• High Power Laser and Particle Beams
  • Vol. 34, Issue 5, 056007 (2022)
Qiong Li1、2, Zijing Liu1、2、*, Hao Xiao1, [in Chinese]1、2, Pengcheng Zhao1、2, Chang Wang1, and Tao Yu1、2
Author Affiliations
  • 1School of Nuclear Science and Technology, University of South China, Hengyang 421001, China
  • 2Hunan Engineering and Technology Research Center for Virtual Nuclear Reactor, University of South China, Hengyang 421001, China
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    DOI: 10.11884/HPLPB202234.210560 Cite this Article
    Qiong Li, Zijing Liu, Hao Xiao, [in Chinese], Pengcheng Zhao, Chang Wang, Tao Yu. Intelligent optimization method for lead-bismuth reactor based on Kriging surrogate model[J]. High Power Laser and Particle Beams, 2022, 34(5): 056007 Copy Citation Text show less
    Main technical principle of core intelligent optimization method
    Fig. 1. Main technical principle of core intelligent optimization method
    Comparison of two sampling results
    Fig. 2. Comparison of two sampling results
    Flow diagram of SEUMRE spatial search algorithm
    Fig. 3. Flow diagram of SEUMRE spatial search algorithm
    Realization flowchart of DOPPLER
    Fig. 4. Realization flowchart of DOPPLER
    SPARLER-4 structure diagram
    Fig. 5. SPARLER-4 structure diagram
    URANUS structure diagram
    Fig. 6. URANUS structure diagram
    Comparison of Keff, burnup predicted by Kriging surrogate model and RMC calculated value
    Fig. 7. Comparison of Keff, burnup predicted by Kriging surrogate model and RMC calculated value
    Iterative graph of fuel loading optimization for SPALLER-4
    Fig. 8. Iterative graph of fuel loading optimization for SPALLER-4
    Comparison of Keff, burnup predicted by Kriging surrogate model and RMC calculated value
    Fig. 9. Comparison of Keff, burnup predicted by Kriging surrogate model and RMC calculated value
    Iterative graph of fuel loading optimization for URANUS
    Fig. 10. Iterative graph of fuel loading optimization for URANUS
    correlation functionexpression
    exponential function${R}_{k}\left({\theta }_{k},{d}_{k}\right)=\exp(-{\theta }_{k}{d}_{k})$
    Gaussian function${R}_{k}\left({\theta }_{k},{d}_{k}\right)=\exp(-{\theta }_{k}{d}_{k}^{2})$
    linear function$ {R}_{k}\left({\theta }_{k},{d}_{k}\right)=\mathrm{m}\mathrm{a}\mathrm{x}\{\mathrm{0,1}-{\theta }_{k}{d}_{k}\} $
    cubic spline function${R}_{k}\left({\theta }_{k},{d}_{k}\right)=\left\{\begin{array}{l}1-15{\zeta }_{k}+30{\zeta }_{k}^{3},\quad 0\leqslant {\zeta }_{k}\leqslant 0.2\\ 1.25{(1-15{\zeta }_{k})}^{3},\quad 0.2 < {\zeta }_{k} < 1\\ 0,\quad{\zeta }_{k}\geqslant 1,{\zeta }_{k}={\theta }_{k}{d}_{k}\end{array}\right.$
    Table 1. Commonly used related functions of Kriging surrogate model and their expressions
    design scheme thermal power/MW fuel loading/kg equivalent diameter of active region/cm height of active area/cm average volume power density of active region/(W·cm−3) fuel (mass fraction of Pu)/% coolant and reflector shielding layer
    SPALLER-44577.8995.4806.99PuN-ThN (31/48)208Pb-Bi(90) B4C(126)
    URANUS1001758097.0218019.18UO2(9.55/17.09) 208Pb-Bi(27.11 cm) B4C(15 cm)
    design scheme solid moderator (thickness/cm) gate diameter ratio fuel rod core radius/cm air gap of fuel rod (thickness/cm) cladding of fuel rod (thickness/cm) upper/lower end plug of fuel rod (height/cm) gas cavity/ spring area of fuel rod (height/cm) top/bottom insulation of fuel rod (height/cm)
    SPALLER-4BeO (3.5)1.200.60He (0.015)TH-9(0.06)TH-9(3/3)He(48/14)He(1/1)
    URANUS1.350.72He (0.010)TH-9(0.06)TH-9(30/30)He(130/30)
    Table 2. Materials used for the design parameters of SPALLER-4 and the interval value of optimization variables
    contrast group thickness of solid moderator/cm mass fraction of Pu in fuel/% fuel rod core radius/cm height of core active zone/cm grid diameter ratio third-year Keffburnup/(MW·d·kg−1)
    prediction by KSM calculation by RMC relative error/% prediction by KSM calculation by RMC relative error/%
    14.655547.20240.2911112.16591.37101.05021.0503−0.015422.947722.79600.6654
    24.822245.41010.2776115.23531.37731.03521.03520.000624.661024.44600.8794
    34.990848.93150.2608118.18601.41171.03251.0334−0.084626.864626.89400.1093
    44.589948.82280.2117103.66061.35341.01641.0174−0.098746.352846.54400.4108
    54.782846.66470.2173116.59181.35481.02441.02340.099439.158939.39600.6019
    Table 3. Accuracy verification results of Kriging surrogate model for predicting Keff and burnup
    thickness of solid moderator/cm mass fraction of Pu in fuel/% fuel rod core radius/cm height of core active zone/cm grid diameter ratio third-year Keffburnup/(MW·d·kg−1)
    prediction by KSM calculation by RMC relative error/% prediction by KSM calculation by RMC relative error/%
    4.573249.86860.2003100.08181.31311.00571.00520.055053.702153.7990−0.0018
    Table 4. Optimization results of SPALLER-4 core design scheme
    contrast group fuel rod core radius/cm height of core active zone/cm grid diameter ratio twentieth-year Keffburnup/(MW·d·kg−1)
    prediction by KSM calculation by RMC relative error/% prediction by KSM calculation by RMC relative error/%
    10.7287164.31191.32071.00101.0018−0.080944.079744.4100−0.7438
    20.7373157.44531.32081.00041.0007−0.033845.274645.27100.0080
    30.7388156.99331.32111.00051.0009−0.040945.226645.21300.0301
    40.7410153.93311.32050.99940.9999−0.058543.583043.55400.0666
    50.7374157.43871.32031.00061.00030.029745.264545.25600.0187
    Table 5. Accuracy verification results of Kriging surrogate model for predicting Keff and burnup
    URANUS core fuel rod core radius/cm height of core active zone/cm grid diameter ratio initial Kefftwentieth-year Keffburnup/(MW·d·kg−1)
    prediction by KSM calculation by RMC relative error/% prediction by KSM calculation by RMC relative error/%
    initial0.7200180.00001.35001.02891.003141.5240
    optimization0.7314155.58381.28931.03071.00071.0010−0.022946.577346.55300.0523
    Table 6. Optimization results of design parameters for URANUS core
    URANUS core refueling interval/ EFPY fuel loading/kg total mass of core (including reflector)/kg volume of the active area/m3average volume power density of the active area/(W·cm−3) total volume of core (including reflector)/m3maximum temperature of fuel cladding/K maximum temperature of fuel core/K
    initial2017580.0925175459.36335.213819.18008.5734600.6219770.3892
    optimization2015681.0697155309.94964.269723.42087.1059604.1702796.0589
    Table 6. [in Chinese]
    Qiong Li, Zijing Liu, Hao Xiao, [in Chinese], Pengcheng Zhao, Chang Wang, Tao Yu. Intelligent optimization method for lead-bismuth reactor based on Kriging surrogate model[J]. High Power Laser and Particle Beams, 2022, 34(5): 056007
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