Daniel Troyetsky

My research focuses on the development of physics-based and data-driven models of plasma for spacecraft electric propulsion systems. Together, these models represent a multipronged approach towards improving predictive engineering capabilities which can aid in the design and analysis of new devices.

Despite decades of research and development, the fundamental physics of Hall effect thrusters (HETs) are still not entirely understood, and fully predictive models have yet to be developed. The state-of-the-art simulations use heavily simplified descriptions of the plasma, neglecting electron inertia and assuming quasineutrality of the plasma. Combined, these prevent the self-consistent resolution electron shear effects and plasma sheaths, both of which are thought to play a role in anomalous electron transport. To work towards predictive modeling capabilities, we follow a multipronged approach of data-driven and physics-based modeling. We demonstrate that data assimilation can be used to estimate time-resolved plasma properties from a non-invasive discharge current measurement at the thruster anode by coupling a zero-dimensional global plasma model of a HET to an extended Kalman filter. We also show that a gradient-based optimization framework can be used to automate the model calibration process of the anomalous electron transport profile in a one-dimensional quasineutral drift-diffusion code. Lastly, we develop an axial-radial fluid model for HETs which maintains electron inertial effects and plasma non-neutrality.