# Uncertainties propagation in the framework of a Rod Ejection Accident modeling based on a multi-physics approach

## Abstract

The control of uncertainties in the field of reactor physics and their propagation in best-estimate modeling are a major issue in safety analysis. In this framework, the CEA develops a methodology to perform multi-physics simulations including uncertainties analysis. The present paper aims to present and apply this methodology for the analysis of an accidental situation such as REA (Rod Ejection Accident). This accident is characterized by a strong interaction between the different areas of the reactor physics (neutronic, fuel thermal and thermal hydraulic). The modeling is performed with CRONOS2 code. The uncertainties analysis has been conducted with the URANIE platform developed by the CEA: For each identified response from the modeling (output) and considering a set of key parameters with their uncertainties (input), a surrogate model in the form of a neural network has been produced. The set of neural networks is then used to carry out a sensitivity analysis which consists on a global variance analysis with the determination of the Sobol indices for all responses. The sensitivity indices are obtained for the input parameters by an approach based on the use of polynomial chaos. The present exercise helped to develop a methodological flow scheme, to consolidate the usemore »

- Authors:

- CEA/DEN/DM2S, CEA/Saclay, 91191 Gif sur Yvette Cedex (France)

- Publication Date:

- Research Org.:
- American Nuclear Society, 555 North Kensington Avenue, La Grange Park, IL 60526 (United States)

- OSTI Identifier:
- 22107782

- Resource Type:
- Conference

- Resource Relation:
- Conference: ICAPP '12: 2012 International Congress on Advances in Nuclear Power Plants, Chicago, IL (United States), 24-28 Jun 2012; Other Information: Country of input: France; 12 refs.; Related Information: In: Proceedings of the 2012 International Congress on Advances in Nuclear Power Plants - ICAPP '12| 2799 p.

- Country of Publication:
- United States

- Language:
- English

- Subject:
- 22 GENERAL STUDIES OF NUCLEAR REACTORS; 97 MATHEMATICAL METHODS AND COMPUTING; CHAOS THEORY; COMPUTER CODES; DATA COVARIANCES; NEURAL NETWORKS; NUCLEAR POWER PLANTS; POLYNOMIALS; REACTOR ACCIDENT SIMULATION; REACTOR PHYSICS; ROD EJECTION ACCIDENTS; SAFETY ANALYSIS; SENSITIVITY ANALYSIS; STRONG INTERACTIONS; THERMAL HYDRAULICS

### Citation Formats

```
Le Pallec, J. C., Crouzet, N., Bergeaud, V., and Delavaud, C.
```*Uncertainties propagation in the framework of a Rod Ejection Accident modeling based on a multi-physics approach*. United States: N. p., 2012.
Web.

```
Le Pallec, J. C., Crouzet, N., Bergeaud, V., & Delavaud, C.
```*Uncertainties propagation in the framework of a Rod Ejection Accident modeling based on a multi-physics approach*. United States.

```
Le Pallec, J. C., Crouzet, N., Bergeaud, V., and Delavaud, C. Sun .
"Uncertainties propagation in the framework of a Rod Ejection Accident modeling based on a multi-physics approach". United States.
```

```
@article{osti_22107782,
```

title = {Uncertainties propagation in the framework of a Rod Ejection Accident modeling based on a multi-physics approach},

author = {Le Pallec, J. C. and Crouzet, N. and Bergeaud, V. and Delavaud, C.},

abstractNote = {The control of uncertainties in the field of reactor physics and their propagation in best-estimate modeling are a major issue in safety analysis. In this framework, the CEA develops a methodology to perform multi-physics simulations including uncertainties analysis. The present paper aims to present and apply this methodology for the analysis of an accidental situation such as REA (Rod Ejection Accident). This accident is characterized by a strong interaction between the different areas of the reactor physics (neutronic, fuel thermal and thermal hydraulic). The modeling is performed with CRONOS2 code. The uncertainties analysis has been conducted with the URANIE platform developed by the CEA: For each identified response from the modeling (output) and considering a set of key parameters with their uncertainties (input), a surrogate model in the form of a neural network has been produced. The set of neural networks is then used to carry out a sensitivity analysis which consists on a global variance analysis with the determination of the Sobol indices for all responses. The sensitivity indices are obtained for the input parameters by an approach based on the use of polynomial chaos. The present exercise helped to develop a methodological flow scheme, to consolidate the use of URANIE tool in the framework of parallel calculations. Finally, the use of polynomial chaos allowed computing high order sensitivity indices and thus highlighting and classifying the influence of identified uncertainties on each response of the analysis (single and interaction effects). (authors)},

doi = {},

journal = {},

number = ,

volume = ,

place = {United States},

year = {2012},

month = {7}

}