Within the air purification system of a nuclear power plant, specific radioactive isotopes are extracted from gases through adsorption onto activated carbon. To properly dispose of used activated carbon, it is essential to determine the concentration of radioactive nuclides within it. This study discusses the application of the pyrolysis method for analyzing the concentrations of 3H and 14C in spent activated carbon. The pyrolysis was conducted using Raddec’s Pyrolyser, with adjustments made to parameters such as temperature profiles, airflow rates, sample quantities, and trapping solution volumes. The evaluation method for the pyrolysis of activated carbon to analyze 3H and 14C involved adding 3H and 14C sources to the activated carbon before use and subsequently assessing the recovery rates of the added sources in comparison to the analysis results.

In order to establish disposal plans for sludge, which is one of the untreated waste materials from domestic nuclear power plants, it is necessary to determine the radioactivity concentration of radioactive isotopes. In this study, we aim to evaluate the gross alpha radioactivity of sludge containing radioactive contaminants after pre-treatment, in order to assess the level of sludge waste and obtain analytical data for discussing disposal methods. Samples of sludge generated from nuclear power plants were pre-treated, solutionized, and prepared as analysis samples for evaluating the gross alpha radioactivity.

Typically, the bottom of the effluent treatment facility at a nuclear power plant contains sediment, which is low-contamination waste consisting of sludge, gravel, sand, and other materials from which radioactive contaminants have been removed. Among these sediments, sludge is an irregular solid form consisting of small particles that are coagulated together, with radioactive isotopes containing cobalt attached. Currently, there is a record of disposing of dry active waste from domestic nuclear power plants, and efforts are underway to gather basic data for the disposal of untreated waste such as sludge, spent filter, and spent resin. In particular, the classification and disposal methods of waste will be determined based on the radioactivity concentration. Therefore, plans are being made to determine the radioactivity concentration of radioactive isotopes and establish disposal plans for sludge samples. In this study, pre-treatment and solutionization were carried out for the analysis of radioactive isotopes in sludge sampels from nuclear power plants. The deviation of the gamma radioisotope analysis results was derived to obtain an optimal sample quantity that represents the sludge.

For the disposition of radioactive wastes generated from nuclear power plant, radioisotope inventory must be analyzed to determine an activity concentration of radionuclides. Radionuclides in low- and intermediate-low-level of radioactive wastes, however, can be easily classified to easyto- measure (ETM) and difficult-to-measure (DTM) nuclides. ETM nuclides are gamma emitting nuclides that is relatively easy to measure because they do not need to be destroyed for the preprocessing. On the other hands, DTM nuclides are alpha and beta emitting nuclides that need to be destroyed for the preprocessing and also need chemical separation. Currently, measurement methods for DTM nuclides are developed and in this paper measurement methods of Fe-55, Ni-59, Ni-63, Sr-90 and Tc-99 will be introduced.

In the ocean, there exist infinite resources, including certain metallic elements that can serve as potential energy sources. One of the methods for extracting these dissolved resources from seawater involves adsorption. This study discusses the results of experiments conducted in real seawater using a developed fiber-type adsorbent capable of extracting dissolved oceanic resources. The fiber-type adsorbent was deployed in seawater to adsorb the elemental resources. It was then retrieved after 2, 3, and 4 weeks for evaluation of its adsorption performance. The evaluation was carried out by dissolving the adsorbent in a strong acidic solution and calculating the adsorption amount per gram of adsorbent using ICP-MS. The results indicated that the adsorption performance was slightly lower than previously reported values. Nevertheless, it confirmed the feasibility of adsorbing and recovering dissolved resources from actual seawater

To evaluate the inventory of radionuclides for the disposal of waste generated from nuclear power plants, indirect assessment methods such as the scaling factor method or average radioactivity concentration method can be applied. A scaling factor represents the average concentration ratio between key radionuclides and difficult-to-measure (DTM) radionuclides, while the average radioactivity concentration refers to the average concentration of DTM radionuclides, regardless of the concentration of key radionuclides or within specific ranges of key radionuclide concentrations. These indirect assessment methods can be statistically derived through the analysis of representative drums. This study will address how to apply these scaling factors and average radioactivity concentrations. Firstly, the concentration of gamma-emitting radionuclides will be analyzed using a drum radionuclide analyzer, and the concentration of DTM radionuclides will be determined by applying scaling factors specific to each DTM radionuclide. In the case of using the average radioactivity concentration method, the average concentration of DTM radionuclides will be applied independently of the concentration of gamma-emitting radionuclides. It is crucial to perform radioactive decay correction based on the date of generation or disposal when applying scaling factors or average radioactivity concentration. Additionally, for repackaged 320 L drums, determining which drum among the two 200 L drums inside should serve as the reference is of utmost importance

In order to apply indirect methods (such as scaling factors) to assess the radionuclide inventory of waste generated by nuclear power plants, it is essential to first evaluate the correlation coefficient between key radionuclides and those that are difficult to measure (DTM). The benchmark for the correlation coefficient (r) applied in indirect assessments is set at 0.6, and its significance can vary based on both its value and the size of the dataset. For instance, deriving a correlation coefficient using three data points versus utilizing a dataset with a hundred data points would yield different implications. This study addresses the variance in correlation coefficients based on data selection and presents a methodology for validating the significance of these coefficients. Additionally, we will discuss how these variances may impact the results of indirect assessments, such as scaling factor evaluations.

To effectively assess the inventory of radionuclides generated from nuclear power plants using a consistent evaluation method across diverse groups, it is imperative to analyze the similarity in radioactive distribution between these groups. Various methodologies exist for evaluating this similarity, and the application of statistical approaches allows us to establish similarity at a specific confidence level while accounting for the dataset size (degrees of freedom). Initially, if the variance characteristics of the two groups are similar, a t-test for equal variances can be employed. However, if the variance characteristics differ, methods for unequal variances should be applied. This study delineates the approach for assessing the similarity in radioactive distribution based on the analytical characteristics of the two groups. Furthermore, it delves into the results obtained through two case studies to offer insights into the assessment process.

For the disposal of radioactive waste from nuclear facilities, assessing their radioactivity inventories is essential. As a result, countries with nuclear facilities are implementing assessment schemes tailored to their respective policies and available resources for radioactive waste management. This paper specifically describes the assessment scheme for radioactivity inventory applied to metal waste generated during the dismantling of the Japan Power Demonstration Reactor (JPDR), a 1.25 MW BWR. The distinctive aspect of the Japanese approach lies in the fact that, for a pair of a key nuclide and a difficult-to-measure (DTM) nuclide that lack a significant correlation in their concentrations, the mean activity concentration method was used. In this method, an arithmetic average of all measurements of the DTM nuclide from representative drums, including MDAs (Minimum Detectable Activities), was assigned to the concentration of the DTM nuclide for all drums, regardless of the concentration of its paired key nuclide. Conversely, for a specific pair of a key nuclide and a DTM nuclide with a significant correlation, the scaling factor method was applied, as is common in many other countries. This Japanese case can serve as a valuable reference for Korea, which does not have the option of using the mean activity concentration method in its assessment scheme.

To ensure the long-term supply and sustainability of uranium fuel, exploring alternative resources is essential, particularly considering that terrestrial reserves of uranium are limited (about 4.6 million tons). Since the amount of uranium dissolved in seawater is approximately 1000 times that of terrestrial reserves (i.e., about 4.5 billion tons), uranium extraction from seawater (UES) can be an alternative resource. However, the ultra-low concentration of uranium in seawater (about 3.3 ppb) poses a significant challenge in achieving economic feasibility for UES. This paper introduces case studies on the cost analysis of systems for recovering uranium from seawater, specifically focusing on braided fiber-based adsorbents developed by JAEA and ORNL. The cost analysis has been conducted based on using the deployment of these adsorbents on the bottom of the sea, which is a passive deployment method, thereby reducing the total costs of recovery. The analysis results can be used to identify R&D areas necessary for reducing cost components, making UES economically feasible.

Given the limited terrestrial reserves of uranium (approximately 4.6 million tons), exploring alternative resources is necessary to secure a sustainable, long-term supply of nuclear energy. Uranium extraction from seawater (UES) is a potential solution since the amount of uranium dissolved in seawater (approximately 4.5 billion tons) is about 1,000 times that of terrestrial reserves. However, due to the ultra-low concentration of uranium in seawater (approximately 3.3 ppb), making UES economically viable is a challenging task. In this paper, we explore the potential of using thermal discharge from domestic nuclear power plants for uranium extraction. The motivation for this comes from previous research showing that the adsorption capacity of amidoxime-based adsorbents is proportional to the temperature of the seawater in which they are deployed. Specifically, a study conducted in Japan found that a 10°C increase in seawater temperature resulted in a 1.5-fold increase in adsorption capacity.

To analyze the radioactivity of 3H and 14C in miscellaneous radioactive wastes generated from nuclear power plants, a wet digestion method using sulfuric acid is currently used. However, sulfuric acid is classified as a special management material, and there is no disposal method for contaminated radioactive waste. Therefore, research on a thermal decomposition method that can analyze the DAW radioactive waste samples without using sulfuric acid is necessary. In this study, we will cover the final sample amount, sample injection method, and prevention of organic ignition to meet the minimum detection limit requirements of the analysis equipment. Through this research, optimal conditions for the thermal decomposition method for analyzing the radioactivity of 3H and 14C in DAW radioactive wastes generated from nuclear power plants can be derived.

For the final disposal of radioactive waste, concentration of gamma nuclides such as Co-58, Co-60, Cs-137, Nb-94 have to be determined to meet nuclear regulatory requirements. In general, gamma nuclide analysis can be performed with simple sample pretreatment without complicated chemical separation processes due to the characteristics of the nuclide and high resolution of the measuring equipment. However, when the concentration of Co-60 is high in a specific radioactive waste generated at the NPP, the background is increased by the compton continuum of Co-60. That makes it difficult to evaluate accurately Nb-94, which is in the lower energy band than the gamma ray energy region of Co-60 and especially Cs-137, which is used as a key nuclide of scaling factor. In this study, We consider the problem of MDA dissatisfaction or overestimation due to the increased background by Co-60.

When self-disposing of radioactive waste, it is important to follow the acceptable concentration standards for each nuclide set by the Nuclear Safety and Security Commission (NSSC). Gamma-emitting nuclides can be easily analyzed with a simple pretreatment process, but beta-emitting nuclides require a chemical separation procedure to be analyzed for radiochemistry analysis. When analyzing betaemitting nuclides for the purpose of self-disposal, there may be difficulties in radiation detection after the chemical separation process. This is because the concentration of beta nuclides in the sample may be low and some of them may be lost during the chemical separation. Therefore, measurement method of gross-beta activity can be used instead of that of each nuclide to access the compliance of selfdisposal criteria. While a proportional counter is commonly used to measure gross-beta activity, liquid scintillation counting can also be used to measure gross-beta, and we plan to compare the results of both methods.

To analyze the activity concentration of radionuclides in radioactive sludge samples generated from low- and intermediate-low-level radioactive waste from domestic nuclear power plant, a pretreatment process that dissolves and homogenizes the sample is essential. However, this pretreatment process requires the use of hydrofluoric acid, which makes analysis difficult and challenges users to handle harmful chemicals. Therefore, we aim to minimize the use of hydrofluoric acid by measuring gamma nuclides in the sludge sample without pretreatment process and compare the differences of measurement results according to the sample matrix with and without pretreatment process. We will collect about 0.1 g of the sludge sample, and dissolve it using an acid treatment process after using microwave decomposition. We will then use gamma spectroscopy to check the concentration of nuclides present in the sludge before and after dissolution and consider the effect of the sample matrix.

To develop technology for extracting energy resources from seawater, we first investigated the research experiences of domestic experts. The survey items included the types of adsorbents that can adsorb dissolved resources in seawater, the subjects of experiments, and the scope of research. We divided the types of adsorbents into organic and inorganic categories and compared their adsorption performance. We also examined how adsorption experiments were conducted using simulated solutions and confirmed whether there were any experiences of conducting experiments in actual seawater. A total of 14 domestic research papers on extracting dissolved resources from seawater were reviewed, excluding topics such as removing dissolved resources from seawater and seawater desalination. This review provides an understanding of domestic research trends and will be helpful in setting directions for future research and development.

Seawater containing metals such as lithium and manganese is a “treasure trove” of infinite energy resources. Numerous domestic and foreign institutions are developing technologies to economically extract these resources from seawater. One method for extracting metal ions dissolved in seawater is the development of adsorbents with negative functional groups. Generally, adsorbents have adsorption performance that depends on factors such as seawater pH and temperature, but controlling the pH and temperature of seawater is practically impossible. On the other hand, thermal effluent discharged from power plants tends to be slightly higher in temperature than the surrounding environment. Therefore, this study investigates the potential for utilizing power plant effluent to extract dissolved resources in seawater. Results of investigations into several items related to the effluent from the Gori, Wolsong, Hanbit, and Hanul power plants are presented.

Given the limited terrestrial reserves of uranium (about 4.6 million tons), exploring alternative resources is essential to ensure the long-term supply and sustainability of nuclear energy. Uranium extraction from seawater (UES) is a potential solution to this issue since the amount of uranium dissolved in seawater (about 4.5 billion tons) is approximately 1000 times that of terrestrial reserves. However, the ultra-low concentration of uranium in seawater (about 3.3 ppb) makes it a challenging task to make UES economically feasible. This paper provides an overview of the current status of UES technology, which has evolved over the past seven decades. Starting from inorganic adsorbents such as hydrous titanium oxide in the 1960s, amidoxime-based fibrous adsorbents gained the most attention until the early 2010s due to their ease of deployment in actual seawater conditions and high affinity for uranium. Nowadays, research on organic adsorbents with microstructures is prevailing due to their ability to easily control surface area and compositions. In addition, this study identifies the key issues that need to be addressed to make UES technology economically viable.

Radioactive wastes that are generated as a result of operating NPPs, contain 63Ni and 59Ni that should be analyzed in accordance with the notice of Nuclear Safety and Security Commission (NSSC) for the acceptance of Korea Radioactive Waste Agency (KORAD). Analyzing 63Ni and 59Ni has few challenges to determine activities of each nuclide in radioactive waste sample that contains both nuclides. As is well known, 63Ni can be analyzed by liquid scintillation counter (LSC) detecting its emitted beta rays, however, beta rays emitted from 59Ni are overlapped on the spectrum. Therefore, to discriminate those two nuclides, spectrum channel should be divided according to its dedicating part of the spectrum. For instance, 59Ni contribute to spectrum channel 30–250, on the other hand, 63Ni contributes to spectrum channel 30–450. In other word, 63Ni solely can be analyzed on the channel from 260 to 450. To analyze both 63Ni and 59Ni using this channel division method, detection efficiency must be measured in advance; efficiency of 63Ni and 59Ni at ch. 30–250, and efficiency of 63Ni at ch. 260–450, then the activity can be calculated using the corresponding efficiency. In this study, for verifying the feasibility of channel division method, 5 simulated samples were prepared with different ratio of 63Ni/59Ni. The ratio varies as 1, 2, 10, 20 and 100 spiking standard source of 63Ni and 59Ni. Each sample was mixed with scintillation cocktail and detected for 90 minutes by LSC (300SL, Hidex) after the stabilization of solutions. As a result, calculated 63Ni activities for all sample were averaged as 97% of spiked activity. However, calculated 59Ni activity were 101%, 103%, 128%, 140%, 260%, respectively. The result indicates that 59Ni cannot be discriminated by channel division method when it exists in the sample with high 63Ni over 10 times then 59Ni such as radioactive waste sample. However, the results also show that the channel division method for analyzing 63Ni activity was successful verifying it can determine the activity of 63Ni regardless of the affect of 59Ni on the spectrum.

Radioactivity of radiostrontiums, Sr-89 and Sr-90, which are both pure beta-emitters, are generally measured via Cherenkov counting. However, the determination of Cherenkov counting efficiencies of radiostrontiums requires a complicated procedure due to the presence of Y-90 (also a pure betaemitter) which is the daughter nuclide of Sr-90. In this study, we have developed a machine learning approach using a linear regression model which allows an easier and simultaneous determination of the Cherenkov counting efficiencies of the radiostrontiums. The linear regression model was employed because total net Cherenkov count (Ct) from the three beta-emitters at time t after the separation of Y- 90, can be expressed as a linear combination of their respective time-varying radioactivities with their respective coefficients (parameters) being their counting efficiencies: Ct = εSr-90[ASr-90·exp(–λSr-90·t)] + εSr-89[ASr-89·exp(–λSr-89·t)] + εY-90[ASr-90·exp(1–λSr-90·t)], where ε is a counting efficiency, A is an initial activity, λ is a decay constant and t is time after the separation of Y-90, Thus, if we train the model with multiple Cherenkov counts measured from the three beta emitters, then we can obtain their estimates for counting efficiencies (so-called parameters) straightforward. For this, the model has been trained by two methods: Ordinary Least Squares (OLS) and Bayesian linear regression (BLR), for which two software packages, PyMC3 and Stan were employed to compare their performances. The results showed that the accuracy of the OLS was worse than that of the BLR. Particularly, the counting efficiency of Sr-90 was estimated to be smaller than 0, which is an unrealistic value. On the other hand, the estimates of the BLR gave realistic values which are close to the true values. Additionally, the BLR was able to provide a distribution for each counting efficiency (so-called “posterior”) from which various types of inference can be made including median and credible interval in the Bayesian statistics which is analogous to, but different from confidence interval in the Frequentist statistics. In the results of the BLR, the Stan package gave more accurate estimates than the PyMC3 package. Therefore, it is expected that counting efficiencies of the radiostrontiums including radioyttrium can be determined at the same time, more easily and accurately, by using the BLR with the Stan package and that the activities of radiostrontium also can be determined more easily by using the BLR if we know their counting efficiencies in advance. It is worth noting that the usage of the linear regression model in this study was different from the usual one where the trained model is used to predict a response value (count) from a set of unseen regressor values (activities).