NASA NTRS · 20150010981
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D'Souza, Sarah. 2015-05-21. Adapting Guidance Methodologies for Trajectory Generation in Entry Shape Optimization. https://ntrs.nasa.gov/citations/20150010981
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The experimental, fully electric X-57 Maxwell is designed to enable lower energy con-sumption at cruise compare to a fuel burning baseline. This is to be achieved using a sumof subsystem benefits incorporated in the electric, airframe, and propulsion systems. AMission Planning Tool captures the three stages of X-57 development in order to assess thedesign of each subsystem in the context of the whole aircraft. The Mission Planning Toolfor the fully electric X-57 Maxwell captures the aerodynamics, propulsion, heat transfer,and power system of the aircraft with trajectory optimization capabilities. It is able tomodel these subsystems through all phases of flight, from taxi to landing. Through thismultidisciplinary approach, we are able to predict the benefit of each subsystem and theeffect of key design assumptions and how the aircraft will react if they are not met or ex-ceeded. As the aircraft progresses and systems are tested, we can use the Mission PlanningTool to continue to predict performance. This paper details the continued development ofthe X-57 Mission Planning Tool and demonstrates its capabilities.
This paper presents an algorithm to rapidly generate trajectories for a kinematic fixed-wing Unmanned Aircraft System (UAS) model flying at constant altitude in a uniform wind field. Arrival times are specified by operators and rapid generation is accomplished via an elliptic integral problem formulation. Simulations are provided that illustrate this approach in the context of NASA's UAS Traffic Management Project.
Low-thrust trajectory design is tightly coupled with spacecraft systems design. In particular, the propulsion and power characteristics of a low-thrust spacecraft are major drivers in the design of the optimal trajectory. Accurate modeling of the power and propulsion behavior is essential for meaningful low-thrust trajectory optimization. In this work, we discuss new techniques to improve the accuracy of propulsion modeling in low-thrust trajectory optimization while maintaining the smooth derivatives that are necessary for a gradient-based optimizer. The resulting model is significantly more realistic than the industry standard and performs well inside an optimizer. A variety of deep-space trajectory examples are presented.