Hall Thruster Plume Data Analysis – ASU
INSTITUTION
Arizona State University
CLASS
Nickel Class (2020 – 2021)
STUDENT TEAM
Mitchell Bucklew, Computer Science
Joshua Knoll, Informatics
Tatiana Koski, Engineering Management
Nitin Miyyapuram, Computer Science
Jessica (Jess) Sherman, Informatics
Ruijun Yang, Computer Science
SCIENTIFIC & TECHNICAL GUIDANCE
Dr. Jason Frieman, NASA Glenn Research Center
ACADEMIC GUIDANCE
Dr. Helen Chavez, Lecturer, School of Computing, Informatics, and Decision Systems Engineering, ASU
Dr. Joe Juarez, Lecturer, School of Computing, Informatics, and Decision Systems Engineering, ASU
PROJECT DESCRIPTION
The Psyche spacecraft will rely on a type of electric propulsion known as Hall thrusters in order to propel itself from Earth to the Psyche asteroid. During operation, these thrusters exhaust a hemispherical cloud of plasma known as a plume. Knowledge of the shape and composition of this plume is important in order to understand how well the thruster is operating as well as verify that the plume does not impact (and potentially damage) any sensitive spacecraft components. During ground tests, the plume shape is measured by obtaining measurements at discrete locations, which then need to be analyzed in order to determine an estimate for the plume centroid. The student team applied statistical and machine learning techniques to NASA-provided datasets in order to generate improved regressions and predictions of the plume centroid and implemented these centroid predictions into a 3-D plume visualization.