A Stochastic Dynamic Network Model of the Space Environment

2024-11-05

arXiv.org

AI Summary

Modeling the long-term evolution of the space environment remains challenging due to complex, stochastic interactions among orbital objects. Method: This study proposes a stochastic dynamic network framework: space objects are categorized as nodes, while probabilistic collision events and orbital coupling relationships constitute edges. Drawing an analogy to ecological networks, we establish a space carrying capacity theory; sustainable capacity is defined via stability analysis of the network’s equilibrium state, and policy interventions—such as collision avoidance and post-mission disposal—are quantified accordingly. The approach integrates stochastic processes, dynamic network theory, nonlinear dynamical systems analysis, and orbital mechanics. Contribution/Results: The model successfully reproduces historical debris growth trends, identifies critical node categories—including defunct satellites and spent rocket upper stages—and pinpoints high-risk regions, notably the LEO–SSO intersection zone. It significantly improves predictive accuracy for long-term impacts of launch traffic and mitigation strategies, thereby enhancing policy-relevant decision support.

Technology Category

• Reasoning under Uncertainty: Stochastic Optimization
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Humans and AI: Planning and Decision Support for Human-Machine Teams

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Web Mining and Content Analysis: Models for Web evolution
• Social Networks and Social Media: Social media analysis through the lenses of networks

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.

Problem

• Modeling space environment as stochastic dynamic network
• Analyzing critical object species and orbit regimes
• Studying policy effects on collision avoidance maneuvers

Innovation

• Stochastic dynamic network models space environment
• Equations derived from network structure and topology
• Theory of space carrying capacity based on stability