lower gross take-off mass compared to fully rocket powered designs. Nevertheless, the application requires an improved vehicle design to obtain a feasible design.

The startup Rocket Factory Augsburg (RFA) is developing the RFA ONE orbital launch vehicle. A significant hurdle for its closed-loop guidance is the need to fully deplete the third stage for insertion during the first flight, which results in lengthy burn-arcs and complexity not managed properly by traditional guidance algorithms. Additionally, new testing methods introduce uncertainty and component failure risks, demanding an adaptable guidance system.This thesis therefore aims to enhance RFA's closed-loop guidance system to ensure optimal orbit insertion in all feasible scenarios. This was achieved by redesigning the closed-loop guidance system to make it more robust for extended thrust-arcs.Furthermore an in-flight estimation algorithm for the key performance parameters was implemented. Finally the guidance can now fall back to alternate target orbits in case of insufficient performance margins. It was shown that the new guidance is able to successfully complete the maiden flight with the large amount of expected uncertainty.

RLV development can be considered as the modern step towards mission design due to financial and strategic decisions. In the past, reusability has been addressed however the level of maturity of the technology, both in terms of hardware and software was not yet reached. There are several aspects to developing a RLV, and these can be categorized into optimization of the LV, optimization of the trajectory, and cost analysis. TO be able to determine the feasibility of the mission, it is not just necessary to develop a suitable configuration, but to also determine the physical feasibility of the trajectory. Several methods exist of which convex optimization is selected. This class of algorithms have risen in popularity in the regime of powered descent guidance, and present a desirable trade-off between performance and computational cost. An already existing algorithm, DESCENDO, for a two-staged vehicle CALLISTO purposed for a mission to a geo-synchronous orbit, is taken as reference. The algorithm is rewritten in YALMIP allowing it to perform more efficiently by saving computation time through creation of multiple controllers based on a discretized burn schedule. A potential candidate for reusability in the future is selected, which is a VEGA variant, considered as a two-staged vehicle with set requirements on the mission and configuration. Through closed-loop simulations, the feasibility of RTLS for a particular mission of this VEGA variant can be studied. The disciplines involved in the study include the launch vehicle optimization, engine sizing, preliminary ascent & descent, and 3-DoF simulations. Previous research at TU Delft on RLV has included the work Rozenmeijer, Vandamme, Van Kesteren, Miranda, and Contant, graduate students of the TU Delft Aerospace Engineering faculty. The work relied on the usage of the TUDAT C++ software environment and based its feasibility or reusability of operations through a cost-analysis. A shift in direction is taken away from cost-analysis to examine at a greater detail the physical feasibility of the trajectory for a nominal candidate RLV. This is done by examining the influence of simulator to guidance algorithm dynamics and guidance algorithm parameters. Moreover, a nominal payload class between 100 and 500 kg is selected to determine the configuration of the vehicle ideal for this mission. To be able to determine feasibility of RTLS, three metrics are considered, which are the final landing velocity, final landing position, and maximumdynamic pressure. The study performs higher fidelity analysis only on the return phase, and as such the starting conditions for descent are determined through a preliminary design process by considering a drag-less ascent. This returns a starting altitude of around 26-30 km, with similar values for starting downrange position, and varying conditions of initial mass and velocity. For the preliminary descent, it is found that the metric of dynamic pressure does not reach more than around 60% of the limit imposed by the VEGA-C, which is similar for other VEGA variants. This coincides with research done with the CALLISTO vehicle. All in all, the best cases for these metrics and one included as an overall best case where candidates for the 400 kg payload class. The selection criteria for best cases of the preliminary descent involved the dynamic pressure, final velocity, and required propellant mass for descent. Moreover, the vehicle optimization results showed that this contained the most variation of vehicle characteristics, and as such it was deemed as a desirable class to work with for its flexibility in design. The best case burnt mass result was selected as the best case velocity required extensive propellant mass to burn for only a less than 7 m/s difference in result, which would not be indicative of what the convex algorithm could achieve due to dynamics involved in the preliminary experiment. This nominal candidate is then tested for various variations of controller tuning parameters combinations, burn schedules, and simulator/guidance frequencies. The results showed a clear desirable region for the final time of just between 300 and 310 seconds for return, favouring shorter burns. The solution envelope for the burn schedule showed gaps in zones of feasibility as well as optimality, suggesting some performance issues with the algorithm due to it failing to find solutions. Nevertheless this envelope is well defined and several feasible solutions existed. The influence of parameter tuning and simulator frequency was studied. It was determined that no set of guidance parameters could give an advantage over the other, but that some values did favour feasibility more. This is somewhat in contrast to the selection of frequencies, as despite the fact there was also a large difference for higher frequency ratios between the Q3 to Q4 and Q0 to Q2, there is a noticeably trend that higher ratios are favoured. Moreover, a local optimal ratio of frequency of 10-1 was also found, and being the same ratio used for the other experiments as well as the CALLISTO study, provides more evidence that this effect is intended. The uncertainties studied are for the initial state variations, errors in reading of position and velocities, and process time delays. It was noted that almost all the errors in the initial state variations shared similar distributions for ranges of values of the metrics. The overall majority returned feasible as well as the large minority of this returned optimal. Of little to no significance was the processing time delay, of which the overwhelming majority returned optimal results, and the rest where outliers whose process time factor where beyond the 3σ limit imposed in the creation of normal random variables. The largest errors arose from the real-time uncertainty in the velocities and position, modelled after pseudo-range errors. Although results showed a high density in the feasible and optimal regions for metrics of final time and position, there was also a high density past the feasible regions. It can be considered that the feasibility of RTLS operations for such a VEGA vehicle is restricted by such errors as expected, but nevertheless results are promising in what can be the main steps to lead to an error analysis study by the use of state estimation techniques and testing various modifications made to the SOCP problem to improve performance.

The Mars Ascent Vehicle will bring samples back from the surface of Mars to its low orbit in 2031. Its preliminary design has been performed by NASA, defining it as a two-stage solid propellant rocket. However, a research gap exists in finding what the optimum solid rocket motors geometries are to bring the Martian samples to a target orbit between 300km and 375km above Mars.
To this extent, the ascent and propellant burn have been modelled, allowing for variation in the geometry of the motors, but also in the launch and separation angles, and in thrust vectoring control. This model has been incorporated into an optimisation, from which a minimum lift-off mass of 343kg was found, 57kg less than required. In the process, 18 thousand different solutions have been found that satisfy all requirements, would the priority shift from the mass of the vehicle to for instance the burn time, or the final altitude.

A flight termination system (FTS) is one of the most important safety features on a launch vehicle, as it allows for the vehicle's flight to be terminated in a controlled way when predetermined safety criteria or boundaries are exceeded. Currently, T-Minus Engineering B.V. aims to develop a custom flight termination system for the Dart payload stage of their DART XL sounding rocket. A sounding rocket is by definition sub-orbital, so an important safety constraint is its impact location. Based on this impact location, an advice can be formed for a range safety officer (RSO) to base flight termination decisions on. Therefore, the objective of this thesis is creating an algorithm to predict the instantaneous impact point (IIP) of the DART XL's ballistic payload stage in near real-time during a launch, considering impact probability area boundaries and requirements for the accuracy and update rate.

To meet this objective, two separate models were created. The first was a pre-flight nominal trajectory model aimed at evaluating the nominal vehicle trajectory and thereby producing inputs and verification tools to assist the development of the second model. The second model, the in-flight IIP prediction model, is intended to run during a DART XL launch to continuously predict the ballistic trajectory and IIP of the Dart stage in the post-separation phase. An important element of developing both models is determining the model definitions. The final environment model selection consists of a US76 atmospheric model, a central gravity model including the J2 effect, a local wind model and a rotating, ellipsoidal Earth model. Furthermore, using 3-degrees of freedom (3-DoF) for the IIP prediction model resulted in IIP predictions close to those predicted using a nominal trajectory model of more degrees of freedom.
Additionally, an Euler integrator with a step-size of 0.1 s was used for the IIP prediction model. With this step-size, the IIP prediction model successfully met the computation time requirement of an update rate below 1 s. For the accuracy requirement, the IIP prediction model shall only include parameters that influence the prediction in the order of 1 km. This requirement was successfully met using the step-size of 0.1 s, with a distance to a verification IIP of less than 600 m.
Lastly, the nominal impact point distribution was determined by performing Monte Carlo simulations of the pre-flight nominal trajectory model. The resulting IIP distribution was used to determine the 3-σ impact probability area, which serves as a measure of the uncertainty of the nominal impact point.

It should be noted that uncertainties remain in this nominal prediction larger than the desired 1 km accuracy radius. However, it is unlikely that the uncertainty of the nominal IIP prediction can be decreased below a radius of 1 km due to the inherent unpredictability of launch conditions. The overall conclusion is therefore that the thesis work has successfully developed a model for the near real-time instantaneous impact point prediction of the DART XL sounding rocket's Dart payload stage.

Single-Stage-To-Orbit (SSTO) launch vehicles are capable of reaching orbit while being potentially fully reusable. A technology capable of enabling SSTO access to space is the air-breathing engine, which has a high specific impulse and low thrust-over-weight (T/W) ratio compared to conventional rocket engines. This necessitates the use of a Horizontal Take-off and Horizontal Landing (HTHL) launch vehicle with a lifting surface, which enables banking maneuvers that can manipulate the orbital Right Ascension of the Ascending Node (RAAN) that the space plane achieves. This means that the space plane is capable of advancing or delaying its time of launch, while still achieving a similar orbital RAAN. This effectively increases the launch window even if a precise orbit insertion is necessary.

This thesis answers the question what the fuel-optimal ascent trajectory is for a space plane that would extend its launch window. In order to answer this question, the full six DoF equations of motion have been defined to simulate the ascent trajectory of a space plane. Additionally, a robust Guidance and Control system is developed that can use the nonlinear translational and rotational equations of motion.

For several launch times, ranging from two hours earlier to two hours later than the nominal launch time, the ascent trajectory has been optimized that included a banking maneuver. It was found that at the cost of propellant, it is possible to have a launch time delayed are advanced by as much as two hours, which means that the space plane can manipulate the RAAN by ± 30 degrees. The extra propellant cost can be related to increased drag losses during the banking maneuver.

The small satellite market is rapidly growing and becomes more competitive by the day. In order to reduce launch costs, the concept of reusable launch vehicles wins popularity. Only few companies have managed to successfully recover and re-use their launch vehicle, of which SpaceX is the only one using a powered descent technique. This study focuses on applying that same technique on a small satellite launcher: Rocket Labs Electron. A 3-DOF trajectory optimization is performed to find the fuel optimal ascent and descent trajectories of the Electron. The original design of the Electron is adhered to as much as possible. The optimization is performed for a variety of Single- and Multi objective optimizers and different settings. Although this is only a feasibility study in which many assumptions are made, the results look promising for further research to be done.

Dawn Aerospace is developing a horizontal take-off and landing two stage to orbit partially-reusable launcher concept. The re-usable first stage spaceplane operates on a return to launch site trajectory and integrates into the existing airspace, flying as an UAV. For any re-entry vehicle the design needs to account for aerothermodynamic behaviour around the vehicle, to ensure the structure can survive the re-entry temperatures. The unique mission of the Mk-III means the thermal design considerations are unique and provide a new engineering challenge and research topic.

This thesis investigates the aerothermodynamic behaviour of the Mk-III flow and structure. A loosely coupled model was created for this purpose, which couples engineering methods to predict the aerothermodynamics and the thermal behaviour of the structure. The coupling is done by transferring the external skin temperature and convective heat flux between the two simulations.

The primary research question for this thesis is “What thermal protection systems have potential to be implemented on the Dawn Aerospace Mk-III spaceplane for a range of different design trajectories.” Two thermal protection systems (TPS) and material choices have been identified as potential solutions. The first is a fully titanium structure, which can handle the temperature experienced by the Mk-III for all trajectories at every point along the vehicle. The second is a combined titanium and BMI CF structure with an insulation layer on the BMI CF. The titanium is required for the temperatures experienced on the vehicle’s leading edges, while the BMI CF has been identified as suitable in areas away from the leading edge if protected by an insulation TPS. A benefit this option produces is that the insulation layer can be changed in thickness to lighten the vehicle for lower design trajectories, therefore creating different vehicles for different trajectories. However, combining a metal with a composite could pose manufacturing issues such as cost for different manufacturing processes and joining problems. This thesis could not properly trade-off between these two options due to it being outside the scope of this thesis and due to limitations in detailed structural knowledge.

These two material choices were chosen from four materials analysed in the thesis and four different TPS. Other TPS were not suitable at decreasing the structural temperature for the Mk-III mission or had an unjustifiable weight penalty. The other material choices would have been suitable in certain situations but were heavier than the current proposed options and might have required a TPS.

This thesis provides valuable insight in what suitable material and TPS choices could be for the Mk-III mission. It also shows that for any future material and TPS choice to be made, a comprehensive structural analysis is required. Mass is a key trade-off parameter between the two proposed solutions and a better structural analysis is required for any further trade-off.

In this thesis, the achievable performance and limitations of a Synthetic Aperture Radar (SAR) seeker on an Anti-Ship Ballistic Missile (ASBM) for a set of parameters has been investigated. This was achieved by modelling the dynamics of an ASBM and the constraints related to the acquisition requirements of a maritime surface target in the "Generation and Improvement Algorithm for Nonlinear Trajectories" (GIANT) optimisation tool provided by TNO. The angular velocities of the ASBM were set as the control variables for the optimal control problem where the objectives were set to the minimisation and maximisation of the exposure time and vertical end velocity of the missile and the minimisation of the required time for creating one SAR image by the SAR seeker.

Three experiments were carried out to investigate the influences for different initial conditions and resolution constraints on the optimised trajectory. In the first experiment, the trajectory was optimised for initial reentry conditions that are representative for typical ASBMs. The target was placed at the location that would match the uncorrected ballistic flight impact location of the ASBM. This allowed to compare and visualise the optimised manoeuvres of the ASBM relative to its ballistic flight trajectory. In the second experiment, the target was placed at the same location, but the initial re-entry conditions were optimised by GIANT, that provided the optimal trajectory. In the last experiment, the constraints related to the resolution of the target were lowered to analyse the maximum performance of the system.

The experiments show that a larger initial squint angle of the re-entry position of the ASBM improves the overall performance. This is because a larger squint angle allowed the missile to obtain a larger seeker look angle during the SAR phase while performing minimal manoeuvres during the re-entry phase. This permitted the dwell time of the SAR seeker and the exposure time of the missile to be as short as possible, while the missile’s vertical end velocity could be maximised. It was also shown that a ground range and crossrange resolution of 1.60 m could be achieved for an average dwell time of 0.1170 s. For better resolutions, the bandwidth of the SAR seeker appeared to be the limiting factor of the system for the chosen set of parameters.

The last 20 years has brought with it a surge in efforts toward the Red Planet as the next frontier is human space exploration draws closer. Many concepts have been proposed for a sustained human settlement on Mars, with NASA’s ISRU-to-the-wall campaign identifying the need for a shuttle vehicle between theMartian surface and a station in an orbit around the planet. Two such vehicle concepts have been designed: the Charon by Gaffarel et. al. and Hercules by Komar et. al.. However a Multidisciplinary Design Optimisation (MDO) has thus far not been applied. In this research an MDO is employed for the same mission scenario as the Charon vehicle’s. The vehicle must transport 1200 kg, including 6 crew, to a 607 km circular orbit at 44.96± inclination from the Martian base that is located at 42.5± North and 25.5± East. It must then return to the base, its entry beginning at 80 km altitude at a velocity of 3500 m/s. The MDO in this research is performed by dividing the design of the vehicle and its trajectories into various disciplines, which are optimised in parallel. In reality cost commonly is the dominant factor that drives the design, in this case, the vehicle’s Gross Take OffWeight (GTOW) is taken as the objective. Estimating the cost of the Martian shuttle vehicle within reasonable accuracy is exceedingly difficult, as not only is its realisation still decades away, costs such as the shuttle’s transportation to Mars, its operational costs, and its maintenance costs are very hard to estimate. However, a vehicle’s GTOW is directly influential on its cost, and its reduction is therefore the optimisation’s goal. The disciplines within the optimisation are the vehicle’s geometry, mass, aerodynamics, and ascent and descent trajectories. Constraints are set for both the vehicle and its trajectories, to which the design must adhere, and the performance of the design is determined by a fitness function that ensures the reduction of the vehicle’s GTOW. The optimiser itself is written using Tudat software, a set of C++ libraries developed by the TU Delft. As the same mission scenario is taken for the vehicle in this research as that of the Charon vehicle, the Charon design can be directly compared to that of the optimiser. TheMDO is able to significantly reduce the vehicle GTOW, obtaining an optimum solution of 146.2 tonnes, which is more than 20 tonnes lighter than Charon, at 168.1 tonnes. The greatest reduction in mass is found in the ascent propellant mass, which is the greatest contributor to the GTOW. This reduction is mostly due to the lower maximum Thrust to Weight (TW) ratio used in the MDO. Other scenarios are also investigated and their effects observed. Two other target orbits and rendezvous strategies are tested, namely the same as the Hercules vehicle (108 km pericentre altitude and an eccentricity of 0.0178), and a direct ascent to the orbital node at a circular 500 km altitude orbit. The Hercules vehicle scenario proved to be by far the most GTOW-preferable, with a GTOW of only 103.0 tonnes. The GTOW of the MDO solution found for the Hercules scenario is also less than that of the Hercules vehicle design, which is 162.8 tonnes, however the Hercules vehicle transports a payload mass of 5750 kg as opposed to the MDO’s 1200 kg, therefore the mass reductions cannot be solely attributed to the optimiser performance. It is clear from the results that the altitude of the initial target orbit is the greatest factor contributing to the GTOW, with a reduction in both payload mass andMartian base latitude also shown to reduce the GTOW. Neither an increase in the maximum acceleration constraint, nor a change in ascent thrust profile, were shown to have any benefit on the GTOW. The sensitivity of the optimum design with respect to uncertainties is assessed. The final pericentre and final eccentricity are both most sensitive to the final pitch node value, especially when taking interference with other variables into account. The inclination, however, was almost solely influenced by the first pitch angle value. The latitude and longitude are also almost solely influenced by a single variable, namely the flight path angle, and the final velocity and final pitch angle are both highly volatile to all variables when interference effects are taken into account. TheMDO model as a whole is found to be sensitive to changes in both aerodynamics coefficients and propulsive efficiency; an increase in aerodynamic coefficients adversely affects the GTOW, and an increase in propulsive efficiency benefits the GTOW, and vice versa.