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In this paper, we validate the decay heat calculation capability via a two-step method to analyze spent nuclear fuel (SNF) discharged from pressurized water reactors (PWRs). The calculation method is implemented with a lattice code STREAM and a nodal diffusion code RAST-K. One of the features of this method is the direct consideration of three-dimensional (3D) core simulation conditions with the advantage of a short simulation time. Other features include the prediction of the isotope inventory by Lagrange non-linear interpolation and the use of power history correction factors. The validation is performed with 58 decay heat measurements of 48 fuel assemblies (FAs) discharged from five PWRs operated in Sweden and the United States. These realistic benchmarks cover the discharge burnup range up to 51 GWd/MTU, 23.2 years of cooling time, and spanning an initial uranium enrichment range of 2.100–4.005 wt percent. The SNF analysis capability of STREAM is also employed in the code-to-code comparison. Compared to the measurements, the validation results of the FA calculation with RAST-K are within ± 4%, and the pin-wise results are within ± 4.3%. This paper successfully demonstrates that the developed decay heat calculation method can perform SNF back-end cycle analyses.

The authors developed the modified power method (MPM) in previous publications to obtain multiple eigenmodes of an eigenvalue problem at the same time by employing a generalized eigenvalue problem (GEP) of the form of WX = VXK. Special attention has been paid to the Monte Carlo (MC) implementation of the MPM because it always suffers from the inherent statistical noises. In this paper, a preconditioning method for the GEP has been developed for the MC MPM, so that the performance is more stable and robust to the MC statistical noises. This preconditioning method is crucial for MC solving of problems with degenerated eigenmodes, which requires the accumulation of a so-called transfer matrix and the division of the system space into multiple sub-regions, the number of sub-regions being greater than the number of eigenmodes to be solved. The preconditioning method solves the issues arising from the mismatch between the number of sub-regions and the target number of eigenmodes to be calculated. The numerical results for a model cube problem and BEAVRS whole core neutron transport eigenvalue problem successfully demonstrate the validity of the preconditioning method and the extended applicability of the MC MPM for practical problems.

The status of nuclear power plants’ conditions must be checked to avoid initial events which may eventually lead to accidents. Axial power and axial offset (AO) are key parameters which are usually used to state 3-dimensional core power peaking, in the form of a practical parameter. Group method of data handling (GMDH) has a wide range of applications. Here, a GMDH is used and modified as an efficient method to predict the axial power and AO of the reactor core as well as fuel assemblies. In this paper, axial power offset of the whole reactor core is reconstructed by using in-core detectors. By using the developed GMDH algorithm, the optimum relationship between the independent in-core detector signals and the dependent variables, the core axial power and AO, is determined. Two separate sets of big data are prepared and analyzed. The first set includes power at each of 24 axial nodes at different core states. The second set is similar to the first set except as it also contains fuel assembly data.

This study presents the first application of the advanced Rossi-alpha method (theoretically introduced by Kong et al., 2014) on the reactivity measurements in a research reactor: detector count signals at the Kyoto University Critical Assembly (KUCA) facility. The detector signals in the KUCA A-type core are analyzed by three subcriticality measurement methods: (1) Feynman-alpha (F-α) method, (2) Rossi-alpha (R-α) method, and (3) advanced Rossi-alpha (advanced R-α) method. Four cases are analyzed for two different subcritical states of the core and two different neutron source locations. Two different negative reactivity ρ values are obtained by the measurements of control rod worth and regarded as the reference reactivity values, comparing the results by the four methods. The F-α shows reactivity errors ranging between 7.1 and 7.3% due to its use of variance-to-mean ratios of detector count signals, which are not very sensitive to neutron background noise. However, the fitting uncertainties associated to the F-α results are large, ranging between 5.4 and 12.8% at one standard deviation. The R-α shows small fitting uncertainties ranging between 2.8 and 3.8%, although reactivity errors are in the range of 3.5–26.5% due to the neutron background noise. Finally, the advanced R-α that explicitly models the neutron background noise contrary to the previous methods shows the reactivity errors in the range of 1.0–11.8%, and provides the lowest uncertainties of the measured ρ in the range of 0.4–0.9%. In conclusion, among the four methods applied to the reactivity measurements at KUCA, the advanced R-α reveals the best accuracy with the lowest uncertainties.

This paper presents a methodology developed and implemented in the neutron transport code STREAM to perform high-fidelity, multicycle, multiphysics simulations of light water reactor whole-core problems. STREAM uses state-of-the-art methodologies to achieve high accuracy and computational performance. Further, it can compute fine-mesh neutron transport solutions for three-dimensional (3D) whole-core problems using the 3D method of characteristics/diamond-difference (MOC/DD). For multigroup calculation, STREAM generates problem-dependent multigroup cross-sections using intrinsic cross-section libraries and a resonance self-shielding method. To perform the multicycle analysis of commercial power reactors, many advanced methods and features have been developed and implemented. In this paper, the methodologies and features of STREAM are presented, followed by the whole-core simulation capability.

The International Atomic Energy Agency and the China Institute of Atomic Energy proposed a coordinated research project (CRP) to establish a benchmark, based on the China Experimental Fast Reactor (CEFR) start-up tests which include fuel loading and criticality, measurements of control rod worth and reactivity coefficients, and foil activation measurements. As a participant in the CRP, the computational reactor physics and experiment laboratory of the Ulsan National Institute of Science and Technology has been studying and analyzing the neutronic performance of the CEFR. The verification and validation are performed for the simulations in the CEFR analysis. A verification process of the methodology was conducted to compare the predicted results with those obtained by a well-known MCNP6.1 Monte Carlo code. The results obtained by the MCS code were compared against the experimental data. The difference in various wire models at the critical state are evaluated in this study.

This paper presents a new high performance burnable absorber (BA) design for advanced Pressurized Water Reactors (PWRs) aiming for a long-cycle operation with a low soluble boron concentration. The new BA consists of a UO 2 – 157 Gd 2 O 3 rod covered with a thin layer of Zr 167 Er 2 . A key feature of this new BA is that enriched isotopes, 157 Gd and 167 Er, are used as absorber materials. Since the high absorption cross section of 157 Gd can reduce the mass fraction of Gd 2 O 3 in UO 2 –Gd 2 O 3 , the thermal margin of fuel rods will increase with higher heat conductivity. Also, the 157 Gd transmutes into 158 Gd by neutron absorption and therefore the residual penalty at the end of cycle (EOC) will decrease. Since 167 Er has a resonance near the thermal neutron energy region, the moderator temperature coefficient (MTC) will become more negative and the control rod worth will increase. These advantages of the new BA are demonstrated with three verification cases: a 17 × 17 Westinghouse (WH) type fuel assembly, a 16 × 16 Combustion Engineering (CE) type fuel assembly, and an OPR-1000 equilibrium core.

As one of participants of recent coordinated research project proposed by International Atomic Energy Agency and China Institute of Atomic Energy, the computational reactor physics and experiment laboratory of Ulsan National Institute of Science and Technology, Republic of Korea, is currently focused on a study involving the neutronic simulation of the China Experimental Fast Reactor (CEFR) start-up tests. The CEFR start-up tests include obtaining measurements of the criticality, control rod worth, sodium void reactivity, temperature reactivity, and subassembly swap reactivity. The fast reactor neutronic analysis code SARAX is selected for performing such simulations for additional validation. The obtained numerical results are compared with measurement data. In addition, the differences in the expected results of the heterogeneous and homogeneous models are quantified in this study. According to the simulation, the calculated results agreed well with the measured values in the case of the majority of the neutronic characteristics.