Browsing by Author "Fu, David"
- Results Per Page
- Sort Options
Microsat Mission Design for Magnetosphere and Ring Science in the Uranian System
(2025-04-23) Fu, David; Beeson, RyneNASA 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.