Acta Physica Sinica, Volume. 68, Issue 23, 232901-1(2019)

Source boundary parameter of Monte Carlo inversion technology based on virtual source principle

Zi-Ning Tian*, Xiao-Ping Ouyang, Wei Chen, Xue-Mei Wang, Ning Deng, Wen-Biao Liu, and Yan-Jie Tian
Figures & Tables(16)
The inversion theory model of source boundary parameters.源边界参数反演理论模型
The detection mode 1.探测模式1
The detection mode 2.探测模式2
Calculation model of MCNP procedure for detection mode 1.探测模式1的MCNP程序计算模型
Calculation model of MCNP procedure for detection mode 2.探测模式2的MCNP程序计算模型
  • Table 1. Energy peak count of experimental spectrum and process results for detection mode 1.

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    Table 1. Energy peak count of experimental spectrum and process results for detection mode 1.

    测量对象测量时长t/105 s N241 (54—57 keV) N241 (59.54 keV) N239 (51.62, 129 keV) A/104 Bq
    241Am 239Pu
    探测模式13.16432513625339979
    239Pu体源 2.0075248200239711, 527174.5618.7
  • Table 2. Energy peak count of experimental spectrum and process results for detection mode 2.

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    Table 2. Energy peak count of experimental spectrum and process results for detection mode 2.

    测量对象测量时长 t/105s N241 (26.4 keV) N241 (54—57 keV) N241 (59.54 keV) A/× 104 Bq
    26.4 keV59.54 keV
    探测模式24.002400509531180659645368.168.91
    241Am点源 0.5654160024653314567.748.38
    241Am体源 0.8004534627457730.4230.532
  • Table 3.

    The detection efficiency and peak/valley of equivalent virtual point source.

    等效虚拟点源探测效率及峰谷比

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    Table 3.

    The detection efficiency and peak/valley of equivalent virtual point source.

    等效虚拟点源探测效率及峰谷比

    h/cm ${\varepsilon _{241}}(h)$/10–3${\varepsilon _{239}}(h)$/10–3A241/104 Bq A239/105 Bq Q${N}/{ { {N_{\rm v}} } }(h)$
    –1.2524.324.60.9210.4975.48.05
    –1.6017.919.51.240.6295.06.99
    –2.0012.915.11.730.8104.76.12
    –2.409.4511.92.361.034.45.44
    –2.807.009.453.191.304.14.92
    –3.205.247.604.261.613.84.51
    –3.603.976.165.621.983.54.18
    –3.803.475.566.452.203.44.04
    –4.003.035.047.372.433.33.90
  • Table 4.

    The mean square deviation calculation data of equivalent virtual point at different combination.

    不同组合下等效虚拟点的均方偏差计算数据

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    Table 4.

    The mean square deviation calculation data of equivalent virtual point at different combination.

    不同组合下等效虚拟点的均方偏差计算数据

    wh/cm $\varepsilon (h)$/10–3${\varepsilon ^*}(h)$/10–3${N}/{ { {N_{\rm v}} } }(h)$X2/10–3X3/10–3X1$\sigma (X)$
    0.10–1.2524.324.68.05
    0.90–3.205.247.604.517.159.304.870.177
    0.90–3.603.976.164.186.008.014.560.308
    0.90–3.803.475.564.045.557.474.440.385
    0.90–4.003.035.043.905.166.994.310.458
    0.10–1.6017.919.56.99
    0.90–3.205.247.604.516.518.794.760.217
    0.90–3.603.976.164.185.367.504.460.396
    0.90–3.803.475.564.044.916.964.330.479
    0.90–4.003.035.043.904.526.484.210.554
    0.10–2.0012.915.16.12
    0.90–3.205.247.604.516.018.354.670.277
    0.90–3.603.976.164.184.867.064.370.474
    0.90–3.803.475.564.044.416.524.240.559
    0.90–4.003.035.043.904.026.044.120.635
    0.10–2.409.4511.95.44
    0.90–3.205.247.604.515.668.034.610.327
    0.90–3.603.976.164.184.526.744.300.530
    0.90–3.803.475.564.044.066.204.180.616
    0.90–4.003.035.043.903.675.724.050.693
  • Table 5. [in Chinese]

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    Table 5. [in Chinese]

    h/cm w$\sigma (X)$w$\sigma (X)$w$\sigma (X)$w$\sigma (X)$
    –1.250.600.700.800.9
    –3.200.401.650.301.980.202.310.102.64
    –3.600.401.550.301.900.202.260.102.61
    –3.800.401.510.301.880.202.240.102.60
    –4.000.401.480.301.850.202.220.102.60
    –1.600.600.700.800.90
    –3.200.401.000.301.230.201.450.101.67
    –3.600.400.9100.301.160.201.400.101.65
    –3.800.400.8720.301.130.201.380.101.64
    –4.000.400.8390.301.100.201.370.101.63
    –2.000.600.700.800.90
    –3.200.400.4980.300.6300.200.7630.100.898
    –3.600.400.4100.300.5610.200.7160.100.875
    –3.800.400.3750.300.5330.200.6980.100.865
    –4.000.400.3470.300.5090.200.6810.100.857
    –2.400.600.700.800.90
    –3.200.400.1940.300.2440.200.3050.100.372
    –3.600.400.1690.300.1990.200.2670.100.351
    –3.800.400.1740.300.1860.200.2520.100.342
    –4.000.400.1860.300.1780.200.2400.100.335
  • Table 5.

    The mean square deviation calculation data of equivalent virtual point at different combination.

    不同组合下等效虚拟点的均方偏差计算数据

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    Table 5.

    The mean square deviation calculation data of equivalent virtual point at different combination.

    不同组合下等效虚拟点的均方偏差计算数据

    h/cm w$\sigma (X)$w$\sigma (X)$w$\sigma (X)$w$\sigma (X)$w$\sigma (X)$
    –1.250.100.200.300.400.50
    –3.200.900.1770.800.3550.700.6640.600.9880.501.32
    –3.600.900.3080.800.2230.700.5080.600.8480.501.20
    –3.800.900.3850.800.2010.700.4480.600.7920.501.15
    –4.000.900.4580.800.2100.700.3990.600.7440.501.11
    –1.600.100.200.300.400.50
    –3.200.900.2170.800.1950.700.3600.600.5680.500.784
    –3.600.900.3960.800.2100.700.2340.600.4350.500.669
    –3.800.900.4790.800.2620.700.2030.600.3840.500.622
    –4.000.900.5540.800.3180.700.1960.600.3430.500.583
    –2.000.100.200.300.400.50
    –3.200.900.2770.800.1870.700.1770.600.2560.500.371
    –3.600.900.4740.800.3280.700.2100.600.1810.500.272
    –3.800.900.5590.800.3990.700.2570.600.1780.500.238
    –4.000.900.6350.800.4650.700.3070.600.1930.500.215
    –2.400.100.200.300.400.50
    –3.200.900.3270.800.2640.700.2090.600.1730.500.167
    –3.600.900.5300.800.4350.700.3440.600.2610.500.195
    –3.800.900.6160.800.5100.700.4070.600.3090.500.225
    –4.000.900.6930.800.5770.700.4640.600.3560.500.257
  • Table 6.

    The inversion data of volume source parameters.

    体源参数的反演计算数据

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    Table 6.

    The inversion data of volume source parameters.

    体源参数的反演计算数据

    hV/cm 体源厚度/cm$\varepsilon ({h_{\rm{V}}})$/10–3${\varepsilon ^*}({h_{\rm{V}}})$/10–2${N}/{ { {N_{\rm v}} } }({h_{\rm{V} } })$$\sigma (X)$
    –2.800.804.540.6894.690.444
    –2.801.24.600.6964.740.431
    –2.801.64.700.7054.810.414
    –2.450.805.680.8185.030.231
    –2.451.25.760.8265.070.217
    –2.451.65.890.8375.160.200
    –2.452.06.050.8515.260.181
    –2.452.56.310.8745.410.159
    –2.453.06.650.9035.630.163
    –2.454.07.570.9816.240.289
    –2.454.98.781.087.120.539
    –2.000.807.621.035.580.188
    –2.001.27.751.045.640.212
    –2.001.67.931.055.750.248
    –2.002.08.171.075.880.295
    –2.002.58.551.106.110.373
    –2.003.09.031.146.410.474
    –2.004.010.41.257.350.769
    –1.500.8010.71.336.430.744
    –1.501.210.91.356.540.781
    –1.501.611.21.376.680.834
    –1.502.011.51.406.900.905
    –1.503.012.91.507.791.18
    –0.500.8022.02.3410.12.81
  • Table 7.

    The detection efficiency, peak/valley and acvitiy ratio of equivalent virtual point source.

    等效虚拟点源探测效率、峰谷比及活度比

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    Table 7.

    The detection efficiency, peak/valley and acvitiy ratio of equivalent virtual point source.

    等效虚拟点源探测效率、峰谷比及活度比

    h/cm ${\varepsilon _{26.4\;{\rm{keV}}}}(h)$/10–3${\varepsilon _{59.54\;{\rm{keV}}}}(h)$/10–2A26.4 keV/104 Bq A59.54 keV/104 Bq A59.54 keV/A26.4 keV${N}/{ { {N_{\rm v}} } }(h)$
    0.8048.20014.40.05190.3186.1017.0
    0.4013.5008.790.18500.5232.8012.0
    04.0605.560.61500.8261.309.3
    –0.202.2604.481.11001.0300.908.4
    –0.401.2703.641.97001.2600.607.7
    –0.600.7172.983.49001.5400.407.1
    –0.800.4092.456.12001.8800.306.6
  • Table 8.

    The mean square deviation calculation data of equivalent virtual point at different combination.

    不同组合下等效虚拟点的均方偏差计算数据

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    Table 8.

    The mean square deviation calculation data of equivalent virtual point at different combination.

    不同组合下等效虚拟点的均方偏差计算数据

    h/cm w$\sigma (X)$w$\sigma (X)$w$\sigma (X)$w$\sigma (X)$w$\sigma (X)$
    0.800.100.200.300.400.50
    –0.400.902.4140.801.7830.702.8070.603.8320.504.86
    –0.600.902.1150.801.5120.702.5690.603.6270.504.69
    –0.800.901.9510.801.3620.702.4330.603.5100.504.59
    0.400.100.200.300.400.50
    –0.400.900.4660.800.2910.700.5290.600.7800.501.03
    –0.600.900.1770.800.1190.700.2860.600.5670.500.857
    –0.800.900.1850.800.2450.700.1750.600.4470.500.753
    00.100.200.300.400.50
    –0.400.900.1900.800.1600.700.1680.600.2350.500.327
    –0.600.900.4310.800.3460.700.2140.600.1230.500.165
    –0.800.900.6200.800.5120.700.3500.600.1970.500.112
  • Table 8. [in Chinese]

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    Table 8. [in Chinese]

    h/cm w$\sigma (X)$w$\sigma (X)$w$\sigma (X)$w$\sigma (X)$
    0.800.600.700.800.90
    –0.400.405.880.306.910.207.930.108.96
    –0.600.405.750.306.810.207.870.108.92
    –0.800.405.670.306.750.207.830.108.90
    0.400.600.700.800.90
    –0.400.401.290.301.550.201.800.102.06
    –0.600.401.150.301.440.201.730.102.03
    –0.800.401.060.301.380.201.690.102.01
    00.600.700.800.90
    –0.400.400.4270.300.5320.200.6390.100.747
    –0.600.400.2870.300.4250.200.5670.100.711
    –0.800.400.2070.300.3610.200.5230.100.689
  • Table 9.

    The inversion data of volume source parameters.

    体源参数的反演计算数据

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    Table 9.

    The inversion data of volume source parameters.

    体源参数的反演计算数据

    hV/cm 体源 厚度/cm ${\varepsilon ^*}({h_{\rm{V}}})$/ 10–2$\varepsilon ({h_{\rm{V}}})$/ 10–3${N}/{ { {N_{\rm v}} } }({h_{\rm{V} } })$$\sigma (X)$hV/cm 体源 厚度/cm ${\varepsilon ^*}({h_{\rm{V}}})$/ 10–2$\varepsilon ({h_{\rm{V}}})$/ 10–3${N}/{ { {N_{\rm v}} } }({h_{\rm{V} } })$$\sigma (X)$
    0.751.003.5410.411.901.59000.152.202.455.009.340.2310
    0.750.603.478.0611.401.01000.151.602.312.698.540.3470
    0.750.303.447.2311.200.80600.151.002.211.728.070.5920
    0.252.002.595.499.610.35300.150.402.171.327.860.6920
    0.251.902.564.919.440.211002.502.264.409.000.0900
    0.251.802.544.429.290.089002.452.244.148.900.0470
    0.251.702.514.009.140.022002.402.233.908.830.0640
    0.251.602.493.639.030.109002.002.132.528.300.3950
    0.251.502.473.328.920.187001.502.041.607.830.6260
    0.251.302.432.818.720.313001.001.971.137.540.7470
    0.250.802.372.048.380.5080–0.251.101.650.6026.860.8910
    –0.250.501.610.4576.700.9300
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Zi-Ning Tian, Xiao-Ping Ouyang, Wei Chen, Xue-Mei Wang, Ning Deng, Wen-Biao Liu, Yan-Jie Tian. Source boundary parameter of Monte Carlo inversion technology based on virtual source principle[J]. Acta Physica Sinica, 2019, 68(23): 232901-1

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Paper Information

Received: Jul. 16, 2019

Accepted: --

Published Online: Sep. 17, 2020

The Author Email:

DOI:10.7498/aps.68.20191095

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