Data Mining-Based Cislunar Escape-Family Analysis in The Multi-Body Models

TL;DR

This paper introduces a comprehensive analysis of escape trajectories from Earth-Moon and Sun-Earth/Moon systems using data mining and dynamical analysis to identify escape families and understand their characteristics.

Contribution

It proposes a novel methodology combining data mining and dynamical analysis to identify and analyze escape trajectory families in multi-body gravitational models.

Findings

Solar gravity perturbation affects escape trajectory numbers.

Escape families can emerge or disappear due to perturbations.

Insights into model selection for escape trajectory design.

Abstract

Escape trajectories from the Earth-Moon system play an important role in interplanetary transfer. This paper focuses on the escape trajectories from a 167 km circular Earth orbit in the Earth-Moon planar circular three-body problem and the Sun-Earth/Moon planar bicircular four-body problem and is denoted to providing a comprehensive analysis on these escape trajectories. To achieve these purposes, the global maps of escape trajectories are constructed, and escape trajectories with one lunar gravity assist are pre-filtered. Then, an effective method to identification escape families is proposed based on dynamical analysis and data mining techniques. Once the escape families are identified, the corresponding characteristics are analyzed to provide insights into the construction of escape trajectories. Based on these escape families, the effects of the solar gravity perturbation on the number of escape trajectories, the emergence and disappearance of escape families, variation in generalized energy, and transfer characteristics are further summarized, providing insights into the model selection in the escape trajectory construction. This paper establishes an analysis methodology of escape trajectories from a perspective of escape families, deepening the understanding of escape dynamics.