This thesis explores the design and simulation of a control system that would enable omnicopter drones to simulate close proximity spacecraft rendezvous maneuvers. Close proximity rendezvous simulations typically exist either as simplified online models that lack real-world dynamics or as prohibitively expensive physical testbeds. By leveraging the six degrees of freedom (6-DOF) capability of omnicopters—drones with non-planar rotor configurations allowing complete spatial movement developed by Dario Brescianini and Raffaello D’Andrea—this research provides a cost-effective middle ground between purely digital and full-scale physical simulations. The study implements relative orbital motion using the Clohessy-Wiltshire equations to model the dynamics between a ”chief” and ”deputy” omnicopter, simulating target and approaching spacecraft respectively in close proximity operations. A cascaded control architecture that separately handles attitude and position control enables the simulated deputy omnicopter to approach and maintain specific poses relative to the chief within small distances, mirroring the final critical phase of spacecraft rendezvous. Using MATLAB, the research validates this control strategy through simulation, demonstrating its effectiveness for precise close proximity maneuvers. This work’s contributions lie in: (1) implementing close proximity orbital rendezvous control for omnicopters in simulation, (2) providing improved documentation of omnicopter capabilities to address gaps in publicly available resources, and (3) establishing a foundation for future physical implementation and testing. While physical deployment remains outside the scope of this thesis, the comprehensive modeling and simulation work presented here creates a viable pathway between theoretical spacecraft dynamics and accessible hardware implementation for future research in close proximity operations.

This thesis presents the design and modeling of a self-expanding lunar factory capable of utilizing resources on the Moon to manufacture components for its own growth. A comprehensive system architecture is developed integrating extraction, processing, manufacturing, and assembly subsystems optimized for the lunar environment, with a focus on achieving high resource closure rates while remaining feasible with near-term technologies. An 8,925 kg initial factory configuration is established for further analysis.

A time-step simulation model is implemented to evaluate factory growth dynamics, resource utilization efficiency, and production bottlenecks under various operational scenarios. Using a genetic algorithm to optimize resource allocation strategies, the model demonstrates the initial factory can triple its mass over five years of operation, with 85% of new components manufactured from lunar resources. Key findings reveal that power constraints and processing bottlenecks significantly impact growth trajectories, producing linear rather than exponential growth. Counterintuitively, increased Earth resupply (2,500 kg/yr vs. 500 kg/yr) resulted in not only greater total mass growth (44,491 kg vs. 25,318 kg) but also a higher percentage of lunar-sourced components (71.3% vs. 57.9%).

This work provides insights into production process integration, operational constraints, and growth potential of self-expanding lunar manufacturing, demonstrating how strategic design choices can help establish sustainable industrial capability on the Moon with minimal Earth dependence.

Human space exploration represents the culmination of the best of what our world has to offer—scientific and technological capability walking hand-in-hand with the human drive to explore and understand. Mars, the closest and most similar neighboring planet to Earth, has long been a source of inspiration for both science fiction and scientific advancement. It is the first logical target for investigating the presence of life on other planets and launching an era of interplanetary human existence. Designs for crewed Mars missions have long been tied to development of technology and operational capabilities on and around the Moon, but some of the aerospace community has historically been divided on the role the Moon should play in the development of crewed Mars mission architecture. This thesis explores the viability of executing a crewed mission to Mars without significant prior development of technology and operational capabilities on and around the Moon. Current prominent Mars mission architectures are compared and contrasted, technological and knowledge gaps are identified, and the necessity of the lunar prerequisites is evaluated. This paper compares the mission architectures of Mars Direct, NASA’s Design Reference Architecture 5.0, NASA's System Analysis Cycle 2021, SpaceX’s Starship architecture, and the preliminary architecture discussions of NASA’s Moon to Mars program. Commonalities of the prominent architectures are identified. Sub-architectures are then reviewed, including: entry, descent, and landing systems; ascent systems and in situ resource utilization; life support systems; communication considerations; surface power systems; and crew health and performance. The extent to which the Moon serves as a beneficial "proving ground" for the development of these areas is evaluated and discussed, ultimately determining the extent to which creating a robust, feasible, and safe crewed Mars mission architecture depends on prior development in the lunar domain.

NASA has selected Ice Giants exploration as the priority flagship mission of the next decade, with an orbiter and atmospheric probe being identified as the primary architecture. This design report proposes a Low-Cost Uranus Magnetosphere Observing Satellite (LUMOS) architecture to supplement the planned Uranus Orbiter and Probe (UOP) mission, leveraging unused launch vehicle capabilities in the current UOP design. The LUMOS microsat will pursue magnetosphere mapping and ring imaging objectives in parallel with the primary orbiter's tour of the Uranian moons, improving the science return of the overall mission by increasing spatial and temporal coverage of the magnetosphere and rings and pursuing higher-risk science that is prohibitive for the primary orbiter. The feasibility of such an architecture is demonstrated with a low-fidelity trajectory design for the microsat, high-level design of the science payload and all key spacecraft subsystems, and a mission cost assessment. Each element of the mission design is presented with requirements definition, design approach, trade studies, key analysis, and verification and validation. The trajectory design closes with high coverage for mapping magnetic longitudes and latitudes and imaging ring longitudes. The spacecraft design closes within constraints, with a total mass footprint of 290 kg (microsat wet mass of 156 kg plus 134 kg of additional orbiter fuel for interplanetary cruise and insertion), maximum power draw of 345 W, and total launch volume envelope of 0.68 x 0.66 x 1.37 m^3, for a total volume of 0.62 m^3. The total cost of the mission is estimated at $180M (FY$25). We find that LUMOS is a feasible mission concept that can significantly improve the science return of the UOP Mission. Future work for this design concept will involve transitioning designs into high-fidelity models and analysis, optimizing the mission for science return and fuel consumption, and fully integrating with the UOP design.

NASA has selected Ice Giants exploration as the priority flagship mission of the next decade, with an orbiter and atmospheric probe being identified as the primary architecture. This design report proposes a Low-Cost Uranus Magnetosphere Observing Satellite (LUMOS) architecture to supplement the planned Uranus Orbiter and Probe (UOP) mission, leveraging unused launch vehicle capabilities in the current UOP design. The LUMOS microsat will pursue magnetosphere mapping and ring imaging objectives in parallel with the primary orbiter’s tour of the Uranian moons, improving the science return of the overall mission by increasing spatial and temporal coverage of the magnetosphere and rings and pursuing higher-risk science that is prohibitive for the primary orbiter. The feasibility of such an architecture is demonstrated with a low-fidelity trajectory design for the microsat, high-level design of the science payload and all key spacecraft subsystems, and a mission cost assessment. Each element of the mission design is presented with requirements definition, design approach, trade studies, key analysis, and verification and validation. The trajectory design closes with high coverage for mapping magnetic longitudes and latitudes and imaging ring longitudes. The spacecraft design closes within constraints, with a total mass footprint of 290 kg (microsat wet mass of 156 kg plus 134 kg of additional orbiter fuel for interplanetary cruise and insertion), maximum power draw of 345 W, and total launch volume envelope of 0.87 x 0.69 x 1.16 m3, for a total volume of 0.7 m3. The total cost of the mission is estimated at $180M (FY$25). We find that LUMOS is a feasible mission concept that can significantly improve the science return of the UOP Mission. Future work for this design concept will involve transitioning designs into high-fidelity models and analysis, optimizing the mission for science return and fuel consumption, and fully integrating with the UOP design.

NASA has selected Ice Giants exploration as the priority flagship mission of the next decade, with an orbiter and atmospheric probe being identified as the primary architecture. This design report proposes a Low-Cost Uranus Magnetosphere Observing Satellite (LUMOS) architecture to supplement the planned Uranus Orbiter and Probe (UOP) mission, leveraging unused launch vehicle capabilities in the current UOP design. The LUMOS microsat will pursue magnetosphere mapping and ring imaging objectives in parallel with the primary orbiter’s tour of the Uranian moons, improving the science return of the overall mission by increasing spatial and temporal coverage of the magnetosphere and rings and pursuing higher-risk science that is prohibitive for the primary orbiter. The feasibility of such an architecture is demonstrated with a low-fidelity trajectory design for the microsat, high-level design of the science payload and all key spacecraft subsystems, and a mission cost assessment. Each element of the mission design is presented with requirements definition, design approach, trade studies, key analysis, and verification and validation. The trajectory design closes with high coverage for mapping magnetic longitudes and latitudes and imaging ring longitudes. The spacecraft design closes within constraints, with a total mass footprint of 290 kg (microsat wet mass of 156 kg plus 134 kg of additional orbiter fuel for interplanetary cruise and insertion), maximum power draw of 345 W, and total launch volume envelope of 0.87 x 0.69 x 1.16 m3, for a total volume of 0.7 m3. The total cost of the mission is estimated at $180M (FY$25). We find that LUMOS is a feasible mission concept that can significantly improve the science return of of the UOP Mission. Future work for this design concept will involve transitioning designs into high-fidelity models and analysis, optimizing the mission for science return and fuel consumption, and fully integrating with the UOP design.

A 6 Degree-of-Freedom (6DoF) Flight Simulator in Python was made, leveraging open source libraries to build a simulator capable of running in real-time and offline modes. This simulator, named Python Laptop Air Vehicles (PLAV) is capable of piloted control and has a Hardware-In-The-Loop (HITL) proof-of-concept mode implemented with an Arduino-compatible micro controller. The project is open-source and prioritizes simplicity, with the intent that amateur aircraft designers can use it to test their unique designs with their own flight dynamics model and simulate their flight control with HITL simulation.

The simulator has been validated using the NASA Engineering and Safety Center's Check-cases for Verification of Six-Degree-of-Freedom Flight Vehicle Simulations, ensuring that for a good Flight Dynamics Model (FDM) the simulation gives accurate results. The relevance of implementing the a rotating ellipsoidal Earth is also analyzed in amateur contexts such as high power rocketry. The code is published at https://github.com/adinkojic/PLAV

Space weather (SWx), the complex set of conditions between the Sun and the Earth, is difficult to predict. However, accurate forecasting of the conditions in the interplanetary medium is essential due to the dangers that solar storms pose to technology on the Earth's surface and in the atmosphere. One way to improve forecasting is with data assimilation (DA), a technique that integrates downstream observations into estimates of the solar wind near the Sun. In this thesis, the efficacy of an iterative Ensemble Kalman Smoother (iEnKS) coupled with a reduced-dimension propagation model (HUXt) is investigated. Prior work has been done to assimilate observations from two satellites— STEREO-A and STEREO-B—into this DA algorithm. However, STEREO-B no longer provides operational data. The iEnKS algorithm has thus been tweaked to assimilate observations from a tertiary source — the Advanced Composition Explorer (ACE). An experiment was designed to test the performance of the iEnKS with and without STEREO-B observations over the year of 2012, chosen due to the interception of a large coronal mass ejection (CME) by STEREO-A near the midpoint of the temporal window. iEnKS performance was compared with the performance of a Variational DA technique developed a few years prior.

It was found that when STEREO-B observations were removed from the iEnKS, root-mean squared error (RMSE) at each of the three satellites over the forecast period increased between 3-4%. This consistency was not observed with the Variational DA method in the same circumstances. Additionally, even after the removal of STEREO-B observations, the iEnKS performed more accurately than the Variational method in either case. This points to the effectiveness of the iEnKS as well as its response to changes in observation sources. Further research is needed to determine if error could further decrease with full-dimensional model coupling or the further optimization of the cost-function solving algorithm present in the iEnKS. However, these results are promising in terms of the operational implementation of DA for SWx applications.