A Parallelized Genetic Algorithm to Evaluate Asteroid Impact Missions Using Electric Propulsion

A streamlined genetic algorithm was developed and implemented on a GPU to evaluate low-thrust trajectories of spacecraft propelled by an ion thruster. It was then applied to examine the utility of a specific thruster for an asteroid impact mission. This method was validated by comparing impact speeds of non-thruster results with the DART mission, which does not significantly use the equipped ion thruster. Then, by utilizing the ion thruster for prolonged periods, this model demonstrated the possibility of significant increases in the impact speed and significant decreases in the trip times. This specific test case was used to examine the utility of the model and, by methodically varying relevant variables, this article shows the influence of the genetic algorithm on the results. By examining a range of electrical power levels, the results presented here provide hints as to the possible effects of spacecraft design trade-offs on impact speed. The analysis of the effects of the algorithm on the results and the evaluation of thruster operating parameters indicate the applicability of this model to a variety of spaceflight missions.

Automated summary

This article introduces a streamlined genetic algorithm implemented on a GPU to evaluate low-thrust trajectories of spacecraft propelled by an ion thruster. The results demonstrate the utility of utilizing the ion thruster to significantly increase impact speed and decrease trip times, as well as the influence of spacecraft design trade-offs on impact speed. The analysis and evaluation indicate the applicability of this model to various spaceflight missions.