Fission yield uncertainty propagation with Monte Carlo method for decay heat calculation

Decay heat is a key safety parameter in nuclear systems. Its accurate prediction requires reliable nuclear data and robust uncertainty quantification methods. This master thesis focuses on the propagation of fission yield uncertainties to decay heat calculations using the Monte Carlo approach, with particular attention to the effects of choosing different sampling methods, including lognormal and gamma distributions, and on the role of covariance matrices. Various sampling methods are applied using the JEFF-4.0 library, which provides official covariance matrices for thermal systems. The resulting samples are evaluated through statistical indicators, some taken from the literature and some developed specifically for this work, to assess convergence in probability and the quality of the samples produced by each method. Case studies on thermal Pu-239 fission pulses are performed with the COCODRILO code, developed at Subatech. Results show that different sampling distributions have little impact on the final decay heat values and uncertainties, while correlations among fission yields significantly reduce uncertainties. This work, carried out within the European ENDURANCE project, extends the capabilities of COCODRILO and provides a methodological foundation for future studies on innovative reactor concepts, including molten salt reactors, to be carried out within the PhD which follows this work.