Demonstrates rapid dose rate calculations in nuclear fuel systems, suggesting improved efficiency for evaluations.
The dose rates for used nuclear fuel storage systems and transportation packages are typically calculated using three-dimensional Monte Carlo (MC) computer codes such as Monte Carlo N-Particle (MCNP) or Standardized Computer Analyses for Licensing Evaluation (SCALE)/Monaco with Automated Variance Reduction using Importance Calculations (MAVRIC). As these are heavily shielded deep-penetration problems, the MC calculations require a significant number of particle histories to produce statistically acceptable estimates for the external dose rates. Even with the variance reduction techniques available with these programs, the runtimes for a single calculation often take days to achieve acceptably low statistical uncertainties. The “on-the-fly” method is being developed for the Storage, Transportation and Disposal Analysis Resource and Data System (STANDARDS) code system. It is named “on-the-fly” to describe how dose rate calculations can be performed quickly, reducing runtimes of days to just minutes. This is achieved by performing the MC calculations ahead of time on a per-particle and per-particle-energy basis for each axial burnup zone within each assembly location for many locations of interest around a specific spent nuclear fuel (SNF) storage system or transportation package design. Once the loading of a system or package is determined, the radiation source terms for gamma rays and neutrons emitted by the irradiated fuel, as well as for 60Co in the activated fuel assembly hardware, are calculated using the Transport Rigor Implemented with Time-dependent Operation for Neutronic depletion (TRITON)/Oak Ridge Isotope GENeration (ORIGEN) Assembly Isotopics (ORIGAMI) codes in the SCALE code system. The source term strength and spectra for each assembly are used with the on-the-fly libraries to quickly calculate the dose rate of the SNF storage system or transportation package. Although this method consists of a significant effort to generate libraries ahead of time, it results in the ability to save significant time when a specific system or loading pattern needs to be analyzed in the future. This paper presents the implementation of on-the-fly libraries into STANDARDS.
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Kucinski et al. (2026) studied this question.
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