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代码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。研究针对多种转移场景开展了防扩散性能评估与分析，此类场景假设了从转移核材料转化为目标金属的过程中，采用不同的目标材料与钚提取率。在PRAETOR代码中，防扩散性能评估采用三级架构开展，各级别配备对应权重，并运用多属性效用分析（multi-attribute utility analysis, MAUA）方法。多属性效用分析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某一特定路径的吸引力。一级评估（Tier 1）中将68项属性输入整合为11个子组的效用值；二级评估（Tier 2）将11个子组整合为4个阶段的效用值，这4个阶段分别为转移、运输、转化与武器化；最终在三级评估（Tier 3）中，将4个阶段的效用值合并为整体防扩散性能指标值。