Propagation of nuclear data uncertainties for ELECTRA burn-up calculations

TL;DR

This study propagates nuclear data uncertainties for the ELECTRA reactor's fuel inventory during burn-up using the Total Monte Carlo method, highlighting the impact of data uncertainties on reactor parameters and the potential for benchmark data to reduce these uncertainties.

Contribution

It introduces a fast TMC methodology for efficient uncertainty propagation in nuclear reactor burn-up calculations, focusing on the ELECTRA reactor and Pu-239 data.

Findings

Uncertainty in long-term radiotoxicity and decay heat is insignificant.

Uncertainty in minor actinides can be large, affecting recycling.

Criticality benchmarks can reduce inventory uncertainties.

Abstract

The European Lead-Cooled Training Reactor (ELECTRA) has been proposed as a training reactor for fast systems within the Swedish nuclear program. It is a low-power fast reactor cooled by pure liquid lead. In this work, we propagate the uncertainties in Pu-239 transport data to uncertainties in the fuel inventory of ELECTRA during the reactor life using the Total Monte Carlo approach (TMC). Within the TENDL project the nuclear models input parameters were randomized within their uncertainties and 740 Pu-239 nuclear data libraries were generated. These libraries are used as inputs to reactor codes, in our case SERPENT, to perform uncertainty analysis of nuclear reactor inventory during burn-up. The uncertainty in the inventory determines uncertainties in: the long-term radio-toxicity, the decay heat, the evolution of reactivity parameters, gas pressure and volatile fission product content. In this work, a methodology called fast TMC is utilized, which reduces the overall calculation time. The uncertainty in the long-term radiotoxicity, decay heat, gas pressure and volatile fission products were found to be insignificant. However, the uncertainty of some minor actinides were observed to be rather large and therefore their impact on multiple recycling should be investigated further. It was also found that, criticality benchmarks can be used to reduce inventory uncertainties due to nuclear data. Further studies are needed to include fission yield uncertainties, more isotopes, and a larger set of benchmarks.