Impact of nuclear data validation with uncertainty quantification and diverse benchmarks on criticality safety

Presently, a criticality safety evaluation methodology for the final geological disposal of Swiss spent nuclear fuel is under development at the Paul Scherrer Institute in collaboration with the Swiss National Technical Competence Centre in the field of deep geological disposal of radioactive waste. This method in essence pursues a best estimate plus uncertainty approach and includes burnup credit. Burnup credit is applied by means of a computational scheme called BUCSS-R (Burnup Credit System for the Swiss Reactors–Repository case) which is complemented by the quantification of uncertainties from various sources. BUCSS-R consists in depletion, decay and criticality calculations with CASMO5, SERPENT2 and MCNP6, respectively, determining the keff eigenvalues of the disposal canister loaded with the Swiss spent nuclear fuel assemblies. However, the depletion calculation in the first and the criticality calculation in the third step, in particular, are subject to uncertainties in the nuclear data input. In previous studies, the effects of these nuclear data-related uncertainties on obtained keff values, stemming from each of the two steps, have been quantified independently. Both contributions to the overall uncertainty in the calculated keff values have, therefore, been considered as fully correlated leading to an overly conservative estimation of total uncertainties. This study presents a consistent approach eliminating the need to assume and take into account unrealistically strong correlations in the keff results. The nuclear data uncertainty quantification for both depletion and criticality calculation is now performed at once using one and the same set of perturbation factors for uncertainty propagation through the corresponding calculation steps of the evaluation method. The present results reveal the overestimation of nuclear data-related uncertainties by the previous approach, in particular for spent nuclear fuel with a high burn-up, and underline the importance of consistent nuclear data uncertainty quantification methods. However, only canister loadings with UO2 fuel assemblies are considered, not offering insights into potentially different trends in nuclear data-related uncertainties for mixed oxide fuel assemblies.

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CROSS-EVALUATION OF HIGHLY ENRICHED METAL URANIUM FAST CRITICALITY EXPERIMENTS

EPJ Web of Conferences ◽

10.1051/epjconf/202124717006 ◽

2021 ◽

Vol 247 ◽

pp. 17006

Author(s):

Fan Kai ◽

Li Fu ◽

Wang Jiangmeng ◽

Yin Yanpeng ◽

Song Lingli ◽

...

Keyword(s):

Calculation Result ◽

Evaluation Method ◽

Nuclear Data ◽

Experimental Results ◽

Data Validation ◽

Physical Explanation ◽

The Cross ◽

Parameter Prediction ◽

Data Adjustment ◽

Criticality Safety

Criticality experiments are the foundation of the criticality safety validation, the reactor parameter prediction and the nuclear data validation. Criticality experiments have been used in the field of nuclear data adjustment in the last decades. In applications like criticality safety validations and nuclear data adjustments, many criticality experiments are used together in one application. In practice, experts found that some experiments have bad influence in nuclear data adjustments, and they excluded them in these applications. But the reason why these experiments should be excluded is not clear. To give these exclusion a clear physical explanation, we have developed the cross-evaluation method, which could evaluate the random biases of the experimental results by analyzing the C − E (Calculation result - Experiment result) values of similar experiments. In this paper, we use the cross-evaluation method to assess the random biases of some highly enriched metal uranium fast criticality experiments. By the cross-evaluation method, experts could choose criticality experiments which should be used in the applications of criticality safety validations or nuclear data adjustments, and might find the reason why some experiments should be excluded in applications of nuclear data adjustments.

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