Numerical study of viscosity and heat flux role in heavy species dynamics in Hall thruster discharge

A two-and three-dimensional velocity space axisymmetric hybrid-PIC model of Hall thruster discharge called Hybrid2D has been developed.The particle-in-cell(PIC) method was used for neutrals and ions(heavy species),and fluid dynamics on a magnetic field-aligned(MFA) mesh was used for electrons.A time-saving method for heavy species moment interpolation on a MFA mesh was developed.The method comprises using regular rectangle and irregular triangle meshes,connected to each other on a pre-processing stage.The electron fluid model takes into account neither inertia terms nor viscous terms and includes an electron temperature equation with a heat flux term.The developed model was used to calculate all heavy species moments up to the third one in a stationary case.The analysis of the viscosity and the heat flux impact on the force and energy balance has shown that for the calculated geometry of the Hall thruster,the viscosity and the heat flux terms have the same magnitude as the other terms and could not be omitted.Also,it was shown that the heat flux is not proportional to the temperature gradient and,consequently,the highest moments should be calculated to close the neutral fluid equation system.At the same time,ions can only be modeled as a cold non-viscous fluid when the sole aim of modeling is the calculation of the operating parameters or distribution of the local parameters along the centerline of the discharge channel.This is because the magnitude of the viscosity and the temperature gradient terms are negligible at the centerline.However,when a simulation’s focus is either on the radial divergence of the plume or on magnetic pole erosion,three components of the ion temperature should be taken into consideration.The non-diagonal terms of ion pressure tensor have a lower impact than the diagonal terms.According to the study,a zero heat flux condition could be used to close the ion equation system in calculated geometry.

Machine learning-based method to adjust electron anomalous conductivity profile to experimentally measured operating parameters of Hall thruster

The problem of determining the electron anomalous conductivity profile in a Hall thruster,when its operating parameters are known from the experiment,is considered.To solve the problem,we propose varying the parametrically set anomalous conductivity profile until the calculated operating parameters match the experimentally measured ones in the best way.The axial 1D3V hybrid model was used to calculate the operating parameters with parametrically set conductivity.Variation of the conductivity profile was performed using Bayesian optimization with a Gaussian process(machine learning method),which can resolve all local minima,even for noisy functions.The calculated solution corresponding to the measured operating parameters of a Hall thruster in the best way proved to be unique for the studied operating modes of KM-88.The local plasma parameters were calculated and compared to the measured ones for four different operating modes.The results show the qualitative agreement.An agreement between calculated and measured local parameters can be improved with a more accurate model of plasma-wall interaction.