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• A structural method for uncertainty evaluation of constitutive models is proposed. • Several tools for model uncertainty quantification are investigated and discussed. • Uncertainties of important models during the LBLOCA are quantified. • Best estimate plus uncertainty analysis is applied to the LP-02-6 experiment. Best estimate (BE) codes are developed to carry out realistic safety analysis of the nuclear reactor, and generally hundreds of constitutive models are comprised in a BE code. Nevertheless, uncertainties of these constitutive models are often not properly handled in the best estimate plus uncertainty (BEPU) analysis. It is not sufficient to fully evaluate the uncertainties of different sorts of models with only one method. Thereby a structural method for uncertainty quantification (UQ) of constitutive models is proposed and relevant description is presented. Based on the method, constitutive models will be classified into two categories according to the characteristics, namely the independent model and the dependent model, and different methods will be adopted for different sorts of model. Several statistical methods for UQ of constitutive models such as the non-parametric curve estimation method, the Bayesian calibration method and the coverage calibration method are evaluated and the characteristics of these methods are discussed. In addition, several methods for the construction of surrogate model are utilized to reduce the computational cost, and a model selection technique is adopted to opt the optimal model among all alternative models. The large break loss of coolant accident (LBLOCA) experiment LOFT LP-02-6 is utilized to verify the proposed structural method, and the BEPU analysis of the LP-02-6 experiment is carried out. The results show that uncertainty intervals of the identified models obtained through the structural method are reasonable, uncertainties of the peak cladding temperature (PCT) as well as the accumulator injection time (AIT) are quantified, and the sensitivity analysis is carried out to evaluate the influence of different input parameters on the 1st PCT, 2nd PCT and the AIT. [ABSTRACT FROM AUTHOR]

• Development of a global sensitivity analysis technique for time-dependent outputs. • Application of the proposed technique to the nuclear reactor LBLOCA scenario. • Analysis of the influence changing of the input parameters on the PCT. The sensitivity analysis plays a key role in the reliability assessment and safety analysis of the reactor accident scenarios. Conventional techniques mainly assess the influences of input parameters on outputs at scalar points. However, the phenomena and parameters vary significantly within the accident phases and it is necessary to consider time-dependent outputs. In this study, a sensitivity analysis technique for time-dependent outputs was implemented. The time-dependent sensitivity measures are obtained by firstly performing certain code calculations, then converting the time-dependent output data into functional data using the B-spline function, followed by aligning the features of the functional curves using the registration strategy, and finally calculating the global sensitivity measure of each input over time. The proposed technique was applied to the analysis of the LOFT large break loss of coolant accident (LBLOCA), and the time-dependent sensitivity measures of 20 inputs on the cladding temperature were acquired and analyzed. Results showed that the proposed technique could well estimate the influences of the important inputs over time, and was applicable to identify the key parameters in nuclear reactor accident transients. [ABSTRACT FROM AUTHOR]

The reflood is an important phase in the large break loss of coolant accident (LBLOCA) in nuclear power plants, which is often difficult to be accurately simulated in the code due to the presence of complex thermal hydraulic phenomena, so the uncertainty of the reflood model requires to be considered in the best estimate calculation. Uncertainty evaluation of the reflood model in the ARSAC was carried out in this research. Based on the FLECHT-SEASET scenarios, surrogate models were firstly constructed using the Kriging method, and the uncertainty of the ARSAC reflood model was evaluated using the Bayesian calibration. Then the uncertainty propagation was executed using the RBHT tests to validate the accuracy of the uncertainty evaluation results. It is shown that the ARSAC reflood model can accurately simulate the phenomenon and has very good applicability after considering the uncertainty, which can be considered as a best estimate model. • Uncertainty evaluation of the ARSAC reflood model with Bayesian calibration. • Uncertainty quantification of the model with FLECHT-SEASET based on Kriging model. • Validation of the model uncertainty evaluation results with RBHT. [ABSTRACT FROM AUTHOR]

The mainstream deterministic and probabilistic methods for safety analysis of the nuclear power plant (NPP) are the best estimate plus uncertainty (BEPU) analysis and probabilistic safety analysis (PSA), respectively. With the development of techniques, a more "realistic" simulation of the NPP has become a long-term goal to improve the economic efficiency. Nowadays, the combination of BEPU and PSA, also known as the risk-informed uncertainty method, is under development. In this paper, the cold leg double-ended break accident of a typical pressurized water reactor was selected to be the target scenario for a preliminary study of the combined method. A failure analysis of the emergency core cooling system based on PSA was carried out first, and the failure probability of each event sequence was determined. Then the conditional core damage probability of each event sequence was evaluated through BEPU analysis, and the core damage frequency of the reactor was finally determined. [ABSTRACT FROM AUTHOR]

• Improvement of uncertainty evaluation of the closure models in uncertainty methods. • Improvement of sensitivity analysis method and framework of the uncertainty methods. • Development of an optimized uncertainty method. • Application of the improved uncertainty method to the CPR1000 LBLOCA. Best estimate plus uncertainty methodology is an advanced technology for licensing application of the nuclear power plants, but some aspects can still be improved in the conventional input-driven methodologies. For instance, uncertainties of the closure models are not properly handled; local sensitivity analysis methods not suitable for complex nuclear systems are still widely utilized; the sensitivity analysis process needs to be performed again every time new parameters are identified. Optimization researches were carried out in the study. A structural method was proposed to quantify the uncertainties of the closure models, and a low-cost moment-independent global sensitivity analysis method was developed to improve the sensitivity analysis framework. By integrating the improvements into the conventional input-driven framework, an uncertainty method with model treatment and improved sensitivity analysis was obtained. Finally, the method was validated through a large break loss of coolant accident in a three-loop pressurized water reactor. [ABSTRACT FROM AUTHOR]

The best estimate plus uncertainty (BEPU) methodology is developed to carry out realistic safety analysis of the nuclear power plant. However, the sensitivity analysis in the conventional methodologies often leads to inaccurate results when lacking of the phenomenon identification and ranking table (PIRT) or adopting the local sensitivity analysis methods. As the initial inputs determined in short of the PIRT may neglect some important parameters or identify some unimportant parameters, and the local methods are not appropriate for complex and non-linear systems. In this study, an optimized moment-independent global sensitivity analysis method with very low computational cost was utilized to improve the sensitivity analysis framework of the BEPU methodology. The reliability as well as the applicability of the method were assessed through some tests and a large break loss of coolant accident (LBLOCA) of the LOFT facility. The improved sensitivity analysis framework was then applied to the BEPU analysis of a typical three-loop pressurized water reactor CPR1000, and the reliability of the optimized moment-independent method was further confirmed by comparing the sensitivity analysis result of the method to the results of the BEMUSE project and the Spearman method. Besides, two new parameters were identified to have great influence on the PCT, and the two parameters should be taken into consideration in the uncertainty analysis of the BEPU methodology. Image 1 • Development of a low-cost global sensitivity analysis method. • Improvement of sensitivity analysis in best estimate plus uncertainty. • Application to the sensitivity analysis of the CPR1000 LBLOCA. [ABSTRACT FROM AUTHOR]

• An optimized moment-independent method with low computational cost is proposed. • The optimized method is assessed through several tests. • The optimized method is applied to the global sensitivity analysis of the LOFT LBLOCA. • Results of the optimized method, original moment-independent method and local method are compared. Best estimate plus uncertainty (BEPU) analysis has been widely adopted for safety evaluation of the nuclear reactor, and the sensitivity analysis is an important part of the BEPU methodology. Local sensitivity analysis methods are still widely utilized in the methodology, which is not suitable for complex non-linear nuclear systems. The global sensitivity analysis is essential but the biggest problem is that the computational cost can hardly be accepted. In this study, the moment-independent global method was adopted and optimized, and a low-cost method was obtained and assessed. The sensitivity analysis of a large break loss of coolant accident (LBLOCA) of the LOFT facility was carried out by using the method. Results show that the optimized method can well evaluate the sensitivity indices with very low cost and relatively high accuracy, and the result obtained through the optimized method is much more reliable than that of the local sensitivity analysis method. [ABSTRACT FROM AUTHOR]