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論文

A Systematic approach for the adequacy analysis of a set of experimental databases: Application in the framework of the ATRIUM activity

Baccou, J.*; Glantz, T.*; Ghione, A.*; Sargentini, L.*; Fillion, P.*; Damblin, G.*; Sueur, R.*; Iooss, B.*; Fang, J.*; Liu, J.*; et al.

Nuclear Engineering and Design, 421, p.113035_1 - 113035_16, 2024/05

In the Best-Estimate Plus Uncertainty (BEPU) framework, the use of best-estimate code requires to go through a Verification, Validation and Uncertainty Quantification process (VVUQ). The relevance of the experimental data in relation to the physical phenomena of interest in the VVUQ process is crucial. Adequacy analysis of selected experimental databases addresses this problem. The outcomes of the analysis can be used to select a subset of relevant experimental data, to encourage designing new experiments or to drop some experiments from a database because of their substantial lack of adequacy. The development of a specific transparent and reproducible approach to analyze the relevance of experimental data for VVUQ still remains open and is the topic of this contribution. In this paper, the concept of adequacy initially introduced in the OECD/NEA SAPIUM (Systematic APproach for model Input Uncertainty quantification Methodology) activity is formalized. It is defined through two key properties, called representativeness and completeness, that allows considering the multifactorial dimension of the adequacy problem. A new systematic approach is then proposed to analyze the adequacy of a set of experimental databases. It relies on the introduction of two sets of criteria to characterize representativeness and completeness and on the use of multi-criteria decision analysis method to perform the analysis. Finally, the approach is applied in the framework of the new OECD/NEA ATRIUM activity which includes a set of practical IUQ exercises in thermal-hydraulics to test the SAPIUM guideline in determining input uncertainties and forward propagating them on an application case. It allows evaluating the adequacy of eight experimental databases coming from the Super Moby-dick, Sozzi-Sutherland and Marviken experiments and identifying the most adequate ones.

論文

Status of the uncertainty quantification for severe accident sequences of different NPP-designs in the frame of the H-2020 project MUSA

Brumm, S.*; Gabrielli, F.*; Sanchez-Espinoza, V.*; Groudev, P.*; Ou, P.*; Zhang, W.*; Malkhasyan, A.*; Bocanegra, R.*; Herranz, L. E.*; Berda$"i$, M.*; et al.

Proceedings of 10th European Review Meeting on Severe Accident Research (ERMSAR 2022) (Internet), 13 Pages, 2022/05

The current HORIZON-2020 project on "Management and Uncertainties of Severe Accidents (MUSA)" aims at applying Uncertainty Quantification (UQ) in the modeling of Severe Accidents (SA), particularly in predicting the radiological source term of mitigated and unmitigated accident scenarios. Within its application part, the project is devoted to the uncertainty quantification of different severe accident codes when predicting the radiological source term of selected severe accident sequences of different nuclear power plant designs, e.g. PWR, VVER, and BWR. Key steps for this investigation are, (a) the selection of severe accident sequences for each reactor design, (b) the development of a reference input model for the specific design and SA-code, (c) the selection of a list of uncertain model parameters to be investigated, (d) the choice of an UQ-tool e.g. DAKOTA, SUSA, URANIE, etc., (e) the definition of the figures of merit for the UA-analysis, (f) the performance of the simulations with the SA-codes, and, (g) the statistical evaluation of the results using the capabilities, i.e. methods and tools offered by the UQ-tools. This paper describes the project status of the UQ of different SA codes for the selected SA sequences, and the technical challenges and lessons learnt from the preparatory and exploratory investigations performed.

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