Optimal fuel station arrangement for multiple GEO spacecraft refueling mission

Zhu, Xiaoyu; Chen, Junli; Zhang, Chengxi; Qiao, Bing

doi:10.1016/j.asr.2020.07.028

Cited by 5 publications

(3 citation statements)

References 29 publications

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“…The second CONOP utilizing depots has many considerations as it becomes a "traveling salesman" problem and is bespoke to individual cases, it will not be reviewed in this paper. Other researchers are reviewing the depot servicing model [7,8].…”

Section: Concept Of Operation Of Oosmentioning

confidence: 99%

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Valuation of On-Orbit Servicing in Proliferated Low-Earth Orbit Constellations

Luu

Hastings

2020

Ascend 2020

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On-orbit servicing (OOS) presents new opportunities for refueling, inspection, repair, maintenance, and upgrade of spacecraft (s/c). OOS is a significant area of need for future space growth, enabled by the maturation of technology and the economic prospects. This congestion is leading s/c operators to explore how they can leverage OOS. OOS missions for s/c in geostationary orbit (GEO) are currently underway. This is being driven by the closure of the business case for refueling long lived monolithic chemically propelled GEO assets. However, there are currently no plans for OOS of low-earth orbit (LEO) s/c, aside from technology demonstrations, because of their shorter design life and lower cost. It will become particularly important to enable the servicing of LEO s/c as the industry shifts its focus towards LEO. Designing OOS systems for LEO constellations differs from that of GEO based systems, this difference is attributed to LEO's proliferation of satellites, environmental effects (J2 nodal precession, drag), and different constellation patterns. Satellite constellations in LEO are becoming more distributed due to increased access, distributed risk, flexibility, and cost. OOS of s/c may enable the reduction of requirements on subsystems such as safety and the need for redundancy. These requirement reductions will enable lower risks, lower costs, and increased system resilience. This paper analyzes the benefits of OOS in proliferated LEO constellations. Several OOS system architectures are modeled; in each system architecture the model will vary qualities such as number of servicers, altitudes, and orbital maneuvers. The objective of the model will be to optimize for cost, time, and utility to generate a tradespace for an OOS system architecture.

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Section: Concept Of Operation Of Oosmentioning

confidence: 99%

“…In order to determine the cost for the OOS, we determine the price per kg, 142 ÷ 1040 = 0.14 $ / , of the OSAM-1 mission [8,9]. The ∆v for each maneuver will be totaled and iterated for each maneuver to provide total mass required for each OOS using the rocket Eqs.…”

Section: Time To Plane Change (Days) -125 Km Time To Plane Change (Days) -25% Casementioning

confidence: 99%

Valuation of On-Orbit Servicing in Proliferated Low-Earth Orbit Constellations

Luu

Hastings

2020

Ascend 2020

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“…GEO remote sensing satellite mainly relies on attitude maneuver to image different places, which is different from LEO satellite imaging process. Although researchers have studied the task planning of single or multiple GEO satellites [20,9], there are few studies considering the cooperative tasks of LEO and GEO satellites. Most of the existing researches focus on guiding cooperation in time series [19].…”

mentioning

confidence: 99%

Collaborative mission optimization for ship rapid search by multiple heterogeneous remote sensing satellites

Zhao

Jiang

et al. 2022

JIMO

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<p style='text-indent:20px;'>Multiple heterogeneous satellites mission optimization is a typical kind of non-deterministic polynomial-time hard (NP-hard) problem, and some complicated scenarios bring new challenges. A novel method of missing ship rapid search using multiple grouped heterogeneous satellites is introduced in this paper. The focus is on optimization of collaborative mission optimization for various satellites including low-earth orbit (LEO) satellite and geostationary orbit (GEO) satellites. A fast coverage of the wide sea area using imaging satellites with narrow coverage range has become the most important part to tackle this problem. However, due to different imaging mechanisms of heterogeneous satellites and other constraints, it brings a great challenge to construct the optimization model. A constrained optimization problem model considering the cooperation between LEO and GEO satellites is constructed. A solution strategy based on bi-level metaheuristic algorithm is designed. The time optimal solution of the collaborative task planning between LEO and GEO satellites can be obtained based on the optimal attitude maneuver path of GEO satellites. Thus, wide-area search for missing ships can be conducted in an effective way. The effectiveness of the proposed method is verified by an example.</p>

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Intelligent Decision-Making Method for On-Orbit Service with Multiple Geosynchronous Earth Orbit Targets Based on Reinforcement Learning

Chen

Zhao

2022

Proceedings of 2021 5th Chinese Conference on Swarm Intelligence and Cooperative Control

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Optimal fuel station arrangement for multiple GEO spacecraft refueling mission

Cited by 5 publications

References 29 publications

Valuation of On-Orbit Servicing in Proliferated Low-Earth Orbit Constellations

Valuation of On-Orbit Servicing in Proliferated Low-Earth Orbit Constellations

Collaborative mission optimization for ship rapid search by multiple heterogeneous remote sensing satellites

Intelligent Decision-Making Method for On-Orbit Service with Multiple Geosynchronous Earth Orbit Targets Based on Reinforcement Learning

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