Theresa Bender
(Advisor: Prof. Dimitri Mavris)
"Methodological Improvements for the Integration of In-Space Trajectory Optimization into Conceptual Space Mission Design"
Friday, April 28th at 9:00 a.m.
Weber Space Science and Technology Building, CoVE
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Abstract
Trajectory design and optimization is a key element of space mission design. It provides information on the specific route a vehicle will take, as well as numerical estimates related to fuel consumption and transfer time. Since such estimates are generally required for the analysis of other subsystems and the overall mission, some level of trajectory design must be performed during the conceptual design phase. Due to the complexity, high computational costs, and long runtimes of high-fidelity trajectory analysis, less accurate methods are typically used. Low fidelity estimates provide sufficient accuracy for initial analyses; however, they often lack valuable information about the trajectory that is important to consider during the conceptual design phase. As a result, potential trajectory options that could impact mission concept of operations or objectives may not be considered.
This research will propose methodological improvements to the in-space trajectory design and optimization process in order to better incorporate it into conceptual space mission design studies. Spacecraft trajectory design is often a manual process requiring humans-in-the-loop and intermediate steps that hinder its integration into the conceptual space mission design process. This reliance on humans also makes it subject to human error and leaves open the possibility that parts of the design space may be overlooked. Although subject matter experts are critical to the design process and cannot be fully replaced, methods can be proposed that assist trajectory analysts in performing trajectory design and optimization in order to facilitate more complete and efficient analyses. In addition to methodological considerations, there are gaps in knowledge regarding how design inputs affect the trajectory solution space. This makes it difficult to perform efficient design space exploration and target certain solution types, particularly when mission requirements and constraints are continually evolving.
The first part of this research will provide a better understanding and characterization of the solution space in order to reveal relationships between solutions and design inputs. It is expected that commonalities will exist that can be used to better predict the behavior and variability of the solution space for similar problem types. The second part of this research will identify and quantify the identified relationships so that a methodology can be developed for determining how inputs can be strategically selected to improve the efficiency and completeness of design space exploration studies. This consists of finding inputs that provide a comprehensive spread of the solution space, lead to unique solutions, and exhibit strong convergence properties. These methods will then be leveraged to determine how trajectory optimization can most effectively be performed under loose constraints and evolving mission requirements. A final demonstration will be conducted to illustrate how the use of these methodologies can result in trades between trajectory design and other mission design considerations that are more efficient, accurate, and flexible than current methods allow.
Committee
- Prof. Dimitri Mavris – School of Aerospace Engineering (Advisor)
- Prof. Glenn Lightsey – School of Aerospace Engineering
- Prof. John Christian – School of Aerospace Engineering
- Prof. Mariel Borowitz – School of International Affairs
- Dr. Michael Steffens – School of Aerospace Engineering