The illicit trafficking of radioactive materials, especially weapon-grade uranium or plutonium, is a significant security threat. Nuclear forensics helps trace the illicit trafficking of radioactive materials. The present study develops the methods for the forensics of the possible origins of fuels irradiated in nuclear reactors, which are the most powerful sources producing radioactive materials, including plutonium. Three key factors are significant for irradiated fuel forensics, namely, initial ${}^{235}\mathrm{U}$ enrichment, burnup, and the type of irradiation nuclear reactors. The methods for the first two are determined based on experimental data of six nuclear-reactor technologies and are further verified using the neutron-transport-depletion coupling simulation of the two major commercial reactor technologies, a pressurized-water reactor (PWR) and a boiling-water reactor (BWR). In addition, three machine-learning techniques are applied to discriminate between a PWR and a BWR, which are quite similar in neutronic properties, with nice accuracy and generalization ability. In summary, the presently determined methods provide a reliable pathway to predict the origins of spent nuclear fuels.

中文翻译：

---

六种核反应堆乏燃料核取证的线性回归和机器学习

放射性物质的非法贩运，尤其是武器级铀或钚，是一个重大的安全威胁。核取证有助于追踪放射性材料的非法贩运。本研究开发了对核反应堆中辐照燃料的可能来源进行取证的方法，核反应堆是生产包括钚在内的放射性物质的最强大来源。三个关键因素对辐照燃料取证很重要，即初始${}^{235}\mathrm{ü}$浓缩、燃耗和辐照核反应堆的类型。前两个方法是根据六种核反应堆技术的实验数据确定的，并使用压水反应堆 (PWR) 和沸腾反应堆这两种主要商业反应堆技术的中子传输损耗耦合模拟进一步验证-水反应堆（BWR）。此外，应用三种机器学习技术来区分中子特性非常相似的压水堆和沸水堆，具有良好的准确性和泛化能力。总之，目前确定的方法提供了预测乏核燃料来源的可靠途径。