Sensitivity Analysis of Multi-Layer Molten Pool Model of PWR Lower Head

Li Zhigang; An Ping; Pan Junjie; Liu Wei; Lu Wei

doi:10.13832/j.jnpe.2021.04.0138

Volume 42 Issue 4

Aug. 2021

Turn off MathJax

Article Contents

Article Navigation > Nuclear Power Engineering > 2021 > 42(4): 138-143

Li Zhigang, An Ping, Pan Junjie, Liu Wei, Lu Wei. Sensitivity Analysis of Multi-Layer Molten Pool Model of PWR Lower Head[J]. Nuclear Power Engineering, 2021, 42(4): 138-143. doi: 10.13832/j.jnpe.2021.04.0138

Citation:

Li Zhigang, An Ping, Pan Junjie, Liu Wei, Lu Wei. Sensitivity Analysis of Multi-Layer Molten Pool Model of PWR Lower Head[J]. Nuclear Power Engineering, 2021, 42(4): 138-143. doi: 10.13832/j.jnpe.2021.04.0138

Citation:

PDF( 8916 KB)

Sensitivity Analysis of Multi-Layer Molten Pool Model of PWR Lower Head

doi: 10.13832/j.jnpe.2021.04.0138

Science and Technology on Reactor System Design Technology Laboratory, Nuclear Power Institute of China, Chengdu, 610213, China

Received Date: 2020-05-16
Rev Recd Date: 2020-12-20

Available Online: 2021-08-06

Publish Date: 2021-08-15

Abstract

Abstract

The molten pool model of the lower head is an important model to evaluate the effectiveness of In Vessel Retention (IVR), which has been widely used in the safety evaluation of typical pressurized water reactor (PWR). The distribution and transfer process of the composition and heat of the melt in the pool of the traditional two-layer pool model and the three-layer pool model proposed in recent years are simulated, which is with the characteristics of complex relationship and strong nonlinearity. In order to provide a support for the optimization of the molten pool delamination model and the mitigation strategy of serious accidents, both global sensitivity analysis library (SALib) and IVR analysis code (CISER V2.0) developed by Nuclear Power Institute of China are used to analyze the sensitivity of four molten pool multilayer models and obtain the influence degree of the main input parameters on the key result parameters of each model. The sensitivity analysis results reflected a typical characteristics of the molten pool model. The radius of the lower head has a significant impact on the four molten pool multilayer models, while the input parameters that have significant influence on the key result parameters are basically the same in the Salay & Fichot model and the two-layer molten pool model, the initial mass of molten material has the greatest impact on the Esmaili model, and the density of the molten material has the greatest impact on the Seiler model.
- Global sensitivity analysis,
- Molten pool model of lower head,
- Two-layer molten pool model,
- Three-layer molten pool model,
- CISER V2.0

FullText(HTML)

References(17)

References

[1]	苏光辉, 田文喜, 张亚培, 等. 轻水堆核电厂严重事故现象学[M]. 北京: 国防工业出版社, 2016.
[2]	THEOFANOUS T G, LIU C, ADDITON S, et al. In-vessel coolability and retention of a core melt[R]. Washington: Department of Energy, 1996.
[3]	PARKER G W, HODGE S A. Small scale BWR core debris eutectics formation and melting experiment[J]. Nuclear Engineering and Design, 1990(121): 341-347. doi: 10.1016/0029-5493(90)90016-Q
[4]	REMPE JL, KNUDSON DL, ALLISON CM, et al. Potential for AP600 in-vessel retention through ex-vessel flooding: INEEL/EXT-97-00779[R]. USA: Idaho National Engineering and Environmental Laboratory, 1997.
[5]	BECHTA SV, GRANOVSKY V S, et al. Corium phase equilibria based on MASCA METCOR and CORPHAD results[J]. Nuclear Engineering Design, 2008(238): 2761-2771.
[6]	ESMAILI H, KHATIB-RAHBAR M. Analysis of likelihood of lower head failure and ex-vessel fuel coolant interaction energetics for AP1000[J]. Nuclear Engineering and Design, 2005(235): 1583-1605.
[7]	SEILER JM, TOURNIAIRE B, et al. Consequences of material effects on in-vessel retention[J]. Nuclear Engineer Design, 2007(237): 1752-1758.
[8]	SALAY M, FICHOT F. Modelling of Corium Stratification in the Lower Plenum of a Reactor Vessel[C]. France: OECD/NEA MASCA Seminar 2004, 2004.
[9]	ZHANG Y P, QIU S Z, SU G H. Analysis of safety margin of in-vessel retention for AP1000[J]. Nuclear engineering and Design, 2010(240): 2023-2033.
[10]	EPRI. MAAP5 Computer Code[CP]. USA: Electric Power Research Institute, 2008.
[11]	关仲华,向清安,陈彬,等. ROAAM应用于ACP1000严重事故下实施IVR策略的有效性概率分析[J]. 核动力工程,2015, 36(6): 56-60.
[12]	向清安,关仲华,邓纯锐,等. AP1000 IVR三层熔池结构评价分析[J]. 核动力工程,2013, 34(6): 84-87.
[13]	LIU L L, YU H X, DENG J, et al. Analysis of the configurations and heat transfer of corium pool in RPV lower plenum[J]. Annals of Nuclear Energy, 2019(124): 172-178.
[14]	SOBOL I M. Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates[J]. Mathematics and Computers in Simulations, 2001, 55(1-3): 271-280. doi: 10.1016/S0378-4754(00)00270-6
[15]	SALTELLI A, ANNONI P, AZZINI I, et al. Variance based sensitivity analysis of model output, design and estimator for the total sensitivity index[J]. Computer Physics Communications, 2010(181): 259-270.
[16]	LI Z G, LIU W, MING P Z, et al. The sensitivity analysis of the core low head molten pool model based on variance decomposition[C]. ICONE27, Ibaraki, Japan, 2019.
[17]	ZAVISCA M, YUAN Z, KHATIB-RAHBAR M. Analysis of selected accident scenarios for AP1000: ERI/NRC 03-301[R]. USA: Energy Research, Inc., 2003.