Irradiated fuel salt data library for a molten salt reactor produced with Serpent2 and SOURCES 4C codes

This paper describes the creation and description of a nuclear fuel isotopics dataset for irradiated fuel salt from a Molten Salt Reactor (MSR). The dataset has been created using simulations carried out using the Monte-Carlo particle transport code, Serpent 2.1.32 (released February 24, 2021) and the calculation code SOURCES 4C (released October 09, 2002) for computing properties of irradiated molten fuel salt. The dataset comprises isotopic mass densities of 1362 isotopes (including fission products and major and minor actinides) and their corresponding contributions to decay heat, gamma activity, and spontaneous fission rates computed by Serpent 2.1.32 as well as overall neutron emission rates from spontaneous fission and (ɑ, n) reactions computed by SOURCES 4C. These quantities are computed for a model MSR core utilizing a full-core 3D model of the Seaborg Compact Molten Salt Reactor (CMSR). The dataset spans a wide range of values of burnup (BU), initial enrichment (IE) and cooling time (CT) over which the above-mentioned quantities are reported. The structure of the dataset includes isotopic mass densities (in g/cm³), followed by isotope-wise contributions to decay heat (denoted by suffix '_DH' and reported in Watts), gamma photon emission rates (denoted by suffix '_GS' and reported photons per second), and spontaneous fission rates (denoted by suffix '_SF' and reported in fissions per second). In addition to these columns, the data also includes total neutron emission rates from 1) spontaneous fission (denoted by 'SF' and reported in neutrons per second per cm³), and 2) (ɑ, n) reactions (denoted by 'AN' and reported in neutrons per second per cm³). In total, the dataset has 310,575 rows of different combinations of fuel burnup, initial enrichment, and cooling time (BIC) values spanning the realistic possible range of these parameters. The dataset is made available for public use in a comma-separated value file that can be easily read using one of the numerous popular data analysis tools such as NumPy or Pandas.