In recent years there has been an increasing demand from nuclear research, industry, safety, and regulation bodies for best estimate predictions of Light Water Reactors (LWR’s) performances to be provided with their confidence bounds. From a neutronic point of view, among the different sources of uncertainty the main challenge is represented by the one related to the accuracy of the nuclear data libraries used in the transport calculations. The assessment of nuclear data uncertainties and their impact on the main reactor parameters plays a fundamental role not only for criticality safety but also in burnup analyses. In facts, the accurate prediction of nuclear parameters in burnup calculations strongly affects the management of spent nuclear fuel, the core design, as well as the economy and safety of nuclear reactors. In this paper a study related to the impact of the nuclear data uncertainties on the evolution in time of the criticality and the nuclide concentrations in burnup calculations is presented. The analysis has been performed by using a statistical sampling methodology in which all the uncertain parameters are handled as random dependent variables by a sampling procedure. The probability distributions of the uncertain input parameters are used to generate random variations of these input quantities starting from a covariance library in a 56-group energy structure. Calculations have been performed by means of the SCALE 6.2.2 code and ENDF/B-VII.1 nuclear data. The method has been tested on a PWR pin cell model representative of the TMI-1 15 × 15 assembly as defined in an international benchmark exercise. In the first part of the paper the methodology and the neutronics modelling of the problem are presented.
- Nuclear Engineering Division
Propagation of Nuclear Data Uncertainties in PWR Pin-Cell Burnup Calculations via Stochastic Sampling
Mercatali, L, Alzaben, Y, & Sanchez Espinoza, VH. "Propagation of Nuclear Data Uncertainties in PWR Pin-Cell Burnup Calculations via Stochastic Sampling." Proceedings of the 2018 26th International Conference on Nuclear Engineering. Volume 3: Nuclear Fuel and Material, Reactor Physics, and Transport Theory. London, England. July 22–26, 2018. V003T02A033. ASME. https://doi.org/10.1115/ICONE26-81711
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