Data for: Proliferation Resistance Evaluation for TRU Fuel Cycle employing HTGR using PRAETOR code

These data are output data of proliferation resistance (PR) of nuclear fuels such as inert matrix fuel (IMF) for high temperature gas cooled reactor (HTGR) and mixed oxide fuel for conventional light water reactor obtained by running PRAETOR code. PR evaluation and analysis were performed for some diversion scenarios assuming different target materials and plutonium extraction fraction in the transformation process to get target metal from diverted nuclear material. In the PRAETOR code, the PR evaluation is carried out through three tiers using their respective weights and the multi-attribute utility analysis (MAUA) methodology. The MAUA methodology is a well-established decision-analysis technique wherein a value or utility function is used to represent the attractiveness of a particular route for nuclear material diversion or theft. The sixty-eight attribute inputs are folded into utility values for eleven subgroups in Tier 1. In Tier 2, the eleven subgroups are combined into utility values for four stages consisting of diversion, transportation, transformation and weaponization. Finally, the four stages are combined to an overall PR metric value in Tier 3 evaluation.本数据集为通过运行PRAETOR程序得到的核燃料防扩散性能（proliferation resistance, PR）输出数据，涵盖高温气冷堆（high temperature gas cooled reactor, HTGR）用惰性基质燃料（inert matrix fuel, IMF）以及常规轻水堆用混合氧化物燃料两类核燃料。研究针对多种核材料转移场景开展了防扩散性能评估与分析，这些场景假设了从转移的核材料中提取目标金属的转化过程中，采用不同的目标材料及钚提取率。在PRAETOR程序中，防扩散性能评估通过三层架构开展，各层级采用对应权重，并结合多属性效用分析（multi-attribute utility analysis, MAUA）方法。多属性效用分析方法是一套成熟的决策分析技术，其通过价值函数或效用函数来表征核材料转移或盗窃的特定路径的吸引力。在第一层（Tier 1）中，68项属性输入被整合为11个细分子项的效用值；在第二层（Tier 2）中，11个细分子项被整合为4个阶段的效用值，这4个阶段分别为转移、运输、转化及武器化；最终在第三层（Tier 3）评估中，4个阶段的效用值被整合为整体防扩散性能指标值。