The radioactive cesium, released from the normal operation or the accidental operation of nuclear facilities, should be regularly monitored for environmental regulatory compliance. The 135Cs/137Cs isotopic ratios, potentially useful for long-term tracking Cs transport in seawater, can be used as a tool of understanding how radionuclides are transported from different nuclear production source terms and distributed in the ocean. The ultra-high sensitive mass spectrometers (TIMS, SF-ICP-MS and TQ-ICP-MS) have been used to measure the 135Cs/137Cs isotopic ratios. However, the radiochemical separation of Cs from the seawater matrix is essential for the analysis of Cs using the mass spectrometers. An automated radiochemical procedure for the separation of Cs in seawater was developed for the analysis of 135Cs/137Cs isotopic ratios using a sequential column chromatography with AMPPAN and AG50Wx8 cation exchange resins. National Instrument’s LabVIEW is a graphical programming language and a powerful tool for the instrument control. A virtual instrument system for the automated separation of cesium isotopes was developed by the state machine of the fundamental design patterns in LabVIEW. In this study, the conceptual designs of an automated separation system of cesium isotopes, its virtual instrument system based on the LabVIEW state machine architectures and an automated radiochemical procedure were described for the purification of cesium isotopes at trace levels found in seawater discharged from the various nuclear facilities.

According to Article 4 and 5 of the Nuclear Safety and Security Commission (NSSC) Notice No. 2020-6, radioactive waste packages should be classified by radioactive levels, and finally permanently shipped to underground or surface disposal facilities. The level of the radioactive waste package is determined based on the concentrations of the radionuclides suggested in Article 8 of NSSC Notice No. 2021-26. Since most of the radionuclides in radioactive wastes are beta nuclides, chemical separation and quantification of the target nuclides are essential. Conventional methods to classify chemically non-volatile radionuclides such as Tc-99, Sr-90, Nb- 94, Fe-55 take a lot of time (about 5 days) and have low efficiency. An automated non-volatile nuclide analysis system based on the continuous chemical separation method of radionuclides has been developed to compensate for this disadvantages of the conventional method in this study. The features of the automated non-volatile nuclide separation system are as follows. First, the amount of secondary waste generated during the chemical separation process is very small. That is, by adopting an open-bed resin column method instead of a closed-bed resin column method, additional fittings and connector are unnecessary during the chemical separation. In addition, because the peristaltic pump is supplied for the sample and solution respectively, it is great effective to prevent cross-contamination between radioactive samples and the acid stock solution for analysis. Second, the factors that may affect results, such as solution amount, operating time and flow rate, are almost constant. By mechanically controlling the flow rate precisely, the operating time and additional factors required during the separation process can be adjusted and predicted in advance, and the uncertainty of the chemical separation process can be significantly reduced. Finally, it is highly usable not only in the continuous separation process but also in the individual separation process. It can be applied to the individual separation process because the user can set the individual sequence using the program. As a result of the performance evaluation of the automation system, recovery rates of about 80–90% and reproducibility within 5% were secured for all of the radionuclides. Furthermore, it was confirmed that the actual work time was reduced by more than 50% compared to the previous manual method. (It was confirmed that the operation time required during the separation process was reduced from 6 days to 3 days.) Based on these results, the automation system is expected to improve the safety of workers in radiation exposure, reduce human error, and improve data reliability.