Nuclear reactors are a source of electron antineutrinos due to the presence of unstable fission products that undergo β −decay. They will be exploited by the JUNO experiment to determine the neutrino mass ordering and to get very precise measurements of the neutrino oscillation parameters. This requires the reactor antineutrino spectrum to be characterized as precisely as possible both through high-resolution measurements, as foreseen by the TAO experiment, and detailed simulation models. In this paper, we present a benchmark analysis utilizing Serpent Monte Carlo simulations in comparison with real pressurized water reactor spent fuel data.Our objective is to study the accuracy of fission fraction predictions as a function of different reactor simulation approximations. Then, using the Beta Shape software, we construct reactor antineutrino spectrum using the summation method, thereby assessing the influence of simulation uncertainties on it.

Analysis of reactor burnup simulation uncertainties for antineutrino spectrum prediction

Clementi, C.;Ortica, F.;Romani, A.;
2024

Abstract

Nuclear reactors are a source of electron antineutrinos due to the presence of unstable fission products that undergo β −decay. They will be exploited by the JUNO experiment to determine the neutrino mass ordering and to get very precise measurements of the neutrino oscillation parameters. This requires the reactor antineutrino spectrum to be characterized as precisely as possible both through high-resolution measurements, as foreseen by the TAO experiment, and detailed simulation models. In this paper, we present a benchmark analysis utilizing Serpent Monte Carlo simulations in comparison with real pressurized water reactor spent fuel data.Our objective is to study the accuracy of fission fraction predictions as a function of different reactor simulation approximations. Then, using the Beta Shape software, we construct reactor antineutrino spectrum using the summation method, thereby assessing the influence of simulation uncertainties on it.
2024
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1587054
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