Monte Carlo simulation of excitation and ionization collisions with complexity reduction

Hai P. Le, Bokai Yan, Russel Caflisch, Jean Luc Cambier

Research output: Contribution to journalArticle

Abstract

Kinetic simulation of plasmas with detailed excitation and ionization collisions presents a significant computational challenge due to the multiscale feature of the collisional rates. In the present work, we propose a complexity reduction method based on atomic level grouping for modeling excitation and ionization collisions. High order of accuracy of the reduction method is realized by allowing an internal distribution within each group. We apply the reduction method to the standard Monte Carlo collision algorithm to model an atomic Hydrogen plasma. Numerical results suggest that the stiffness of the collisional kinetics can be significantly reduced with minimal loss in accuracy.

Original languageEnglish (US)
Pages (from-to)480-496
Number of pages17
JournalJournal of Computational Physics
Volume346
DOIs
StatePublished - Oct 1 2017

Fingerprint

Ionization
ionization
collisions
excitation
Plasmas
Kinetics
simulation
kinetics
hydrogen plasma
stiffness
Stiffness
Hydrogen
Monte Carlo simulation

Keywords

  • Boltzmann equation
  • Complexity reduction
  • Excitation–deexcitation
  • H theorem
  • Ionization–recombination
  • Monte Carlo method

ASJC Scopus subject areas

  • Physics and Astronomy (miscellaneous)
  • Computer Science Applications

Cite this

Monte Carlo simulation of excitation and ionization collisions with complexity reduction. / Le, Hai P.; Yan, Bokai; Caflisch, Russel; Cambier, Jean Luc.

In: Journal of Computational Physics, Vol. 346, 01.10.2017, p. 480-496.

Research output: Contribution to journalArticle

Le, Hai P. ; Yan, Bokai ; Caflisch, Russel ; Cambier, Jean Luc. / Monte Carlo simulation of excitation and ionization collisions with complexity reduction. In: Journal of Computational Physics. 2017 ; Vol. 346. pp. 480-496.
@article{bb27ee70254a4d88a66a6a1318441e72,
title = "Monte Carlo simulation of excitation and ionization collisions with complexity reduction",
abstract = "Kinetic simulation of plasmas with detailed excitation and ionization collisions presents a significant computational challenge due to the multiscale feature of the collisional rates. In the present work, we propose a complexity reduction method based on atomic level grouping for modeling excitation and ionization collisions. High order of accuracy of the reduction method is realized by allowing an internal distribution within each group. We apply the reduction method to the standard Monte Carlo collision algorithm to model an atomic Hydrogen plasma. Numerical results suggest that the stiffness of the collisional kinetics can be significantly reduced with minimal loss in accuracy.",
keywords = "Boltzmann equation, Complexity reduction, Excitation–deexcitation, H theorem, Ionization–recombination, Monte Carlo method",
author = "Le, {Hai P.} and Bokai Yan and Russel Caflisch and Cambier, {Jean Luc}",
year = "2017",
month = "10",
day = "1",
doi = "10.1016/j.jcp.2017.06.029",
language = "English (US)",
volume = "346",
pages = "480--496",
journal = "Journal of Computational Physics",
issn = "0021-9991",
publisher = "Academic Press Inc.",

}

TY - JOUR

T1 - Monte Carlo simulation of excitation and ionization collisions with complexity reduction

AU - Le, Hai P.

AU - Yan, Bokai

AU - Caflisch, Russel

AU - Cambier, Jean Luc

PY - 2017/10/1

Y1 - 2017/10/1

N2 - Kinetic simulation of plasmas with detailed excitation and ionization collisions presents a significant computational challenge due to the multiscale feature of the collisional rates. In the present work, we propose a complexity reduction method based on atomic level grouping for modeling excitation and ionization collisions. High order of accuracy of the reduction method is realized by allowing an internal distribution within each group. We apply the reduction method to the standard Monte Carlo collision algorithm to model an atomic Hydrogen plasma. Numerical results suggest that the stiffness of the collisional kinetics can be significantly reduced with minimal loss in accuracy.

AB - Kinetic simulation of plasmas with detailed excitation and ionization collisions presents a significant computational challenge due to the multiscale feature of the collisional rates. In the present work, we propose a complexity reduction method based on atomic level grouping for modeling excitation and ionization collisions. High order of accuracy of the reduction method is realized by allowing an internal distribution within each group. We apply the reduction method to the standard Monte Carlo collision algorithm to model an atomic Hydrogen plasma. Numerical results suggest that the stiffness of the collisional kinetics can be significantly reduced with minimal loss in accuracy.

KW - Boltzmann equation

KW - Complexity reduction

KW - Excitation–deexcitation

KW - H theorem

KW - Ionization–recombination

KW - Monte Carlo method

UR - http://www.scopus.com/inward/record.url?scp=85021417324&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85021417324&partnerID=8YFLogxK

U2 - 10.1016/j.jcp.2017.06.029

DO - 10.1016/j.jcp.2017.06.029

M3 - Article

AN - SCOPUS:85021417324

VL - 346

SP - 480

EP - 496

JO - Journal of Computational Physics

JF - Journal of Computational Physics

SN - 0021-9991

ER -