Bulletin of the American Physical Society
66th Annual Meeting of the APS Division of Plasma Physics
Monday–Friday, October 7–11, 2024; Atlanta, Georgia
Session CP12: Poster Session II:
Science Education, Public Engagement and DEI
High School
Undergraduate
2:00 PM - 5:00 PM
Monday, October 7, 2024
Hyatt Regency
Room: Grand Hall West
Abstract: CP12.00096 : Engineering Design of a Magnetic Reconnection Thruster Using Permanent Magnets*
Presenter:
Yohannes Mergia
(University of California, Los Angeles)
Authors:
Yohannes Mergia
(University of California, Los Angeles)
Fatima Ebrahimi
(Princeton Plasma Physics Laboratory (PPPL))
Kenneth C Hammond
(Princeton Plasma Physics Laboratory (PPPL))
Jiawen Wang
(Princeton Plasma Physics Laboratory)
Michael Zarnstorff
(Princeton University)
A novel concept for space propulsion was introduced by leveraging the conversion of magnetic energy into kinetic energy through magnetic reconnection within an annular channel (Ebrahimi, F. (2020). An Alfvenic reconnecting plasmoid thruster. Journal of Plasma Physics, 86(6)).
It has been shown that exhaust velocities ranging from 20 to 500 km/s, vastly surpassing the 2 to 4 km/s of conventional thrusters can be achieved. The thrust can range at least from a tenth of a newton to tens of newtons. Here, we present the design of this magnetic reconnection thruster utilizing permanent magnets instead of traditional coils. By employing permanent magnets, the system offers significant efficiency, simplicity, durability, and cost advantages.
This thruster design uses permanent magnets to inject linked magnetic field lines into an annular channel, driving current along open field lines to create twister magnetic field lines and forming an elongated current sheet that becomes unstable, triggering spontaneous magnetic reconnection and plasmoid creation. Optimization of the permanent magnet configuration is achieved by employing the Simsopt simulation tool with GPMO (Greedy Permanent Magnet Optimization) and Relax and Split algorithms. GPMO uses a greedy algorithm to iteratively place magnets, selecting positions that most reduce the mean squared error (MSE). A relax-and-split algorithm, suited for high-dimensional sparse regression, alternates between convex and nonconvex subproblems for efficiency. Both optimization methods for thruster design with permanent magnets will be presented. This work is supported by DOE.
*This work is funded by the Department of Energy (DOE).
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