Multifidelity Space Mission Planning and Infrastructure Design Framework for Space Resource Logistics

Author(s)
Chen, Hao
Sarton Du Jonchay, Tristan
Hou, Linyi
Advisor(s)
Editor(s)
Associated Organization(s)
Organizational Unit
Daniel Guggenheim School of Aerospace Engineering
The Daniel Guggenheim School of Aeronautics was established in 1931, with a name change in 1962 to the School of Aerospace Engineering
Series
Supplementary to:
Abstract
To build a sustainable space transportation system for human space exploration, the design and deployment of space infrastructure, such as in-situ resource utilization plants, in-orbit propellant depots, and on-orbit servicing platforms, are critical. The design analysis and trade studies for these space infrastructure systems require the consideration of not only the design of the infrastructure elements themselves, but also their supporting systems (e.g., storage, power) and logistics transportation while exploring various architecture options (e.g., location, technology). This paper proposes a system-level space infrastructure and logistics design optimization framework to perform architecture trade studies. A new space-infrastructure logistics optimization problem formulation is proposed that considers the internal interactions of infrastructure subsystems and their external synergistic effects with space logistics simultaneously. Because the full-size version of this proposed problem formulation can be computationally prohibitive, a new multifidelity optimization formulation is developed by varying the granularity of the commodity-type definition over the space logistics network; this multifidelity formulation can find an approximate solution to the full-size problem computationally efficiently with little sacrifice in the solution quality. The proposed problem formulation and method are applied to the design of in situ resource utilization systems in a multimission lunar exploration campaign to demonstrate their values.
Sponsor
This material is partially based upon work supported by the funding from the NASA NextSTEP program (80NSSC18P3418) awarded to the University of Illinois, where the original version of this work was initiated.
Date
2021-03
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Resource Type
Text
Resource Subtype
Post-print
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