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Daniel Guggenheim School of Aerospace Engineering

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    Interdisciplinary Space Logistics Optimization Framework for Large-Scale Space Exploration
    (Georgia Institute of Technology, 2021-04-28) Chen, Hao
    As low-cost rocket launch technologies and space resource utilization systems emerge, human space exploration is attracting increasing interest from industry, government, and academia. To extend the domain of human activity beyond the low-Earth orbit and maintain a long-term human presence in cislunar space and eventually Mars, we need to build a sustainable and affordable interplanetary space transportation system. It requires a campaign-level perspective for space mission design in addition to the conventional mission-level perspective. This thesis first proposes an integrated space logistics framework to enable concurrent optimization of space transportation scheduling, spacecraft sizing, space infrastructure design and deployment. Then, a periodic time-expanded network is built to resolve the scalability issue in the time dimension for long-term space exploration missions. After establishing efficient space logistics optimization frameworks, we switch our focus to space infrastructure technology trade studies to consider space infrastructure design from the subsystem-level. A multi-fidelity optimization method is introduced to guarantee optimization accuracy while improving computational efficiency. Finally, a flexibility management framework is proposed to handle uncertainties in space mission planning and operations. Multiple case studies for human lunar and Mars exploration campaigns are conducted leveraging the proposed methods and frameworks to demonstrate their values and potential impacts. This research resolves the grand challenge of space logistics mission design for future large-scale multi-mission space campaigns.