Modeling Space System Architectures with Graph Theory

Arney, Dale; Wilhite, Alan W.

doi:10.2514/1.a32578

Cited by 25 publications

(5 citation statements)

References 9 publications

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“…𝒃 𝑘(𝑙−1) ) ⊘ 𝜼 is negative, which then enforces the operating time loss to be zero. Equation (11) calculates the level of remaining stock. If the safety stock is not sufficient to support a launch delay, the remaining supplies 𝒃 𝑘𝑙 are zeros.…”

Section: E Operating Time Loss Evaluation Through Decision Rulesmentioning

confidence: 99%

“…In the space logistics research field, multiple frameworks have been proposed in the past to perform efficient space mission planning under deterministic environments. These frameworks were established through heuristic methods [10], graph theory [11], simulations [12], and multi-commodity network flow models [1-3]. However, deterministic methods tend to give overly optimistic designs and bias anticipated mission performance.…”

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confidence: 99%

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Flexibility Management for Space Logistics Through Decision Rules

et al. 2020

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This paper develops a flexibility management framework for space logistics mission planning under uncertainty through decision rules and multi-stage stochastic programming. It aims to add built-in flexibility to space architectures in the phase of early-stage mission planning. The proposed framework integrates the decision rule formulation into a networkbased space logistics optimization formulation model. It can output a series of decision rules and generate a Pareto front between the expected mission cost (i.e., initial mass in low-Earth orbit) and the expected mission performance (i.e., effective crew operating time) considering

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Section: E Operating Time Loss Evaluation Through Decision Rulesmentioning

confidence: 99%

mentioning

confidence: 99%

Flexibility Management for Space Logistics Through Decision Rules

et al. 2020

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“…Earlier works focused on discrete-event simulation environment [2], followed by the graph-theoretic or network-based modeling of space logistics [3][4][5]. Based on the space logistics network, dynamic space mission design optimization methodologies have been established using the time-expanded generalized multi-commodity network flow model [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Space Exploration Architecture and Design Framework for Commercialization

Chen

Ornik

2022

Journal of Spacecraft and Rockets

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The trend of space commercialization is changing the decision-making process for future space exploration architectures, and there is a growing need for a new decision-making framework that explicitly considers the interactions between the mission coordinator (i.e., government) and the commercial players. In response to this challenge, this paper develops a framework for space exploration and logistics decision making that considers the incentive mechanism to stimulate commercial participation in future space infrastructure development and deployment. By extending the state-of-the-art space logistics design formulations from the game-theoretic perspective, we first analyze the relationship between the mission coordinator and commercial players and then derive the formulation for the optimal architecture design and incentive mechanism in three different scenarios. To demonstrate and evaluate the effectiveness of the proposed framework, we conduct a case study on lunar habitat infrastructure design and deployment. Results show how total mission demands and in-situ resource utilization (ISRU) system performances after deployment may impact the cooperation among stakeholders. As an outcome of this study, we derive an incentive-based decision-making framework that can benefit both the mission coordinator and the commercial

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“…Space logistics have largely been explored in the literature to optimize the design and planning of complex human space exploration missions through heuristics methods [16], simulations [17], the graph theory [18], or network flow models [19][20][21][22][23][24]. The method described in this paper extends the latter to accurately model OOS operations.…”

Section: Introductionmentioning

confidence: 99%

Framework for Modeling and Optimization of On-Orbit Servicing Operations Under Demand Uncertainties

Jonchay

Chen

Gunasekara

et al. 2021

Journal of Spacecraft and Rockets

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This paper develops a framework that models and optimizes the operations of complex onorbit servicing infrastructures involving one or more servicers and orbital depots to provide multiple types of services to a fleet of geostationary satellites. The proposed method extends the state-of-the-art space logistics technique by addressing the unique challenges in on-orbit servicing applications, and integrate it with the Rolling Horizon decision making approach. The space logistics technique enables modeling of the on-orbit servicing logistical operations as a Mixed-Integer Linear Program whose optimal solutions can efficiently be found. The Rolling Horizon approach enables the assessment of the long-term value of an on-orbit servicing infrastructure by accounting for the uncertain service needs that arise over time among the geostationary satellites. Two case studies successfully demonstrate the effectiveness of the framework for (1) short-term operational scheduling and (2) long-term strategic decision making for on-orbit servicing architectures under diverse market conditions.

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Modeling Space System Architectures with Graph Theory

Cited by 25 publications

References 9 publications

Flexibility Management for Space Logistics Through Decision Rules

Flexibility Management for Space Logistics Through Decision Rules

Space Exploration Architecture and Design Framework for Commercialization

Framework for Modeling and Optimization of On-Orbit Servicing Operations Under Demand Uncertainties

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