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Estimation of U Ore Production Using Bayesian Network
Concerns about North Korea’s 7th nuclear test have been rising recently, and it is a significant threat to the situation around the Korean Peninsula. Amidst these threats, the Korean government also shows a strong will for denuclearizing the Korean Peninsula, referring to the “Audacious Initiative.” For denuclearization negotiations with North Korea, it is essential first to understand North Korea’s nuclear capabilities. However, since access to information is complicated and contains many uncertainties, many studies have been conducted to estimate it. Among them, Von Hippel surveyed to estimate the total amount of uranium ore based on information on uranium mining, which is relatively widely known throughout North Korea’s nuclear fuel cycle, and the amounts of HEU and Pu suggested by many experts. KINAC has conducted a study on a methodology that can narrow the estimation range and improve reliability through the Bayesian Network based on Von Hippel’s research results. However, in this study, the probability distribution is assumed to be the simplest form of uniform distribution, and the estimation formula for the amount of Pu produced compared to the amount of uranium loaded in the core is used as it is, which is an error in Von Hippel’s study. Improvement is needed. This study proposes a more reliable BN model by supplementing this and attempts to estimate the amount of uranium ore that North Korea produces or possesses. Of course, the data used as the basic structure of the model is insufficient, and the estimation formula is straightforward, so it is somewhat unreliable to trust the estimate for uranium ore. However, it is expected to be a suitable methodology that can narrow the scope of North Korea’s nuclear material production estimate or compensate for the uncertainty of the nuclear material production estimation model being developed at KINAC.
