Quantifying TBR uncertainty due to lead nuclear data in HCLL blanket modelling by the Total Monte-Carlo method

Abstract

The design of complex and expensive fusion breeder blanket assemblies requires detailed engineering studies that rely upon nuclear analyses to determine essential operating parameters, including tritium production rate, nuclear heating and radiation damage. Lack of precise knowledge of input nuclear physics, referred to as nuclear data, results in simulation uncertainties to which some parameters are highly sensitive. In this work, a set of Pb TENDL-2015 neutron-induced files generated using sampled input parameters are employed using the Total Monte-Carlo method to quantify the uncertainty of tritium breeding in a Helium Cooled Lithium Lead blanket of a demonstration fusion plant. Fully correlated uncertainties including neutron multiplicity reactions and elastic scattering result in a tritium production uncertainty of ±1.2%(1σ).