Implementation of tetrahedral-mesh geometry in Monte Carlo radiation transport code PHITS
- Authors
- Furuta, Takuya; Sato, Tatsuhiko; Han, Min Cheol; Yeom, Yeon Soo; Kim, Chan Hyeong; Brown, Justin L.; Bolch, Wesley E.
- Issue Date
- Jun-2017
- Publisher
- IOP PUBLISHING LTD
- Keywords
- tetrahedron; Monte Carlo simulation; particle and heavy ion transport code systems (PHITS); octree decomposition; computational speed
- Citation
- PHYSICS IN MEDICINE AND BIOLOGY, v.62, no.12, pp.4798 - 4810
- Indexed
- SCIE
SCOPUS
- Journal Title
- PHYSICS IN MEDICINE AND BIOLOGY
- Volume
- 62
- Number
- 12
- Start Page
- 4798
- End Page
- 4810
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/2757
- DOI
- 10.1088/1361-6560/aa6b45
- ISSN
- 0031-9155
- Abstract
- A new function to treat tetrahedral-mesh geometry was implemented in the particle and heavy ion transport code systems. To accelerate the computational speed in the transport process, an original algorithm was introduced to initially prepare decomposition maps for the container box of the tetrahedral-mesh geometry. The computational performance was tested by conducting radiation transport simulations of 100 MeV protons and 1 MeV photons in a water phantom represented by tetrahedral mesh. The simulation was repeated with varying number of meshes and the required computational times were then compared with those of the conventional voxel representation. Our results show that the computational costs for each boundary crossing of the region mesh are essentially equivalent for both representations. This study suggests that the tetrahedral-mesh representation offers not only a flexible description of the transport geometry but also improvement of computational efficiency for the radiation transport. Due to the adaptability of tetrahedrons in both size and shape, dosimetrically equivalent objects can be represented by tetrahedrons with a much fewer number of meshes as compared its voxelized representation. Our study additionally included dosimetric calculations using a computational human phantom. A significant acceleration of the computational speed, about 4 times, was confirmed by the adoption of a tetrahedral mesh over the traditional voxel mesh geometry.
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