As the demand for nuclear power increases as a means to achieve carbon neutrality, concerns about nuclear proliferation have also grown. Consequently, significant researches have conducted to enhance nuclear non-proliferation resistance. Among these research, nuclear material attractiveness is a methodology used to evaluate how appealing a particular material is for potential use in nuclear weapons, based on the characteristics of that material. Existing nuclear material attractiveness assessments focused on materials like U, Pu, and TRU, which could be directly used in the production of nuclear weapons. However, these assessments did not consider how the properties of nuclear materials change throughout the nuclear fuel cycle, with each facility process. This study assumed a scenario of the nuclear fuel cycle of graphite reduction reactors and analyzed including enrichment facilities and PUREX. This study used the FOM (Figure-Of-Merit) method developed by LANL (Los Alamos National Laboratory) for evaluating the nuclear material attractiveness. The FOM formula consists of three parameters such as critical mass, heat content, and dose The critical mass of targe materials and the dose evaluation were conducted using the Monte Carlo N-Particle code. The heat content was calculated using the ORIGEN code embedded in the Scale code. In particular, if U-238 is dominant in the facility’s materials, such as mining and refining facilities, and critical mass evaluation is unpractical. Therefore, 1SQ (Significant Quantity) of that uranium was assumed as the critical mass value for the FOM evaluation, even though 1SQ is not identical to the critical mass As a result of this study, the attractiveness of Pu produced by PUREX among all nuclear fuel cycle facilities was 2.7616, which was the most attractive to be diverted to nuclear weapons. Through this study, it was shown that the proliferation risk of the nuclear facilities in the nuclear fuel cycle and risk of diversion among those facilities.

Bayesian statistics, which is an approach to analyzing data based on Bayes’ theorem, is currently widely used in all fields. However, it has been applied very limitedly to studies related to nuclear nonproliferation. Therefore, this paper provides a knowledge base and directions for using various Bayesian techniques in nuclear non-proliferation. First, the concepts and advantages of the Bayesian approach are summarized and the basic solving methods of Bayesian inference are explained. The Bayesian approach enables more precise posterior estimation using the prior probability and the likelihood functions. To solve Bayes’ theorem, it is necessary to use the conjugate prior distribution, which is analytically solvable, or to use a numerical approach with computing power. Next, for several Bayesian statistics methods, the purpose of use and the mathematical derivation process are described. Bayesian linear regression analysis aims for obtaining a function that outputs the closest value to data of variables and results. Factor analysis is mainly used to derive a smaller number of unobserved latent variables that can represent observed variables. The logit and probit model are nonlinear regression models for when the outcome is binary. The hierarchical model is to analyze by introducing hyper-parameters in an integrated manner when there are several groups of similar data. The Bayesian approach of these methods is generally based on the numerical solution of the Bayesian inference of the multivariate normal distribution. Finally, the previous researches that each introduced method have been applied to nuclear non-proliferation are investigated, and research topics that can be applied in the future are suggested. Bayesian statistics have been mainly used for precise estimation of the amount, location, and radioactivity spectrum of nuclear materials using detectors. Using Bayesian approach, it will be possible to perform various analyzes. For example, the change of activeness of nuclear program can be estimated by Bayesian inferences on the frequency and scale of nuclear tests. And it can be tried predicting the production of plutonium according to the core configuration and burnup using the Bayesian linear regression. Also, by introducing the Bayesian approach to factor analysis or logit analysis of nuclear development motives or nuclear proliferation probability, it can be expected to improve precision. With the development of computer technology, the use of Bayesian statistics increases rapidly. Based on the theory and applied topics summarized in this paper, it is expected that Bayesian statistics will be more actively used for nuclear non-proliferation in the future.

Nuclear security event involving nuclear and other radioactive materials outside of regulatory control (MORC) has the potential to cause severe consequences for public health, the environment, the economy and society. Each state has a responsibility to develop national nuclear security measures including nuclear forensics to respond to such events. In Japan, national nuclear forensics capability building efforts mainly based on research and development (R&D) have been conducted since 2010, in accordance with national statement of Japan at the Nuclear Security Summit in Washington DC. Most of that work is undertaken at the Integrated Support Center for Nuclear Non-proliferation and Nuclear Security (ISCN) of the Japan Atmic Energy Agency (JAEA) in close cooperation with other competent authorities. The ISCN has made increased contributions to the enhancement of international nuclear security by establishing technical capabilities in nuclear forensics and sharing the achievements with the international community. The ISCN has mainly engaged in R&Ds for establishing and enhancing nuclear forensics technical capability. As for the laboratory capability, several new pieces of analytical equipment have been introduced for nuclear forensics R&D purposes. High-precise measurement techniques validated in the past nuclear forensics incidents have been established, and novel techniques that can contribute to the more timely and confident nuclear forensics signature analysis have been developed. The ISCN has been also developed a proto-type nuclear forensics library based on the data of nuclear materials possessed for past nuclear fuel cycle research in JAEA. These technical capability developments have been conducted based on the cooperation with international partners such as the U.S. Department of Energy and EC Joint Research Center, as well as participation in exercises organized by Nuclear Forensics International Technical Working Group (NF-ITWG). Recent R&D works have been mainly based on the needs of domestic competent authorities, such as first responders and investigators, and aim to develop technologies covering the entire spectrum of nuclear forensics processes from crime scene investigation to laboratory analysis and interpretation. One important key issue is the enhancement of technical capability for post-dispersion nuclear forensics. For instance, the ISCN has carried out the development of radiation measurement equipment coupled with the low-cost and mobile radiation detectors that uses machine-learning algorithms for quick and autonomous radioisotope identification to support first responders during crime scene investigations. Laboratory measurement techniques for samples collected at a post-dispersion crime scene are also among the important technical issues studied at the ISCN. The application of emerging technologies to nuclear forensics has also been studied. This includes the application of deep leaning models to nuclear forensics signature interpretation that could provide more confident results, as well as the development of contamination imaging technology that could contribute to the analytical planning on the samples in collaboration with conventional forensics. Many analytical techniques have been developed and the capability to analyze nuclear and other radioactive materials for nuclear forensics purposes has been considerably matured over the past decade. The challenges of post-dispersion samples, collaboration with conventional forensics and the development of novel signatures will be more important in the near future. Therefore, the ISCN will promote the R&Ds to further enhance the technical capabilities solving these issues. In addition, the ISCN is also promoting to expand the nuclear forensics research into universities and other research institutes in Japan. This is expected to contribute to the establishment of a domestic nuclear forensics network that enables to respond timely and flexibly to the MORC incidents, and to the maturation of nuclear forensics as a new academic field.