The motivation for this work stems from the desire within the nuclear industry to improve the economic efficiency of the fuel cycle by moving to longer operational periods. The primary objective of this thesis is to validate the traditional two-step computational approach against given plant data, which is necessary for the design and modeling of alternative high-assay low-enriched fuel cycles with longer cycle lengths.
An established computational sequence for modeling core behavior during the fuel cycle irradiation period involves the use of lattice codes followed by a nodal diffusion core solver. In this thesis, the Monte Carlo-based SERPENT code is coupled to the nodal diffusion code, DYN3D.
The validation data focused on five cycles, and the analysis itself focused on the three benchmarking cycles. The first step in modeling these cycles was to generate the various cross section types in SERPENT that accounted for central fuel layers, blanket fuel layers, and reflector assemblies.
Code-to-code verification was done prior to the benchmarking. This included 2D fuel assembly burnup analysis, 3D fuel assembly with dependencies analysis, and 2D full core comparisons. Very good agreement was obtained for all the examined models. The work also included sensitivity on few-group cross section generation. Finally, the implemented equilibrium search was applied to reproduce performance of the benchmarked cycles.
The last part of this thesis concentrates on preliminary studies regarding the economic benefits of high-enriched cores, where the primary goal is to increase economic margins. In future research, the results obtained intended to be applied with the developed SERPENT-DYN3D computational sequence to investigate the behavior of a higher-enriched core.
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