Hedging direct simulation Monte Carlo bets via event splitting

Oblapenko, Georgii; Goldstein, David; Varghese, Philip L.; Moore, Christopher

doi:10.1016/j.jcp.2022.111390

Cited by 5 publications

(4 citation statements)

References 32 publications

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“…To reduce the computational cost, a variable MP weight is implemented. While other splitting methods [38] and radial weighting methods are available particularly for DSMC calculations [11,39], we focus on the application of the radial weighting scheme to a PIC/MCC simulation for LTP discharges. Noticing that the cell volume ratio between r = 0 and an arbitrary r is V 1 /V 2 = 2r/∆r, a linear particle weighting is considered in this paper.…”

Section: Variable Particle Weightingmentioning

confidence: 99%

Effects of macroparticle weighting in axisymmetric particle-in-cell Monte Carlo collision simulations

Hara

Robertson²,

Kenney³

et al. 2023

Plasma Sources Sci. Technol.

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In this paper, the eﬀects of macroparticle weighting on the plasma discharge, particularly near the centerline, are investigated using a two-dimensional axisymmetric particle-in-cell Monte Carlo collision (PIC/MCC) model. A variable macroparticle weight according to the radial position of the macroparticles is employed to maintain suﬃcient number of macroparticles near the centerline of the plasma source. The plasma density obtained from the PIC/MCC simulations for low-pressure (25-100 mTorr) capacitively coupled plasmas (CCPs) is found to be artiﬁcially large when the macroparticle weight near the centerline is not well resolved, demonstrating the need for particle convergence studies for axisymmetric PIC/MCC simulations.

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Section: Variable Particle Weightingmentioning

confidence: 99%

Effects of macroparticle weighting in axisymmetric particle-in-cell Monte Carlo collision simulations

Hara

Robertson²,

Kenney³

et al. 2023

Plasma Sources Sci. Technol.

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“…Our proposed algorithm, which we will refer to as "event splitting" [8,12], consists of the following steps: an additional particle split is performed for the two equal-weight particles based on the probabilities of the possible collision events that can occur for the considered collision. After the initial split step (during which the particle with the larger computational weight is split into two smaller particles) the (equal weight) particles are split further into smaller particles, with weights 2 , = 1, .…”

Section: Event Splitting In Variable Weight Dsmcmentioning

confidence: 99%

Improving PIC-DSMC Simulations of Electrical Breakdown via Event Splitting

Oblapenko

Goldstein

Varghese

et al. 2022

AIAA SCITECH 2022 Forum

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A newly developed variable-weight DSMC collision scheme for inelastic collision events is applied to PIC-DSMC modelling of electrical breakdown in 1-dimensional helium and argon-filled gaps. Application of the collision scheme to various inelastic collisional and gas-surface interaction processes (electron-impact ionization, electronic excitation, secondary electron emission) is considered. The collision scheme is shown to improve the level of noise in the computed current density compared to the commonly used approach of sampling a single process, whilst maintaining a comparable level of computational cost and providing less variance in the average number of particles per cell.

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“…with higher probabilities are simulated more frequently. In contrast, within the framework of the "event splitting" scheme, 19 the colliding particles (with weights w 2 ) are split further proportionally to the probabilities p i . After the splitting, all of the newly created particles (with weights w 2 p i , i = 1, .…”

Section: Variable Weight Dsmc Collision Schemesmentioning

confidence: 99%

“…Another approach to improvement of modelling of low-probability processes was recently proposed, 19,20 dubbed "event splitting", in which the variable-weight particles are split proportionally to the probabilities of processes that can take place during a given collision. It was shown that use of event splitting for collisions and boundary conditions with secondary emission can noticeably reduce the noise in PIC-DSMC simulations compared to the use of standard sampling approaches to collision process modelling.…”

Section: Introductionmentioning

confidence: 99%

Improving PIC-DSMC Simulations of RF Plasmas via Event Splitting.

Oblapenko,

Goldstein,

Varghese

et al. 2022

Proposed for Presentation at the 9TH EUROPEAN CONFERENCE FOR AERONAUTICS AND AEROSPACE SCIENCES (EUCASS) Held June 27-July 1, 2

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Particle-in-Cell Direct Simulation Monte Carlo (PIC-DSMC) is a widely used method for simulation of non-equilibrium plasmas, especially when the plasma flow is rarefied, and the applicability of fluid models is questionable. However, the PIC-DSMC method is subject to stochastic noise, and depending on the process being simulated, might require extremely large computational efforts. Therefore, the improvement of accuracy of PIC-DSMC methods is a topic of active research. In the present work, a recently developed collision and boundary condition treatment scheme, dubbed "event splitting", which aims at improving simulation of low-probability processes, is applied to ionization processes in xenon and helium plasmas, where it shown to reduce the level of stochastic noise compared to standard DSMC collision schemes.

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Hedging direct simulation Monte Carlo bets via event splitting

Cited by 5 publications

References 32 publications

Effects of macroparticle weighting in axisymmetric particle-in-cell Monte Carlo collision simulations

Effects of macroparticle weighting in axisymmetric particle-in-cell Monte Carlo collision simulations

Improving PIC-DSMC Simulations of Electrical Breakdown via Event Splitting

Improving PIC-DSMC Simulations of RF Plasmas via Event Splitting.

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