Robust and Adaptive Mission Design for Planetary Science in Uncertain Environments
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gentgen-cgentgen-phd-aeroastro-2026-thesis.pdf
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Author(s)
Gentgen, Chloé
Advisor(s)
de Weck, Olivier L.
Weiss, Benjamin P.
Landau, Damon
Date Issued
February 2026
Publisher
Massachusetts Institute of Technology
Abstract
Planetary science missions are expected to deliver ambitious science returns while operating in environments that may be highly uncertain prior to arrival. These uncertainties can introduce risk, either by creating hazardous conditions for the spacecraft or by preventing the collection of measurements needed to meet science requirements. This challenge is amplified when the environment itself is the target of the science investigation and its properties are poorly constrained or exhibit significant temporal and spatial variability. In addition, mission science goals have become increasingly demanding, with a stronger emphasis on targeted, hypothesis-driven investigations that require well-defined measurement strategies and clear traceability to specific scientific questions. This shift places greater emphasis on early formulation, requiring mission teams to demonstrate that a concept of operations can satisfy requirements under environmental conditions predicted at the destination. To address these needs, this thesis develops a design-under-uncertainty methodology that provides a systematic framework for assessing and designing concepts of operations for planetary missions in uncertain environments. The approach assesses mission performance by integrating the concept of operations into physics-based models of the target environment with probabilistic representations of uncertain parameters. Selected science value and safety metrics are then evaluated using Monte Carlo simulations and sensitivity analyses. Design then focuses on increasing robustness and adaptability by generating and evaluating alternative concepts of operations. These efforts are shaped by the mission’s scope, scientific objectives, operational constraints, and anticipated interactions with the environment. Robustness is achieved through refining and comparing candidate concepts of operations based on their statistical performance under uncertainty, while adaptability is addressed through design principles organized into four pillars: flexibility, observability, responsiveness, and commitment. Together, these elements guide the development of concepts of operations that can accommodate both known unknowns and unexpected conditions that may emerge after arrival at the destination. The methodology is demonstrated on two case studies that reflect current highpriority exploration targets. The first examines how candidate Uranus orbiter trajectories can characterize magnetospheric dynamics by evaluating how changes in the magnetopause shape affect crossing opportunities, including both the number of crossings and whether they occur in regions most informative for solar-wind interaction studies. Results show that equatorial tour trajectories perform significantly worse when arriving after 2050 due to changes in Uranus’ geometry, and trajectory-modification strategies to mitigate this loss of performance are evaluated. The second case study quantifies the mass of plume material that an Enceladus mission could sample from orbit. It evaluates how uncertainty in jet parameters affects sampled-mass predictions, how temporal variability modulates the plume output, and how spatial variability from vent distribution and plume density decay with altitude influences sampled mass. The analysis further computes total sampled mass for representative near-rectilinear halo orbits, showing that the average mass collected per pass is lower than commonly assumed in the literature.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
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