Nuclear data adjustment exercise combining information from shielding, critical and kinetics benchmark experiments ASPIS-Iron 88, Popsy and SNEAK-7A/7B

Nuclear cross-sections are being re-evaluated repeatedly since decades, with the objective of improving the agreement with the measurements consistently to the nuclear model predictions and to extend their application domains. In recent years, the evaluations have been in many cases “tuned” to match in particular the critical benchmarks. However, the effective multiplication factor (keff) is a very global parameter and as such provides simply too many possible combinations and variations, all more or less in agreement with the differential cross section data measurements and the associated uncertainties. Adding more extensively other types of integral measurements, such as shielding and kinetics benchmarks, on the cross-section validation menu is expected to provide a complementary and a more complete view on the challenges linked with the radiation propagation calculations. This paper discusses the advantages of exploiting shielding benchmark experiments and effective delayed neutron fraction (βeff) measurements for nuclear data (ND) testing and, eventually, for guiding the evaluations. The cross-section sensitivity and uncertainty analysis revealed some crucial differences in the keff and βeff sensitivity profiles, as well as advantages of shielding benchmarks which makes them favorable for ND validation. The potential benefits of using these types of measurements to reduce the compensation effects was demonstrated through the ND adjustment exercise involving the Popsy and SNEAK-7A & -7B critical and kinetics, and the ASPIS Iron 88 shielding benchmarks. The differences among the available nuclear covariance data and their impact on the adjustment results were investigated to understand the dangers of (mis)interpreting the results of the adjustment and to conclude on the robustness and reliability of the mathematical adjustment procedure using the state-of-the-art nuclear covariance data.