Fusion burn-propagation simulations using the collisional and radiative particle-in-cell code <scp>triforce</scp>

The ability to accurately model burn propagation in inertial confinement fusion plasmas is crucial for advancing fusion energy research. This work presents enhancements to the triforce hybrid fluid-kinetic multiphysics code, focusing on its kinetic half, which employs the particle-in-cell (PIC) method with Monte Carlo collisions (MCC). We use a moment-preserving collision model that mitigates numerical noise, particularly in spherical geometries where particle weights vary significantly. Additionally, we refine the treatment of inverse bremsstrahlung to account for electron–ion collision frequency reductions in degenerate plasmas and incorporate a blackbody radiation source to enable realistic photon injection. These improvements enable the simulation of 1-dimensional (1D) spherical fusion burn propagation in deuterium–tritium plasmas. Benchmark comparisons with the hydra radiation-hydrodynamics code confirm that triforce accurately captures the dynamics of hot-spot expansion and burn propagation, demonstrating sensitivity to ignition thresholds consistent with theoretical models. Findings show the ignition cliff to be less steep in our work compared to radiation-hydrodynamic modeling. These results highlight the role of kinetic effects in fusion ignition physics and underscore the necessity of hybrid fluid-kinetic models for advancing predictive capabilities in high-energy-density plasma systems.

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Publication Details

Journal
Physics of Plasmas
Published
2025-05-01
DOI
https://doi.org/10.1063/5.0268289
Citations
1
Primary Topic
Laser-Plasma Interactions and Diagnostics
Type
article
Field-Weighted Citation Impact
1.87

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article

Fusion burn-propagation simulations using the collisional and radiative particle-in-cell code triforce

Michael Lavell, Eugene S. Evans, A. B. Sefkow, Ayden Kish et al.
1 citations
Physics of Plasmas
Laser-Plasma Interactions and Diagnostics
1.87
article

Fusion burn-propagation simulations using the collisional and radiative particle-in-cell code triforce

Michael Lavell, Eugene S. Evans, A. B. Sefkow, Ayden Kish, A. Sexton
article en
1 citations

Abstract

The ability to accurately model burn propagation in inertial confinement fusion plasmas is crucial for advancing fusion energy research. This work presents enhancements to the triforce hybrid fluid-kinetic multiphysics code, focusing on its kinetic half, which employs the particle-in-cell (PIC) method with Monte Carlo collisions (MCC). We use a moment-preserving collision model that mitigates numerical noise, particularly in spherical geometries where particle weights vary significantly. Additionally, we refine the treatment of inverse bremsstrahlung to account for electron–ion collision frequency reductions in degenerate plasmas and incorporate a blackbody radiation source to enable realistic photon injection. These improvements enable the simulation of 1-dimensional (1D) spherical fusion burn propagation in deuterium–tritium plasmas. Benchmark comparisons with the hydra radiation-hydrodynamics code confirm that triforce accurately captures the dynamics of hot-spot expansion and burn propagation, demonstrating sensitivity to ignition thresholds consistent with theoretical models. Findings show the ignition cliff to be less steep in our work compared to radiation-hydrodynamic modeling. These results highlight the role of kinetic effects in fusion ignition physics and underscore the necessity of hybrid fluid-kinetic models for advancing predictive capabilities in high-energy-density plasma systems.

Physics of PlasmasVol. 32(5)
Energetics (United States) (US), University of Rochester (US)
Advanced Research Projects Agency - Energy, National Nuclear Security Administration
Openalex Percentile: Top 14%
Laser-Plasma Interactions and Diagnostics
1.87
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Fusion burn-propagation simulations using the collisional and radiative particle-in-cell code <scp>triforce</scp> — Michael Lavell, Eugene S. Evans, et al. · Physics of Plasmas (2025) | TGRS Research Map | TGRS