검색결과

검색조건
좁혀보기
검색필터
결과 내 재검색

간행물

    분야

      발행연도

      -

        검색결과 1

        1.
        2023.05 구독 인증기관·개인회원 무료
        As the use of nuclear energy has been expanded, issues in a spent nuclear fuel management are raised. Several methods have been proposed and developed to manage spent fuels safely and efficiently. One method is to reduce environmental burden in disposal of spent fuels by decreasing volume of high-level waste. A nuclides management process (NMP) is one example. Through this novel process, it is able to separate highly mobile nuclides (ex. iodine, krypton), high thermal emission nuclides (ex. strontium, barium), and optionally, uranium from spent fuels. Since the NMP is a back-end fuel cycle technology, a reliable safeguards system should be employed in the facility. As international atomic energy agency (IAEA) recommends safeguards-by-design (SBD), it is desirable to investigate an appropriate safeguards approach at a step of technology development. Process monitoring (PM) is a complemental safeguards technology for traditional safeguards technologies which based on mass balance. PM traces nuclear materials indirectly but consecutively by using process parameters such as temperature, pressure, and flow of fluid. These parameters are obtainable by installing appropriate sensors. In a respect of SBD, PM is a promising approach to achieve the safeguards goal, the timely detection of diversion of a nuclear material. However, it is necessary to classify useful process parameters from all available signals which provided from PM in order to properly utilize PM. In this study, we investigated application methods of the PM approach to NMP. NMP consists of several unit processes in series. Firstly, we inspected a principle and a feature of each unit process. Based on the results, we evaluated applicability of the PM approach to each unit process according to effectiveness in enhancing safeguardability. Several unit processes were expected that their safeguards are able to be enhanced by using certain process parameters from PM.