On-Orbit Servicing Optimization Framework with High- and Low-Thrust Propulsion Tradeoff

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OOS_MultiModal_Manuscript_Submitted_rev_final.pdf (1.26 MB)
Author(s)
Sarton Du Jonchay, Tristan
Chen, Hao
Isaji, Masafumi
Shimane, Yuri
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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
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Research Publications
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http://hdl.handle.net/1853/66801
Abstract
This paper proposes an on-orbit servicing logistics optimization framework capable of performing the short-term operational scheduling and long-term strategic planning of sustainable servicing infrastructures that involve high-thrust, low-thrust, and/or multimodal servicers supported by orbital depots. The proposed framework generalizes the state-of-the-art on-orbit servicing logistics optimization method by incorporating user-defined trajectory models and optimizing the logistics operations with the propulsion technology and trajectory tradeoff in consideration. Mixed-integer linear programming is leveraged to find the optimal operations of the servicers over a given period, whereas the rolling horizon approach is used to consider a long time horizon accounting for the uncertainties in service demand. Several analyses are carried out to demonstrate the value of the proposed framework in automatically trading off the high- and low-thrust propulsion systems for both short-term operational scheduling and long-term strategic planning of on-orbit servicing infrastructures.
Sponsor
This work is supported by the Defense Advanced Research Project Agency Young Faculty Award D19AP00127.
Date
2021-07
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Post-print
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