The BRADLEY DEPARTMENT of ELECTRICAL and COMPUTER ENGINEERING

ECE 6174 Computational Plasma Dynamics | ECE | Virginia Tech

Graduate PROGRAMS

Course Information

Description

Computational techniques for investigating processes in plasmas over a broad range of spatial and temporal scales. Investigation of physical processes including electrodynamics, waves and turbulence, space propulsion, spacecraft environmental effects and various laboratory applications. Computational techniques including full Particle-in-Cell (PIC), hybrid (fluid-electron, PIC ion), magnetohydrodynamics MHD and two-fluid methods.

Why take this course?

The near-earth space plasma environment has profound effects on radio waves, el3ectrical devices, power systems, satellites, space vehicles, as well as humans. As society becomes more dependent on technologies embedded in this environment, more physical understanding and predictive capabilities in terms of 'space weather' will become crucial. Other critical plasma applications are linked to nuclear fusion energy. The plasma medium is highly variable and highly nonlinear. There may be a broad range of turbulent structure spanning many orders of magnitude. Also, the interaction of objects (e.g. spacecraft, antennas, etc.) imbedded in plasmas is typically a challenging problem. Because of this complexity, computational models have become more important than approximate theoretical models for investigating physical processes and the associated impact on technological systems. This course provides students with techniques to study physical processes in such plasma environments over a relatively broad range of spatial and temporal scales and provides discussion of implications of these processes on modern technology.

Prerequisites

5174 or AOE 5174

Advanced knowledge of plasma physics and computational techniques for plasmas which was presented in 5174, builds on the thorough understanding of advanced nonlinear plasma physics concepts, multiple plasma models , and synthesizes the existing literature.

Major Measurable Learning Objectives

  • Design and utilize basic Particle-In-Cell (PIC) computational models to investigate plasma problems.
  • Design and utilize basic hybrid (fluid-electron and PIC ion) computational models to investigate plasma problems.
  • Design and utilize basic magnetohydrodynamic (MHD) and/or two-fluid plasma computational models to investigate plasma problems.
  • Design and utilize basic magnetohydrodynamic (MHD) and/or two-fluid plasma computational models to investigate plasma problems.
  • Assess appropriate High Performance Computing (HPC) resources for solution of computational plasma problems.

Course Topics

Topic

Percentage of Course

1. Introduction: Plasma models, space and time scales 10%
2. Electrostatic Particle-in-Cell Model in 1D 10%
3. Electrostatic Particle-in-Cell Model in Multiple Dimensions 10%
4. Electromagnetic Particle-in-Cell Model 10%
5. Electrostatic Hybrid Models 10%
6. Electromagnetic Hybrid Models 10%
7. Pseudo-spectral Method and Time Stepping Schemes 10%
8. Ideal and Resistive Magnetohydrodynamics (MHD) 10%
9. Two-Fluid Plasma Model 10%
10. Computational Techniques for MHD and Two-Fluid Models 10%