Bayesian Calibration of a Multi-Component Model of the SPT-140 Hall Thruster

We deploy the Joint Advanced Propulsion Institute's (JANUS's) Hall thruster Predictive Engineering Model (PEM) model on the SPT-140 system qualified and flown for NASA's Psyche spacecraft. The purpose of the PEM is to enable rapid predictions and uncertainty quantification of system performance while accounting for facility effects associated with ground-based testing. The most recent instantiation of the PEM framework consists of an analytical model predicting cathode coupling voltage, a 1-D axial fluid Hall thruster code predicting the main discharge, and an analytical plume expansion model predicting ion current density traces. The primary facility effect they capture is background pressure. To deploy the PEM for the SPT-140, we extended the models to enable scaling the Hall thruster's magnetic field at different operating conditions. We then calibrated the PEM using data from ground qualification tests performed by NASA's Jet Propulsion Laboratory (JPL). These datasets include thrust, discharge current, and ion acceleration measurements. A Bayesian calibration of the model parameters yields a posterior consistent with previous calibrations on the SPT-100 and H9 thrusters. Unlike standard practice, where anomalous collisions are calibrated to individual operating conditions, we use a single anomalous transport model parameterized by pressure. Thus we provide initial evidence for predictive capabilities of target quantities of interest. Following calibration, we extrapolate the model predictions to vacuum. Thrust predictions at higher powers are shown to be comparable to modeling by JPL using Hall2De done during qualification, while discharge current data are not reliably predicted. The mismatch of discharge current is attributed to the fact that the PEM assumes a fixed anomalous collision frequency profile whose position shifts with pressure.