Journal of Radiation Research and Radiation Processing, Volume. 42, Issue 1, 010601(2024)

Complete coverage path planning of nuclear radiation field using bio-inspired neural network

Zhaojin LUO1, Chengfeng LIU1, Wenbao JIA1,2, Qing SHAN1, Chao SHI1, Jiandong ZHANG1, Daqian HEI3, Xiaojun ZHANG4, and Yongsheng LING1,2、*
Author Affiliations
  • 1Institute of Nuclear Analysis Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
  • 2Jiangsu University Collaborative Innovation Center for Radiation Medicine, Suzhou 215031, China
  • 3College of Nuclear Science and Technology, Lanzhou University, Nanjing 211106, China
  • 4Suzhou Guanrui Information Technology Co., Ltd., Suzhou 215008, China
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    Figures & Tables(21)
    Map of obstacles to a hypothetical nuclear accident site: (a) reference terrain of the Fukushima Nuclear Power Plant; (b) simulated raster map (color online)
    Normalized radiation dose field calculated by Monte Carlo simulation (color online)
    Diagram of lateral connections of neurons
    Eight bit movement diagram
    Flow chart of unit decomposition method
    Cover times map (color online)
    Real-time dose metrics variation chart: (a) real-time dose rate variation chart; (b) real-time cumulative dose variation chart
    Mobile unit path graph (color online)
    Cow-tillage partition diagram
    Arch overlay strategy diagram
    Flowchart of the algorithm for adding cumulative dose monitoring
    Cover times diagram of 4 units simulation(color online)
    Real-time dose metrics variation chart of 4 units simulation: (a) real-time dose rate variation chart; (b) real-time cumulative dose variation chart (color online)
    Path diagram of 4 units simulation (color online)
    Cover times diagram of 8 units simulation(color online)
    Real-time dose metrics variation chart of 8 units simulation: (a) real-time dose rate variation chart; (b) real-time cumulative dose variation chart (color online)
    Path diagram of 8 units simulation (color online)
    • Table 1. Material element composition

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      Table 1. Material element composition

      元素

      Chemical element

      质量比

      Mass ratio

      混凝土

      Concrete

      H0.65
      O49.83
      Na1.71
      Mg0.24
      Al4.54
      Si31.50
      S0.12
      K1.92
      Ca8.25
      Fe1.22

      空气

      Air

      N0.76
      O0.23
      Ar0.01
    • Table 2. Radioactive source gamma ray energy composition

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      Table 2. Radioactive source gamma ray energy composition

      能量 / MeV

      Energy

      归一化后的

      比例分布 / %

      Normalized proportional

      distribution

      0.049 727.259 3
      0.228 1742.588 0
      0.284 301.082 6
      0.328 760.103 8
      0.364 4814.505 7
      0.487 020.232 6
      0.636 981.296 9
      0.652 923.669 7
      0.662 002.416 0
      0.749 8110.871 6
      0.815 770.119 0
      1.024 6115.367 0
      1.596 200.487 7
    • Table 3. The evaluation index comparison of a unit full coverage simulation test

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      Table 3. The evaluation index comparison of a unit full coverage simulation test

      完成全覆盖步数

      Complete the full coverage steps

      时间 / s

      Time

      重复率 / %

      Repetition rate

      累积剂量 / mSv

      Cumulative dose

      生物启发神经网络

      Biologically inspired neural networks

      3641 8204.000.004 11

      单元分解法

      Unit decomposition method

      4992 49542.570.005 80
    • Table 4. Comparison of simulation test results

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      Table 4. Comparison of simulation test results

      完成全覆盖总步数

      Complete the full coverage steps

      时间 / s

      Time

      重复率 / %

      Repetition rate

      所有单元的总剂量

      / mSv

      Total dose for all units

      单体最大累积剂量 / mSv

      Monomer maximum cumulative dose

      1单元仿真

      1 cell simulation

      3641 8204.000.004 110.004 11

      4单元仿真

      4 cells simulation

      3705405.710.004 340.0012 77

      8单元仿真

      8 cells simulation

      3722406.290.004 240.0008 45
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    Zhaojin LUO, Chengfeng LIU, Wenbao JIA, Qing SHAN, Chao SHI, Jiandong ZHANG, Daqian HEI, Xiaojun ZHANG, Yongsheng LING. Complete coverage path planning of nuclear radiation field using bio-inspired neural network[J]. Journal of Radiation Research and Radiation Processing, 2024, 42(1): 010601

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    Paper Information

    Category: Research Articles

    Received: Oct. 20, 2023

    Accepted: Nov. 23, 2023

    Published Online: Mar. 27, 2024

    The Author Email: LING Yongsheng (凌永生)

    DOI:10.11889/j.1000-3436.2023-0093

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