Date of Award

6-2015

Degree Name

MS in Aerospace Engineering

Department

Aerospace Engineering

Advisor

Kira Abercromby

Abstract

Ever since the revolutionary CubeSat form factor took hold in the Aerospace industry, there has been a desire to send them further and further into space. This thesis introduces an optimization approach to deployment that explores new possibilities of interplanetary CubeSats. In this approach there are three categories of objective functions that are defined by the type of trajectory of a “primary” spacecraft, which carries the CubeSat deployer. These categories are flyby, orbiter, and lander. For each category the objective function starts with four design variables. These are the ΔV of the deployer broken up into three component directions and the true anomaly at the time of deployment. The method then calculates the mission specific objective to be minimized and uses Matlab®’s built in gradient-based optimizer, fmincon. The results show that in the flyby category, the CubeSat has a significantly different turning angle than the primary. The CubeSat can even flyby on the opposite side of the planet. In the orbiter case it is shown that the method works by testing it with two objective functions, the difference in inclination and the difference in eccentricity between the primary and the CubeSat. It is shown that the inclination can be changed by 0.1314° and the eccentricity can be changed by 0.0033. These values, although low in magnitude, are an order of magnitude greater than non-optimal deployment scenarios. Still, another optimization method is introduced to find out how much extra ΔV the CubeSat would need to reach a desired change. This shows that with just an extra 75 m/s of ΔV, the CubeSat can change its orbit by 5°. This could come from either a propulsion system or a modified deployer. The final category, lander, used the flight path angle when entering the atmosphere as an objective. The method shows that flight path angle can be changed by 2.6°. Overall, these examples have proven that the method can find optimal solutions to CubeSat deployment scenarios at other planets.

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