CHAOS: An octree-based PIC-DSMC code for modeling of electron kinetic properties in a plasma plume using MPI-CUDA parallelization

•Linearized Morton Z-ordered forest of octrees with 2:1 criterion are implemented to discretize the domain for PIC.•The Poisson's equation is discretized and solved the preconditioned conjugate gradient method using multiple CPUs and GPUs.•Particle-to-octree mapping and face-neighbor computatio...

Full description

Saved in:
Bibliographic Details
Published in:Journal of computational physics Vol. 373; pp. 571 - 604
Main Authors: Jambunathan, Revathi, Levin, Deborah A.
Format: Journal Article
Language:English
Published: Cambridge Elsevier Inc 15.11.2018
Elsevier Science Ltd
Subjects:
Computational physics
Conjugate gradient method
Debye length
Direct simulation Monte Carlo method
Distribution functions
Electric propulsion
Electron energy
Electron kinetics
Electron velocity distribution
Electrons
Forest of Morton-Z ordered linear octrees
Grid method
Heterogeneous architectures
Ion beams
Kinetics
Mathematical analysis
Neutralization of plasma plume
Octrees
Parallel processing
Partial differential equations
Particle-In-Cell
Plasma physics
Plumes
Poisson distribution
Poisson equation
Protons
Xenon
Particle-In-Cell
Heterogeneous architectures
Neutralization of plasma plume
Forest of Morton-Z ordered linear octrees
Electron kinetics
ISSN:0021-9991, 1090-2716
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:•Linearized Morton Z-ordered forest of octrees with 2:1 criterion are implemented to discretize the domain for PIC.•The Poisson's equation is discretized and solved the preconditioned conjugate gradient method using multiple CPUs and GPUs.•Particle-to-octree mapping and face-neighbor computations are performed using fast bitwise computations.•The strong-scaling studies showed near-ideal speedup with 128 GPUs.•For a shifted electron source, the EVDF was found to transition from bi-modal to a non-Maxwellian distribution with a single peak. A new computational framework for a coupled PIC-DSMC tool using multiple GPUs to model the kinetic behavior of electrons in plasma plumes is presented in this work. The disparate length scales of the Debye length and the collisional mean free path are resolved by using separate, independent linearized Morton Z-ordered forest of trees. A 2:1 restraint is imposed for the PIC module to solve partial differential equations in the context of an AMR/Octree framework. The MPI-CUDA parallelization strategies used to implement a preconditioned conjugate gradient method for solving the electrostatic Poisson's equation on the 2:1 octree are discussed and the scaling of the code to near ideal speedup as a function of the number of GPUs is demonstrated. The PIC method is validated using analytical test cases, and the octree-based PIC simulations are found to be ten times more efficient compared to the uniform grid method especially for plume simulations which have large density variations. The computational strategies are then demonstrated with the simulation of collisionless, mesothermal plasma plumes using a kinetic approach for both ions and electrons. The effect of ion mass and electron source location are analyzed by comparing plume dynamics and electron velocity distribution functions. It is shown that a more confined mesothermal plume is observed for the heavier xenon ions, present in electric propulsion devices, compared to protons. The confinement of the xenon plume traps the electrons resulting in higher electron temperatures compared to the proton plasma case. In both the simulations, however, the electron temperature is found to be anisotropic. Finally, when a shifted electron source location case is considered the electron velocity distributions in all three directions are found to be unequal and non-Maxwellian, contrary to the co-located case. The ion beam is observed to attract the electrons, which initially oscillate between the radial edges of the ion beam as confirmed by the bi-modal velocity distribution at early times. As the plume evolves, it electrostatically traps these electrons within the ion beam, allowing them to thermalize, as observed from the single-peak electron velocity distribution functions at later times. These results demonstrate that GPUs can efficiently accelerate computations of a fully kinetic approach to enable the study of electron kinetics and neutralization with the highest physical fidelity.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0021-9991
1090-2716
DOI:10.1016/j.jcp.2018.07.005