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In this study, a similarity coefficient generation code system was established using the Monte Carlo Code for Advanced Reactor Design (McCARD) transport code and the MIG multi-correlated input sampling code. We considered the adjoint-based sensitivity and uncertainty (S/U) and stochastic sampling (S.S.) approaches to the generation of the ck similarity coefficient. To examine the code system, the ck similarity coefficients of 23 relevant critical experiments and the System-Integrated Modular Advanced Reactor (SMART) small modular reactor (SMR) target system were generated using ENDF/B-VII.1 covariance data with the Los Alamos National Laboratory (LANL) 30-group energy group structure. Our results show that the similarity coefficients between the 16 LEU thermal-spectrum-based critical experiments and SMART are more than 0.90, which is the recommended criterion of the U.S. Nuclear Regulatory Commission (NRC). These results are very helpful for licensees and can be used to justify the determination of critical experiment benchmarks for computational bias estimations of the SMART target system. To examine the discrepancy in the similarity coefficient, ck, due to the covariance data, similarity analyses for a 24 × 24 benchmark matrix were performed using ENDF-VIII.0, JENDL-5.0, and JEFF-3.3 covariance data. The results show that the selection of the covariance data used for ck generation significantly impacts the similarity coefficient. Moreover, it was observed that the current results for the SCALE 6.1 covariance data show a consistent trend with the results reported in earlier studies.

International Criticality Safety Benchmark Evaluation Project (ICSBEP) criticality analyses were conducted using the McCARD Monte Carlo code for 85 selected benchmark problems with 7 evaluated nuclear data libraries (ENDLs): ENDF/B-VII.1, ENDF/B-VIII.0, JENDL-4.0, JENDL-5.0, JEFF-3.3, TENDL-2021, and CENDL-3.2. Regarding the analyses, it was confirmed that the keff results are sensitive to the ENDL. It is noted that the new-version ENDLs show better performance in the fast benchmark cases, while on the other hand, there are no significant differences in keff among the different ENDLs in the thermal benchmark cases. The sensitivity of the keff results depending on the ENDL may impact nuclear core design parameters such as the shutdown margin, critical boron concentration, and power defects. This study and keff results will be a good reference in the development of new types of nuclear cores or new design codes.

The Korea Atomic Energy Research Institute (KAERI) has developed the DeCART2D 2-dimensional (2D) method of characteristics (MOC) transport code and the MASTER nodal diffusion code and has established its own two-step procedure. For design code licensing, KAERI prepared a critical experiment on the verification and validation (V&V) of the DeCART2D code. DeCART2D is able to perform the MOC calculation only for 2D nuclear fuel systems, such as the fuel assembly. Therefore, critical buckling in the vertical direction is essential for comparison between the results of experiments and DeCART2D. In this study, the B1 theory-augmented Monte Carlo (MC) method was adopted for the generation of critical buckling. To examine critical buckling using the B1 theory-augmented MC method, TCA critical experiment benchmark problems were considered. Based on the TCA benchmark results, it was confirmed that the DeCART2D code with the newly-generated critical buckling predicts the criticality very well. In addition, the critical buckling generated by the B1 theory-augmented MC method was bound to uncertainties. Therefore, utilizing basic equations (e.g., SNU S/U formulation) linking input uncertainties to output uncertainties, a new formulation to estimate the uncertainties of the newly generated critical buckling was derived. This was then used to compute the uncertainties of the critical buckling for a TCA critical experiment, under the assumption that nuclear cross-section data have uncertainties.