Publication Type
Journal Article
Version
acceptedVersion
Publication Date
11-2020
Abstract
Robotic on-orbit servicing (OOS) is expected to be a key technology and concept for future sustainable space exploration. This paper develops a novel semi-analytical model for OOS system analysis, responding to the growing needs and ongoing trend of robotic OOS. An OOS infrastructure system is considered whose goal is to provide responsive services to the random failures of a set of customer modular satellites distributed in space (e.g., at the geosynchronous orbit). The considered OOS architecture comprises a servicer that travels and provides module-replacement services to the customer satellites, an on-orbit depot to store the spares, and a series of launch vehicles to replenish the depot. The OOS system performance is analyzed by evaluating the mean waiting time before service completion for a given failure and its relationship with the depot capacity. By uniquely leveraging queueing theory and inventory management methods, the developed semi-analytical model is capable of analyzing the OOS system performance without relying on computationally costly simulations. The effectiveness of the proposed model is demonstrated using a case study compared with simulation results. This paper is expected to provide a critical step to push the research frontier of analytical/semi-analytical model development for complex space systems design.
Discipline
Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
Journal of Spacecraft and Rockets
Volume
57
Issue
6
First Page
1129
Last Page
1138
ISSN
1533-6794
Publisher
AIAA
Embargo Period
3-28-2021
Citation
HO, Koki; WANG, Hai; DE TREMPE, Paul A.; DU JONCHAY, Tristan Sarton; and TOMITA, Kento.
Semi-analytical model for design and analysis of on-orbit servicing architecture. (2020). Journal of Spacecraft and Rockets. 57, (6), 1129-1138.
Available at: https://ink.library.smu.edu.sg/sis_research/5881
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.2514/1.A34663