Exploring Stochastic Sampling in Nuclear Data Uncertainties Assessment for Reactor Physics Applications and Validation Studies

Abstract

Abstract:The quantification of uncertainties of various calculation results, caused by the uncertainties associated with the input nuclear data, is a common task in nuclear reactor physics applications. Modern computation resources and improved knowledge on nuclear data allow nowadays to significantly advance the capabilities for practical investigations. Stochastic sampling is the method which has received recently a high momentum for its use and exploration in the domain of reactor design and safety analysis. An application of a stochastic sampling based tool towards nuclear reactor dosimetry studies is considered in the given paper with certain exemplary test evaluations. The stochastic sampling not only allows the input nuclear data uncertainties propagation through the calculations, but also an associated correlation analysis performance with no additional computation costs and for any parameters of interest can be done. Thus, an example of assessment of the Pearson correlation coefficients for several models, used in practical validation studies, is shown here. As a next step, the analysis of the obtained information is proposed for discussion, with focus on the systems similarities assessment. The benefits of the employed method and tools with respect to practical reactor dosimetry studies are consequently outlined.

Assessment of representativity of the PETALE experiments for validation of Swiss LWRs ex-core dosimetry calculations

“…One can notice that no BWR model has been yet included in the analysis. Nevertheless, according to the results presented in [15], PWR and BWR reactor vessel dosimetry calculations are highly correlated and therefore the findings obtained in this work for the PWR cases shall be also indirectly valid for BWRs. Explicit analysis of cor- relations between the PETALE and BWR simulations with NUSS is currently planned for the near future.…”

“…So far the representativity of the PETALE experiments for the validation of BWR FNF evaluations was not analysed explicitly. Nevertheless, previous studies [15] already showed that in fact PWR and BWR RPV FNF simulations are highly correlated. Based on this information one can deduce that the PETALE experiments should be equally useful for validation studies of both types of LWR reactors.…”

“…PCC computed in correlation studies can be interpreted as the measure of similarity between the tested systems, or, similarly, as a representativity measure of a benchmark model with respect to a certain application system. Up to now, the correlation studies with NUSS have covered both Criticality Safety and Dosimetry applications, as can be found in [15], [16], [17].…”

Correlationν̅p − σ − χin the fast neutron range via integral information

“…As a final remark, the statistical significance of the calculated correlation can be assessed as in reference [32] using the Student's t-test:…”

On the impact of nuclear data uncertainties on LWR neutron dosimetry assessments

“…The second method is based on stochastic sampling of the underlying ND and for that the PSI tool NUSS [8], [9], [10] was employed to randomly sample the ACE formatted ND files for subsequent MCNP sample calculations. In this case a fine 187 energy bin structure was applied for the same reactions as in the case of the deterministic -based approach, however, the CM for ν p and χ p were added to the list of the perturbed ND.…”