Abstract

The solar sail is an exciting technology, enabling spacecraft to maneuver through space without expending propellant to reach their destinations. The Near Earth Asteroid (NEA) Scout mission, being developed by the Marshall Space Flight Center (MSFC) and the Jet Propulsion Laboratory (JPL), is implementing a solar sail on a 6U CubeSat platform to address a specific set of key strategic knowledge gaps laid out by NASA's Human Exploration and Operations Mission Directorate (HEOMD). NEA Scout's mission is to perform a close and slow encounter of a representative NEA as a robotic precursor for future human exploration. In addition to the resource limitations synonymous with small satellites, the NEA Scout flight system is further constrained by the implementation of the solar sail; for the CubeSat's expected 2.5-year mission, the solar sail is the flight system's primary attitude pointing constraint in order to achieve the trajectory needed to reach its target NEA. Due to the unique configuration challenges of fitting an 86 m2 solar sail in the vehicle, NEA Scout's solar panels and medium gain antenna are fixed in a plane parallel to the sail. With the sail pointing constraint, the flight system cannot optimally orient the solar panels directly at the sun, subjecting them to a continuous cosine loss in generation. This may be the first deep space mission that has been designed to nominally not point at the sun — a challenge that traditional systems engineering and power models are not designed to handle optimally. To meet these challenges for NEA Scout and other similar mission concepts, JPL has created a novel flight system analysis model to rapidly simulate and iterate trajectories against spacecraft subsystem performance. Following mission design trajectory inputs, the model performs a Monte Carlo simulation of the flight system's performance. The outputs are distributions of the telecommunications downlink time (important for navigation and data sufficiency) and solar sail cruise angle (important for recharging the batteries before the next downlink). These distributions are processed and give key insight into the feasibility of the reference trajectory and likelihood of mission success.

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