The exploration of planetary plasma environments often demands repeated, well-controlled encounters at varying geometries. For missions constrained by mass, cost, and propulsion capability, resonant gravity-assist trajectories provide an attractive alternative to orbit insertion. This paper presents a science-driven flyby selection methodology developed for a Venus resonant mission dedicated to the study of the Venusian magnetotail.
The algorithm was developed to support the Dungey-V mission concept, which seeks to obtain in-situ measurements of the Venusian magnetotail at varying altitudes and geometries to access whether the plasma has the same reconnection pattern as Earth. 

To address scientific objectives, Venus’ magnetotail is modeled as a cylindrical volume aligned with the antisolar direction and bounded by minimum and maximum altitudes relative to the planet’s radius. Candidate flyby trajectories are screened using periapsis distance limits and subsequently evaluated based on their intersection with the magnetotail volume. The primary selection metric employed in this study is the cumulative time spent inside the modeled magnetotail region, serving as an approximation of science data acquisition potential.

The algorithm constructs a branching tree of admissible flyby sequences, propagating outgoing velocities forward as inputs for subsequent encounters. Due to the combinatorial growth of the solution space, a staged pruning strategy is applied to maintain computational tractability while preserving trajectory diversity. Results demonstrate that thousands of valid multi-flyby sequences exist for a single initial Earth-to-Venus transfer, highlighting the robustness and flexibility of the resonant flyby approach.

The results indicate that resonant flyby missions can provide rich spatial and temporal coverage of plasma environments traditionally accessible only to orbiters, at substantially reduced propulsion cost. The presented approach is applicable beyond Venus and plasma study, and thus is a generalizable framework for multi-encounter mission design where science objectives directly drive flyby geometry selection.