Development of reduced-order models of the ion impact distribution function in magnetized plasma sheaths

Mustafa, Mohammad Abdul-Jalil Mohammad

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https://hdl.handle.net/2142/120312 Copy

Description

Title

Development of reduced-order models of the ion impact distribution function in magnetized plasma sheaths

Author(s)

Mustafa, Mohammad Abdul-Jalil Mohammad

Issue Date

2023-04-24

Director of Research (if dissertation) or Advisor (if thesis)

Curreli, Davide

Committee Member(s)

Kozlowski, Tomasz

Department of Study

Nuclear, Plasma, & Rad Engr

Discipline

Nuclear, Plasma, Radiolgc Engr

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• Plasma physics
• Plasma sheath
• Plasma-surface interactions
• Reduced-order model
• Sensitivity analysis
• Machine learning
• Uncertainty quantification
• Surrogate modeling
• Ion Energy-Angle Distributions

Abstract

In magnetic-confinement fusion devices, high-fidelity models of the energy-angle distribution of the ions impacting on material walls are crucial for characterizing ion-surface interactions and impurity release. Typically, the Ion Energy-Angle Distributions (IEADs) are simulated using plasma kinetic models (e.g. Particle-In-Cell PIC codes, such as hPIC), which are usually computationally intensive. In this work, we constructed an effective surrogate model for the IEADs by means of a data-driven strategy in high-dimensional parameter space. The surrogate model considers up to four input parameters of relevance to the problem: (1) electron-to-ion temperature ratio, (2) magnetic field inclination, (3) magnetic field strength, and (4) plasma density. The hPIC2 code was utilized to generate necessary training and testing data sets. A sparse grid was employed to reduce the cost of the surrogate model construction without compromising accuracy. Least square approximation using data from a denser sparse grid was utilized to mitigate the effect of particle noise. Fitting of IEAD was performed in a transformed coordinate system of the distribution. Additionally, an artificial neural network strategy based on zero-inflated models was employed to construct a surrogate model of plasma sheath potentials. The surrogate models constructed as part of this work provide computationally efficient tools to emulate the output of hPIC with limited errors. A variance-based sensitivity analysis using samples drawn from the surrogate models was performed. The sensitivity analysis of plasma potentials showed that the floating wall potential is solely affected by the electron-to-ion temperature ratio, whereas the potential drop across the magnetic presheath and Debye sheath were significantly affected by the magnetic field inclination angle. The sensitivity analysis of the IEAD moments also showed a strong dependency of ions' impact energy on the electron-to-ion temperature ratio with insignificant dependence on the other physical parameters. On the other hand, the analysis revealed significant dependencies of ions' angle of impact on electron-to-ion temperature ratio and magnetic field inclination angle, with a much lower effect of the remaining parameters.

Graduation Semester

2023-05

Type of Resource

Thesis

Copyright and License Information

Copyright 2023 Mohammad Mustafa

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