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Volume 43 Issue 4
Aug.  2022
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Xiong Qingwen, Gou Junli, Du Peng, Deng Jian, Liu Yu, Chen Wei, Dang Gaojian. Development and Application of Structural Method for Uncertainty Evaluation of Constitutive Models[J]. Nuclear Power Engineering, 2022, 43(4): 147-153. doi: 10.13832/j.jnpe.2022.04.0147
Citation: Xiong Qingwen, Gou Junli, Du Peng, Deng Jian, Liu Yu, Chen Wei, Dang Gaojian. Development and Application of Structural Method for Uncertainty Evaluation of Constitutive Models[J]. Nuclear Power Engineering, 2022, 43(4): 147-153. doi: 10.13832/j.jnpe.2022.04.0147

Development and Application of Structural Method for Uncertainty Evaluation of Constitutive Models

doi: 10.13832/j.jnpe.2022.04.0147
  • Received Date: 2021-05-31
  • Rev Recd Date: 2021-07-12
  • Publish Date: 2022-08-04
  • The best estimate plus uncertainty (BEPU) analysis is recommended by IAEA for safety analysis of nuclear power plants, and has become the mainstream method for license application of nuclear power plants. Typical BEPU method relies on the best estimation program to propagate the uncertainties of input parameters to the output, while the uncertainties of the program constitutive model are often not properly considered. In this study, a structural method is proposed to evaluate the uncertainties of program constitutive model. Based on this method, constitutive models are classified according to characteristics, and different evaluation methods are adopted for different model types. The model evaluation methods used in this study include the non-parametric curve estimation method in the forward method and the Bayesian calibration method and coverage calibration method in the reverse method, as well as alternative model construction methods. The structural method is used to quantify the uncertainties of important models in LOCA, and the quantified model uncertainties are transmitted to the peak cladding temperature through sampling calculation. The results show that both the sampling calculation values and the experimental values are smaller than the conservative calculation value, and the propagation calculation results after considering the model uncertainties can well cover the experimental values, and the safety margins can be effectively increased after considering the model uncertainties.

     

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