Variance reduction method based on adjoint discrete ordinate

Zheng Zheng; Ding Qianxue; Zhou Yan

doi:10.11884/HPLPB201830.170223

Volume 30 Issue 2

Feb. 2018

Turn off MathJax

Article Contents

Abstract

References

Article Navigation > High Power Laser and Particle Beams > 2018 > 30(2): 026004

Zhang Haoran, Zeng Qin, Chen Chong, et al. Testing and analysis of coupled program of MCNP and FISPACT[J]. High Power Laser and Particle Beams, 2017, 29: 036025. doi: 10.11884/HPLPB201729.160424

Citation:

Zheng Zheng, Ding Qianxue, Zhou Yan. Variance reduction method based on adjoint discrete ordinate[J]. High Power Laser and Particle Beams, 2018, 30: 026004. doi: 10.11884/HPLPB201830.170223

Zhang Haoran, Zeng Qin, Chen Chong, et al. Testing and analysis of coupled program of MCNP and FISPACT[J]. High Power Laser and Particle Beams, 2017, 29: 036025. doi: 10.11884/HPLPB201729.160424

Citation:

Zheng Zheng, Ding Qianxue, Zhou Yan. Variance reduction method based on adjoint discrete ordinate[J]. High Power Laser and Particle Beams, 2018, 30: 026004. doi: 10.11884/HPLPB201830.170223

PDF( 16274 KB)

Variance reduction method based on adjoint discrete ordinate

doi: 10.11884/HPLPB201830.170223

Shanghai Nuclear Engineering Research and Design Institute Ltd Co, Shanghai 200233, China

Received Date: 2017-06-20
Rev Recd Date: 2017-08-20
Publish Date: 2018-02-15

Abstract

Abstract

For deep-penetration shielding calculation, Monte Carlo method (MC method) requires modeling a great number of particles to obtain reliable results, thus huge computation time is the main problem of the MC method. Source biasing and weight window technique effectively decrease the tally error of deep penetration problem. This paper studies the variance reduction (VR) method based on adjoint Discrete Ordinate (SN), generates source biasing factors and weight window parameters for the MC method by using the adjoint fluence rates of the SN method, and develops source sampling subroutine for JMCT. The VR method was verified at phaseⅠ of Qinshan Nuclear Power Plant measurements. It was applied to CAP1400 pressure vessel fast neutron fluence rate and cavity neutron and photon dose rate calculations. Numerical results show that the VR method based on SN increases calculation efficiency by 1~2 orders for deep-penetration shielding calculation with high precision compared with unbiased MC method.
- deep-penetration,
- discrete ordinate method,
- Monte Carlo method,
- source biasing,
- weight window

FullText(HTML)

References(9)

References

[1]	Wagner J C. Acceleration of Monte Carlo shielding calculations with an automated variance reduction technique and parallel processing[R]. University Park, 1997.
[2]	Wagner J C, Haghighat A. Automated variance reduction of Monte Carlo shielding calculations using the discrete ordinates adjoint function[J]. Nuclear Science and Engineering, 1998, 128: 186-208. doi: 10.13182/NSE98-2
[3]	Haghighat A, Wagner J C. Monte Carlo variance reduction with deterministic importance functions[J]. Progress in Nuclear Energy, 2003, 42(1): 25-53. doi: 10.1016/S0149-1970(02)00002-1
[4]	Blakeman E D, Peplow D E, Wagner J C, et al. PWR facility dose modeling using MCNP5 and the CADIS/ADVANTG variance-reduction methodology[R]. ORNL/TM-2007/133, 2007.
[5]	Peplow D E, Evans T M, Wagner J C. Simultaneous optimization of tallies in difficult shielding problems[J]. Nuclear Technology, 2008, 168: 785-792.
[6]	Wagner J C, Peplow P E, Evans T M. Automated variance reduction applied to nuclear well-logging problems[J]. Nuclear Technology, 2009, 168: 799-809. doi: 10.13182/NT09-A9309
[7]	Vasiliev A, Ferroukhi H, Zimmermann M A, et al. Development of a CASMO-4/SIMULATE-3/MCNPX calculation scheme for PWR fast neutron fluence analysis and validation against RPV scraping test data[J]. Annals of Nuclear Energy, 2007, 34: 615-627. doi: 10.1016/j.anucene.2007.02.020
[8]	Fero A H. SORCERY user manual[R]. LTR- R EA-06-74, 2006.
[9]	X-5 Monte Carlo Team, MCNP - Ageneral Monte Carlo N-Particle transport code[R]. LA-UR-03-1987, 2003.

Relative Articles

[1]	Xie Rong, Hao Jianhong, Zhao Qiang, Zhang Fang, Fan Jieqing, Xue Bixi, Dong Zhiwei, Cao Xiangchun. Research on Monte Carlo calculation method for photon absorbed dose[J]. High Power Laser and Particle Beams, 2024, 36(10): 106003. doi: 10.11884/HPLPB202436.240037
[2]	Li Kewei, Ling Yongsheng, Zhang Haojia, Shan Qing, Hei Daqian, Jia Wenbao. In-situ detection method of harmful elements in landfill[J]. High Power Laser and Particle Beams, 2018, 30(2): 026002. doi: 10.11884/HPLPB201830.170226
[3]	Li Jie, Li Yunzhao, Wu Hongchun, Zheng Qi. Weighted Monte Carlo solution of neutron kinetics equations[J]. High Power Laser and Particle Beams, 2018, 30(1): 016009. doi: 10.11884/HPLPB201830.170242
[4]	Shen Jingwen, Hu Ye, Zheng Yu, Ma Xubo. Three-dimensional Monte Carlo transport code JMCT in shielding engineering application[J]. High Power Laser and Particle Beams, 2018, 30(4): 046002. doi: 10.11884/HPLPB201830.170222
[5]	Shao Wencheng, Tang Xiaobin, Geng Changran, Shu Diyun, Gong Chunhui, Ai Yao, Zhang Xudong, Yu Haiyan. Novel magnetic-modulated proton therapy method and corresponding modulation mechanism[J]. High Power Laser and Particle Beams, 2017, 29(12): 126015. doi: 10.11884/HPLPB201729.170220
[6]	Han Feng, Liu Yu, Wang Bin. Method for evaluating radiation harden performance of electronic system based on system status[J]. High Power Laser and Particle Beams, 2016, 28(08): 084001. doi: 10.11884/HPLPB201628.150695
[7]	Cheng Zhenbo, Liu Xiaolong, Yan Junkai. Evaluation of uncertainty in peak detector calibration based on Monte-Carlo method[J]. High Power Laser and Particle Beams, 2016, 28(11): 113007. doi: 10.11884/HPLPB201628.151066
[8]	Mu Weibing, Zheng Peng, Shi Zhengjun, Liu Jianbo. Rapid interpolation calculation method based on physical rules with MCNP simulation results[J]. High Power Laser and Particle Beams, 2015, 27(08): 086002. doi: 10.11884/HPLPB201527.086002
[9]	Zhu Jinhui, Xie Honggang, Niu Shengli, Zuo Yinghong. A fast calculation method for Compton current induced by gamma-ray in uniform atmosphere[J]. High Power Laser and Particle Beams, 2015, 27(07): 076005. doi: 10.11884/HPLPB201527.076005
[10]	Zhang Jie, Zhang Ying, Chen Xiulian, Pang Beibei, Bai Lixin. Geometric factor calculation program based on Monte Carlo method[J]. High Power Laser and Particle Beams, 2015, 27(01): 014002. doi: 10.11884/HPLPB201527.014002
[11]	Chen Li, Ma Hao, Zeng Zhi, Li Junli, Cheng Jianping. Monte Carlo-based sourceless efficiency calibration method of HPGe γ spectrometer[J]. High Power Laser and Particle Beams, 2013, 25(01): 201-206. doi: 10.3788/HPLPB20132501.0201
[12]	Zuo Yinghong, Wang Jianguo, . Application of Monte Carlo method to solving boundary value problem of differential equations[J]. High Power Laser and Particle Beams, 2012, 24(12): 3023-3027. doi: 10.3788/HPLPB20122412.3023
[13]	Su Jian, Zeng Zhi, Liu Yue, Yue Qian, Ma Hao, Cheng Jianping. Monte Carlo simulation of muon radiation environment in China Jinping Underground Laboratory[J]. High Power Laser and Particle Beams, 2012, 24(12): 3015-3018. doi: 10.3788/HPLPB20122412.3015
[14]	Zhang Xuan, Huang Jiaofeng, Liu Jun, Guan Yonghong, Liu Jin. Application of Monte Carlo method to boundary location of flash radiographs[J]. High Power Laser and Particle Beams, 2012, 24(12): 2983-2986. doi: 10.3788/HPLPB20122412.2983
[15]	Xie Qin, Geng Changran, Chen Feida, Tang Xiaobin, Yao Ze'en. Calculation of cellular S values for α particle based on Monte Carlo simulation[J]. High Power Laser and Particle Beams, 2012, 24(12): 2970-2974. doi: 10.3788/HPLPB20122412.2970
[16]	Chen Feida, Tang Xiaobin, Wang Peng, Chen Da. Neutron shielding material design based on Monte Carlo simulation[J]. High Power Laser and Particle Beams, 2012, 24(12): 3006-3010. doi: 10.3788/HPLPB20122412.3006
[17]	Wang Ruihong, Ji Zhicheng, Pei Lucheng. Adaptive sampling method in deep-penetration particle transport problem[J]. High Power Laser and Particle Beams, 2012, 24(12): 2941-2945. doi: 10.3788/HPLPB20122412.2941
[18]	fan ruyu, han feng, guo hongxia. Assessment method of gamma-dose radiation hardness of power supply system[J]. High Power Laser and Particle Beams, 2011, 23(02): 0- .
[19]	zhang huabin, zhao xiang, zhou haijing, huang kama. Probabilistic and statistical analysis of mode stirred reverberation chamber and its Monte Carlo simulation[J]. High Power Laser and Particle Beams, 2011, 23(09): 0- .
[20]	chen nan, li cheng-gang, dai wen-hua, li hong, zhou zhi. Application of Monte Carlo method to spot size measurement of X-ray sources[J]. High Power Laser and Particle Beams, 2008, 20(06): 0- .

Supplements(0)

Cited By

Cited by

Periodical cited type(2)

1.	刘利，左应红，牛胜利，朱金辉，李夏至. 中子在大气中产生氮俘获γ的蒙特卡罗模拟研究. 强激光与粒子束. 2022(08): 162-168 . 本站查看
2.	王梦琪，郑征，梅其良，黎辉，程汤培. 全局减方差方法在乏燃料干式贮存容器屏蔽计算中的应用. 原子能科学技术. 2019(05): 884-892 .