Uncertainty research of fuel rod design verification based on Dakota

Xu Duoting; Jin Xin; Wei Xiaoyan; Liu Xiaohan; Zhu Yanan

doi:10.11884/HPLPB202234.210298

Volume 34 Issue 2

Jan. 2022

Turn off MathJax

Article Contents

Article Navigation > High Power Laser and Particle Beams > 2022 > 34(2): 026012

Xu Duoting, Jin Xin, Wei Xiaoyan, et al. Uncertainty research of fuel rod design verification based on Dakota[J]. High Power Laser and Particle Beams, 2022, 34: 026012. doi: 10.11884/HPLPB202234.210298

Citation:

Xu Duoting, Jin Xin, Wei Xiaoyan, et al. Uncertainty research of fuel rod design verification based on Dakota[J]. High Power Laser and Particle Beams, 2022, 34: 026012. doi: 10.11884/HPLPB202234.210298

Citation:

PDF( 2769 KB)

Uncertainty research of fuel rod design verification based on Dakota

doi: 10.11884/HPLPB202234.210298

China Nuclear Power Technology Research Institute Co., Ltd., Shenzhen 518026, China

Received Date: 2021-07-19
Rev Recd Date: 2021-09-09

Available Online: 2021-10-08

Publish Date: 2022-01-11

Abstract

Abstract

Fuel rod design verification is the evaluation process of fuel rod safety performance during operation in reactor, in which the uncertainty of input parameters has important effect on evaluation results. To study the uncertainty systematically, fuel rod performance analysis software has been coupled with Dakota software to carry out fuel rod design verification, the results of nonparametric Monte Carlo and Latin Hypercube Sampling have been compared with those of traditional method. It turns out that the fuel rod inner pressure criterion is vulnerable to be under challenge for the reason of input uncertainty under consideration by traditional method. The defects can be made up by statistical nonparametric sampling, by which a larger safety margin is obtained, and a theoretical basis for fuel rod safety and economic performance enhancement is provided. Meanwhile, the temperature calculation result obtained by two sampling methods can be more referential compared with traditional method. For the cladding corrosion and strain criterion, the results of sampling methods and traditional method show no significant difference, for the reason that the uncertain input parameters are selected suitably. In conclusion, the statistical method based on nonparametric sampling can be more practically significant for safety performance evaluation of fuel rod in operation.
- fuel rod,
- uncertainty,
- nonparametric sampling,
- Monte Carlo sampling,
- Latin Hypercube Sampling,
- Dakota software

FullText(HTML)

References(16)

References

[1]	王璐, 张林, 徐腾, 等. 燃料棒设计关键参数敏感性分析[J]. 应用科技, 2019, 46(6):69-72. (Wang Lu, Zhang Lin, Xu Teng, et al. Sensitivity analysis of key parameters in fuel rod design[J]. Applied Science and Technology, 2019, 46(6): 69-72
[2]	周勤. 压水堆燃料棒设计参数不确定性研究[J]. 原子能科学技术, 2003, 37(s1):5-9. (Zhou Qin. Research on uncertainty of design parameters for PWR fuel rod[J]. Atomic Energy Science and Technology, 2003, 37(s1): 5-9
[3]	International Atomic Energy Agency. Best estimate safety analysis for nuclear power plants: uncertainty evaluation[R]. Vienna: International Atomic Energy Agency, 2008.
[4]	Briggs L L. Uncertainty quantification approaches for advanced reactor analyses[R]. Chicago: Argonne National Laboratory, 2008.
[5]	Prošek A, Mavko B. The state-of-the-art theory and applications of best-estimate plus uncertainty methods[J]. Nuclear Technology, 2007, 158(1): 69-79. doi: 10.13182/NT07-1
[6]	陈炼, 房芳芳, 邓程程, 等. 核电站最佳估算安全分析中的不确定度评估方法分析[J]. 原子能科学技术, 2015, 49(7):1237-1242. (Chen Lian, Fang Fangfang, Deng Chengcheng, et al. Analysis on uncertainty evaluation method in best estimate safety analysis of nuclear power plant[J]. Atomic Energy Science and Technology, 2015, 49(7): 1237-1242 doi: 10.7538/yzk.2015.49.07.1237
[7]	Wensauer A, Distler I, Heins L. Probabilistic uncertainty analysis applied to fuel rod design[M]//Spitzer C, Schmocker U, Dang V N. Probabilistic Safety Assessment and Management. London: Springer, 2004: 2791-2796.
[8]	Boulore A. Importance of uncertainty quantification in unclear fuel behavior modeling and simulation[C]//Best Estimate Plus Uncertainty International Conference. Lucca, 2018.
[9]	Bratton R N, Jessee M A, Wieselquist W A, et al. Rod internal pressure distribution and uncertainty analysis using FRAPCON[J]. Nuclear Technology, 2017, 197(1): 47-63. doi: 10.13182/NT16-75
[10]	Hernandez-Solis A, Ekberg C, Jensen A O, et al. Statistical uncertainty analyses of void fraction predictions using two different sampling strategies: Latin hypercube and simple random sampling[C]//Proceedings of the 18th International Conference on Nuclear Engineering. Xi’an, China: ASNE, 2010: 1059-1068.
[11]	Ikonen T, Tulkki V. The importance of input interactions in the uncertainty and sensitivity analysis of nuclear fuel behavior[J]. Nuclear Engineering and Design, 2014, 275: 229-241. doi: 10.1016/j.nucengdes.2014.05.015
[12]	王国栋, 王喆, 扈本学, 等. 应用DAKOTA程序耦合WGOTHIC程序进行安全壳压力响应敏感性分析[J]. 原子能科学技术, 2015, 49(12):2176-2180. (Wang Guodong, Wang Zhe, Hu Benxue, et al. Sensitivity analysis on containment pressure response using coupled DAKOTA and WGOTHIC codes[J]. Atomic Energy Science and Technology, 2015, 49(12): 2176-2180 doi: 10.7538/yzk.2015.49.12.2176
[13]	Wang J R, Tsai C W, Lin H T, et al. Performing uncertainty analysis of IIST facility SBLOCA by TRACE and DAKOTA[R]. Washington DC: Nuclear Regulatory Commission, 2013.
[14]	高新力, 靖剑平, 温爽, 等. DAKOTA-RELAP不确定性分析方法在大破口事故中的应用[J]. 核安全, 2016, 15(1):66-70. (Gao Xinli, Jing Jianping, Wen Shuang, et al. Application of DAKOTA-RELAP method in the uncertainty analysis of LB-LOCA[J]. Nuclear Safety, 2016, 15(1): 66-70
[15]	兰兵, 潘昕怿, 石兴伟, 等. DAKOTA法量化AP1000堆芯物理不确定性[J]. 核电子学与探测技术, 2019, 39(6):668-672. (Lan Bing, Pan Xinyi, Shi Xingwei, et al. Application of DAKOTA method in AP1000 core physics uncertainty quantization[J]. Nuclear Electronics & Detection Technology, 2019, 39(6): 668-672
[16]	孙山泽. 非参数统计讲义[M]. 北京: 北京大学出版社, 2020: 147-150 Sun Shanze. Nonparametric statistics handout[M]. Beijing: Peking University Press, 2020: 147-150)