Abstract
In the search for new ways to generate carbon-free, reliable base-load power, interest in advanced nuclear energy technologies, particularly Molten Salt Reactors (MSRs), has resurged with multiple new companies pursuing MSR commercialization. To further develop these MSR concepts, researchers need simulation tools for analyzing liquid-fueled MSR depletion and fuel processing. However, most contemporary nuclear reactor physics software is unable to perform high-fidelity full-core depletion calculations for a reactor design with online reprocessing. This paper introduces a Python package, SaltProc, which couples with the Monte Carlo code, SERPENT2 to simulate MSR online reprocessing by modeling the changing isotopic composition of MSR fuel salt. This work demonstrates SaltProc capabilities for a full-core, high-fidelity model of the commercial Molten Salt Breeder Reactor (MSBR) concept and verifies these results to results in the literature from independent, lower-fidelity analyses.
Original language | English (US) |
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Pages (from-to) | 366-379 |
Number of pages | 14 |
Journal | Annals of Nuclear Energy |
Volume | 128 |
DOIs | |
State | Published - Jun 2019 |
Keywords
- Depletion
- Molten salt breeder reactor
- Molten salt reactor
- Nuclear fuel cycle
- Online reprocessing
- Python
- Salt treatment
ASJC Scopus subject areas
- Nuclear Energy and Engineering