Visual tools for 3D plasma simulation: GPU-based isosurface extraction and particle-based rendering
- 1College of AI and Convergence (Dept. of Artificial Intelligence, Design Technology), Graduate School of Electrical and Computer Engineering, Inha University, Michuhol-gu, Incheon, South Korea
- 2Department of Convergence Software, Hallym University, Chuncheon, South Korea
- 3Department of Computer Engineering, Hanbat National University, Yuseong-gu, Daejeon, South Korea
Abstract
This paper presents a GPU-accelerated visualization framework for interactive exploration of fusion-plasma simulation data represented as scalar fields and particle trajectories. The primary technical contribution is a capacity-safe isosurface-extraction pipeline that combines inclusive slab partitioning with a two-pass counting and exact allocation strategy. This design prevents slab-boundary omissions and output-buffer overflow while supporting large scalar grids. The generated positions and normals are written directly to CUDA–OpenGL interoperable buffers, enabling the standalone renderer to display explicit isosurfaces without an intermediate CPU-side copy. The extracted geometry and scalar-volume data are additionally integrated into Unreal Engine through a separate staging interface. This integration provides a unified environment for volume rendering, explicit-isosurface inspection, particle-trajectory visualization, clipping, and VR-based spatial exploration. These engine-side functions are used as interaction and visualization mechanisms rather than being presented as new rendering algorithms. Experiments on electromagnetic-potential fields with resolutions up to 5123 demonstrate stable isosurface extraction across different isovalues. In the most geometrically complex tested case, the method generates approximately 42.81 million vertices in 44.7 ms, uses less than 11 GB of GPU memory, and renders the resulting geometry at 28.6 FPS. The results indicate that the proposed framework provides a practical explicit-surface visualization path for large plasma datasets while complementing direct volume rendering and established scientific-visualization toolkits.
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BibTeX
@article{kim2026visual,
title = {{Visual tools for 3D plasma simulation: GPU-based isosurface extraction and particle-based rendering}},
author = {Jong-Hyun Kim and Mintae Na and Junho Kim and Sejin Yun and Jung Lee and Sun-Jeong Kim},
journal = {PLOS One},
year = {2026},
month = oct,
doi = {10.1371/journal.pone.0359294},
url = {https://doi.org/10.1371/journal.pone.0359294},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Visual tools for 3D plasma simulation: GPU-based isosurface extraction and particle-based rendering
AU - Jong-Hyun Kim
AU - Mintae Na
AU - Junho Kim
AU - Sejin Yun
AU - Jung Lee
AU - Sun-Jeong Kim
PY - 2026
DA - 2026/10/16
JO - PLOS One
DO - 10.1371/journal.pone.0359294
UR - https://doi.org/10.1371/journal.pone.0359294
AB - This paper presents a GPU-accelerated visualization framework for interactive exploration of fusion-plasma simulation data represented as scalar fields and particle trajectories. The primary technical contribution is a capacity-safe isosurface-extraction pipeline that combines inclusive slab partitioning with a two-pass counting and exact allocation strategy. This design prevents slab-boundary omissions and output-buffer overflow while supporting large scalar grids. The generated positions and normals are written directly to CUDA–OpenGL interoperable buffers, enabling the standalone renderer to display explicit isosurfaces without an intermediate CPU-side copy. The extracted geometry and scalar-volume data are additionally integrated into Unreal Engine through a separate staging interface. This integration provides a unified environment for volume rendering, explicit-isosurface inspection, particle-trajectory visualization, clipping, and VR-based spatial exploration. These engine-side functions are used as interaction and visualization mechanisms rather than being presented as new rendering algorithms. Experiments on electromagnetic-potential fields with resolutions up to 5123 demonstrate stable isosurface extraction across different isovalues. In the most geometrically complex tested case, the method generates approximately 42.81 million vertices in 44.7 ms, uses less than 11 GB of GPU memory, and renders the resulting geometry at 28.6 FPS. The results indicate that the proposed framework provides a practical explicit-surface visualization path for large plasma datasets while complementing direct volume rendering and established scientific-visualization toolkits.
SN - 1932-6203
ER -