In the last decade, the best estimate plus uncertainty methodologies in nuclear technology and nuclear power plant design have become a trending topic in the nuclear field. Since BEPU was allowed for licensing purposes by the most important regulator bodies, different uncertainty assessment methods have become popular, overall non-parametric methods. While non-parametric tolerance regions can be well stated and used in uncertainty quantification for licensing purposes, the propagation of the uncertainty through different codes (multi-scale, multiphysics) in cascade needs a better depiction of uncertainty than the one provided by the tolerance regions or a probability distribution. An alternative method based on the parametric or distributional probability boxes is used to perform uncertainty quantification and propagation regarding statistic uncertainty from one code to another. This method is sample-size independent and allows well-defined tolerance intervals for uncertainty quantification, manageable for uncertainty propagation. This work characterizes the distributional p-boxes behavior on uncertainty quantification and uncertainty propagation through nested random sampling.

近十年来，核技术和核电厂设计中的最佳估计加不确定性方法已成为核领域的热门话题。由于最重要的监管机构允许 BEPU 用于许可目的，因此不同的不确定性评估方法变得流行，整体非参数方法。虽然非参数容差区域可以很好地说明并用于许可目的的不确定性量化，但不确定性通过级联中的不同代码（多尺度、多物理场）传播需要比容差区域提供的更好的不确定性描述或概率分布。使用基于参数或分布概率框的另一种方法来执行关于从一个代码到另一个代码的统计不确定性的不确定性量化和传播。这种方法与样本量无关，允许为不确定性量化定义明确的容差区间，可管理不确定性传播。这项工作通过嵌套随机抽样表征了不确定性量化和不确定性传播的分布 p-boxes 行为。