Preliminary design of a hybrid motor for small-satellite propulsion

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Abstract/Contents

Abstract
Small-satellites are a low-cost, low-risk option for an increasing number of applications, including Earth observation and interplanetary exploration. However, their ranges of operation are limited by their ability to carry out critical maneuvers in space and could be further expanded with high-performance micropropulsion systems. Hybrid motors are a type of chemical propulsion option that utilize propellants stored in two different phases, typically a solid fuel and a liquid or gaseous oxidizer. For a small-satellite, a hybrid system would be better suited for rapid, large Delta-v maneuvers than electric thrusters. They have restart and throttling capabilities, and their inherent design makes them safer and more cost-efficient than hydrazine-based liquid engines. The delivered specific impulse is comparable to conventional bipropellant systems (300--350 s). As a result, they are a prime candidate for in-space applications requiring long-term propellant storage and low gross mass. However, with no flight heritage, the technology readiness level of small-scale hybrid motors remains low, and the fundamental understanding and modeling of the combustion phenomena is still immature. To be considered more consistently in system trade studies, the accuracy of preliminary design models and performance estimations must be improved. This thesis work provides a framework for consistent preliminary design analyses to further compare and assess the capabilities of small-scale hybrid motors. Fuel selection and other design choices are discussed. The benefits of using an optimization scheme to determine the best operational parameters are outlined. To improve the quantitative results, it was established that two parameters require further investigation: the solid fuel regression rate and the characteristic velocity c* efficiency. To further improve our understanding of hybrid combustion phenomena, an experimental setup was designed to measure the performance of a small-scale motor using gaseous oxygen and solid polymethylmethacrylate (PMMA). To calculate the instantaneous characteristic velocity, the total mass flow rate expelled during the hotfire must be determined. This requires an accurate measurement of the fuel regression rate in space and time. A non-intrusive, easy-to-implement, and low-cost measurement technique was developed using an optically clear fuel and a high-resolution camera, providing temporally and spatially resolved data. More than 60 hotfires were carried out to validate the method and collect data for a wide range of conditions including varying motor geometry and oxidizer mass flow rates. Experimental investigations led to multiple findings that can further advance our ability to design efficient hybrid motors. In particular, the injection scheme⁠—rarely discussed in regression rate modeling⁠—was found to have a large impact on the fuel regression rate and motor stability. Nozzle erosion and c* efficiency were also measured and guidelines to influence them are outlined.

Description

Type of resource text
Form electronic resource; remote; computer; online resource
Extent 1 online resource.
Place California
Place [Stanford, California]
Publisher [Stanford University]
Copyright date 2019; ©2019
Publication date 2019; 2019
Issuance monographic
Language English

Creators/Contributors

Author Mechentel, Flora Stephanie
Degree supervisor Cantwell, Brian
Thesis advisor Cantwell, Brian
Thesis advisor Bowman, Craig T. (Craig Thomas), 1939-
Thesis advisor Mitchell, Reginald
Degree committee member Bowman, Craig T. (Craig Thomas), 1939-
Degree committee member Mitchell, Reginald
Associated with Stanford University, Department of Aeronautics and Astronautics.

Subjects

Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Flora Stephanie Mechentel.
Note Submitted to the Department of Aeronautics and Astronautics.
Thesis Thesis Ph.D. Stanford University 2019.
Location electronic resource

Access conditions

Copyright
© 2019 by Flora Stephanie Mechentel
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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