A method of quantitatively analyzing radioactivity of uranium waste in the In-situ measurement using Bayesian inference was proposed. When applying the traditional efficiency calibration method, which uses standard sources or Monte Carlo simulation, the radioactivity error is large depending on the degree of spread of the radioactive contamination especially in large sample such as a 200 L drum. In addition, the existing method has a limitation in that it is difficult to reflect the uncertainty according to the location of the source. In this preliminary study, to overcome the limitations of the existing method, a Bayesian statistical-based radioactivity quantitative analysis model was proposed that can increase the accuracy of analysis even in situations where radioactive contamination of uranium waste is non-uniformly distributed. As a result of evaluating the simulated waste with the proposed Bayesian method, the accuracy was improved more than about 6 times compared to the classical efficiency calibration method.

• Jichang Ryu(KEPCO Nuclear Fuel, 242, Daedeok-daero 989beon-gil, Yuseong-gu, Daejeon)
• Junghwan Hong(KEPCO Nuclear Fuel, 242, Daedeok-daero 989beon-gil, Yuseong-gu, Daejeon)
• Jungsuk Park(KEPCO Nuclear Fuel, 242, Daedeok-daero 989beon-gil, Yuseong-gu, Daejeon)
• Gyuseong Cho(Korea Advanced Institute of Science and Technology, 291, Daehak-ro, Yuseong-gu, Daejeon) Corresponding author