Nuclear Engineering and Technology

  • 제55권6호
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  • Pages.1966-1973
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  • 2023
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  • 1738-5733(pISSN)
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  • 2234-358X(eISSN)
한국원자력학회 (Korean Nuclear Society)
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A GPU-based point kernel gamma dose rate computing code for virtual simulation in radiation-controlled area

  • Zhihui Xu (Fundamental Science on Nuclear Safety and Simulation Technology Laboratory, Harbin Engineering University) ;
  • Mengkun Li (Shenzhen Polytechnic) ;
  • Bowen Zou (Hangzhou Institute of Technology, Xidian University) ;
  • Ming Yang (Fundamental Science on Nuclear Safety and Simulation Technology Laboratory, Harbin Engineering University)
  • 투고 : 2022.05.23
  • 심사 : 2023.03.15
  • 발행 : 2023.06.25
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초록

Virtual reality technology has been widely used in the field of nuclear and radiation safety, dose rate computing in virtual environment is essential for optimizing radiation protection and planning the work in radioactive-controlled area. Because the CPU-based gamma dose rate computing takes up a large amount of time and computing power for voxelization of volumetric radioactive source, it is inefficient and limited in its applied scope. This study is to develop an efficient gamma dose rate computing code and apply into fast virtual simulation. To improve the computing efficiency of the point kernel algorithm in the reference (Li et al., 2020), we design a GPU-based computing framework for taking full advantage of computing power of virtual engine, propose a novel voxelization algorithm of volumetric radioactive source. According to the framework, we develop the GPPK(GPU-based point kernel gamma dose rate computing) code using GPU programming, to realize the fast dose rate computing in virtual world. The test results show that the GPPK code is play and plug for different scenarios of virtual simulation, has a better performance than CPU-based gamma dose rate computing code, especially on the voxelization of three-dimensional (3D) model. The accuracy of dose rates from the proposed method is in the acceptable range.

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과제정보

This Work or This Article is Supported by the Funding from Guangdong Soft Science Research Programme (Grant No. 2022A0505050007). The anonymous reviewers have contributed considerably to the publication of this paper.

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