A stochastic dynamic network model of the space environment
Wang, Yirui and Marchi, Pietro De and Vasile, Massimiliano (2024) A stochastic dynamic network model of the space environment. Other. arXiv, Ithaca, NY. (https://doi.org/10.48550/arXiv.2411.03173)
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Abstract
This work proposes to model the space environment as a stochastic dynamic network where each node is a group of objects of a given class, or species, and their relationship is represented by stochastic links. A set of stochastic dynamic equations, governing the evolution of the network, are derived from the network structure and topology. It will be shown that the proposed system of stochastic dynamic equations well reproduces existing results on the evolution of the space environment. The analysis of the structure of the network and relationships among node can help to understand which species of objects and orbit regimes are more critical and affect the most the future evolution of the space environment. In analogy with ecological networks, we develop a theory of the carrying capacity of space based on the stability of equilibria of the network dynamics. Some examples are presented starting from the current population of resident objects and different launch traffic forecast models. It will be shown how the proposed network model can be used to study the effect of the adoption of different policies on the execution of collision avoidance and post mission disposal manoeuvres.
ORCID iDs
Wang, Yirui, Marchi, Pietro De and Vasile, Massimiliano ORCID: https://orcid.org/0000-0001-8302-6465;-
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Item type: Monograph(Other) ID code: 91129 Dates: DateEvent5 November 2024PublishedSubjects: Technology > Motor vehicles. Aeronautics. Astronautics > Astronautics. Space travel
Science > PhysicsDepartment: Faculty of Engineering > Mechanical and Aerospace Engineering
Technology and Innovation Centre > Advanced Engineering and Manufacturing
Strategic Research Themes > Ocean, Air and SpaceDepositing user: Pure Administrator Date deposited: 12 Nov 2024 10:43 Last modified: 19 Dec 2024 01:10 URI: https://strathprints.strath.ac.uk/id/eprint/91129