Numerical Analysis of Fluid Estimation for Source Terms in Neutral Particle Simulations

ABSTRACT In plasma edge simulations, kinetic Monte Carlo (MC) is often used to simulate neutral particles and estimate source terms. For large‐sized reactors, like ITER and DEMO, high particle collision rates lead to a substantial computational cost for such schemes. To address this challenge, an asymptotic‐preserving kinetic‐diffusion Monte Carlo (KDMC) simulation method and a corresponding fluid estimation technique have been proposed in the literature. In this work, we perform numerical analysis on the convergence of KDMC with the fluid estimation. To do so, we compare the accuracy of the analyzed algorithm with the accuracy of an approximate fluid method using the kinetic MC method as a reference. In a one‐dimensional test case, KDMC with the fluid estimation achieves at least one order of magnitude lower errors than the fluid method for both high‐ and low‐collisional regimes. Moreover, KDMC with the fluid estimation outperforms the kinetic MC method with a clear speed‐up. Overall, our analysis confirms the effectiveness of the discussed algorithm.

Authors

Institutions

Publication Details

Journal
Contributions to Plasma Physics
Published
2026-04-20
DOI
https://doi.org/10.1002/ctpp.70129
Primary Topic
Nuclear reactor physics and engineering
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Numerical Analysis of Fluid Estimation for Source Terms in Neutral Particle Simulations

Giovanni Samaey, Zhirui Tang, Emil Løvbak, Julian Koellermeier
Contributions to Plasma Physics
Nuclear reactor physics and engineering
article

Numerical Analysis of Fluid Estimation for Source Terms in Neutral Particle Simulations

Giovanni Samaey, Zhirui Tang, Emil Løvbak, Julian Koellermeier
article en

Abstract

ABSTRACT In plasma edge simulations, kinetic Monte Carlo (MC) is often used to simulate neutral particles and estimate source terms. For large‐sized reactors, like ITER and DEMO, high particle collision rates lead to a substantial computational cost for such schemes. To address this challenge, an asymptotic‐preserving kinetic‐diffusion Monte Carlo (KDMC) simulation method and a corresponding fluid estimation technique have been proposed in the literature. In this work, we perform numerical analysis on the convergence of KDMC with the fluid estimation. To do so, we compare the accuracy of the analyzed algorithm with the accuracy of an approximate fluid method using the kinetic MC method as a reference. In a one‐dimensional test case, KDMC with the fluid estimation achieves at least one order of magnitude lower errors than the fluid method for both high‐ and low‐collisional regimes. Moreover, KDMC with the fluid estimation outperforms the kinetic MC method with a clear speed‐up. Overall, our analysis confirms the effectiveness of the discussed algorithm.

Contributions to Plasma Physics
Karlsruhe Institute of Technology (DE), University of Groningen (NL), Ghent University (BE), KU Leuven (BE)
EUROfusion, Deutsche Forschungsgemeinschaft, Fonds Wetenschappelijk Onderzoek
Openalex Percentile: Top 4%
Nuclear reactor physics and engineering
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.