As nuclear decommissioning ventures become increasingly complex, the role of digitalization in facilitating and enhancing these operations is becoming indispensable. This transition to a more digitized approach presents a myriad of advantages, including: augmented avenues for data acquisition, analysis, and visualization to bolster dismantling strategies; simulations in virtual environments for operator training; precise forecasting of future waste emergence, culminating in refined cost estimations; and more immersive decommissioning visualizations for both operators and external stakeholders. Salient benefits conferred by the integration of digital technologies in decommissioning encompass improved collaboration, enriched knowledge transfer, clarity regarding present technological constraints, insights into key influencing factors, clearer criteria for technology selection, and a profound understanding of the potential challenges and merits of a broader incorporation of digital tools in decommissioning endeavors. Of paramount importance is the opportunity presented for superior workforce training and safety measures, exemplified by ALARAbased planning. Amidst the myriad facets of digital adoption, 3D modeling of nuclear facilities derived from laser-scanned point clouds stands out as a pivotal domain in the digitalization. The transformation of intricate point cloud data into a comprehensible 3D mesh remains the crux of this paper. The process of mesh generation, despite being simpler than its counterpart of converting to a 3D solid model, is crucial for multiple reasons. The resultant 3D mesh offers an enhanced visual representation compared to a sparse point cloud, paving the way for improved spatial perception. Furthermore, it serves as a rudimentary tool for approximating component volumes and the ensuing waste, thereby playing an instrumental role in waste manipulation strategies, notably in collision detection. This paper delves deep into the nuances of mesh generation, conducting an parametric study of mesh conversion algorithms, including down-sampling rates. Through this rigorous examination, we endeavor to shed light on optimal methodologies, hoping to catalyze advancements in the digitalization of nuclear decommissioning processes.

The operation of nuclear facilities involves the potential for on-site contamination of soil, primarily resulting from pipe leaks and other operational incidents. Globally, decommissioning process for commercial nuclear power plants have revealed huge-amounts of soil waste contaminated with Cs-137, Sr-90, Co-60, and H-3. For example, Connecticut Yankee in the United States produced approximately 52,800 ton of contaminated soil waste, constituting 10% of the total waste generated during its decommissioning. Environmental remediation costs associated with nuclear decommissioning in the US averaged $60 million per unit, representing a significant 10% of the whole decommissioning expenses. Consequently, this study undertook a preliminary investigation to identify important factors for establishing a site remediation strategy based on radionuclide- and site-specific media- characteristics, focusing the efficiency enhancement for the environmental remediation. The factors considered for this investigation were categorized into physical/environmental, socioeconomic, technical, and management aspects. Physical/environmental factors contained the site characteristics, contamination levels, and environmental sensitivity, while socio-economic factors included the social concerns and economic costs. Technical and management factors included subcategories such as technical considerations, policy aspects, and management factors. Especially, technical factors were further subdivided to consider the site reuse potential, secondary waste generation by site remediation, remediation efficiency, and remediation time. Additionally, our study focused the key factors that facilitate the systematic planning for the site remediation, considering the distribution coefficient (Kd) and hydrogeological characteristics associated with each radionuclide in specific site conditions. Therefore, key factors in this study focus the geochemical characteristics of site media including the particle size distribution, chemical composition, organic and inorganic constituents, and soil moisture content. Moreover, the adsorption properties of site media were examined concerning the distribution coefficient (Kd) of radionuclides and their migration characteristics. Furthermore, this study supported the development of a conceptual framework, containing the remediation strategies that incorporate the mobility of radionuclides, according to the site-specific media. This conceptual framework would necessitate the spatial analysis techniques involving the whole contamination surveys and radionuclide mobility modeling data. By integrating these key factors, the study provides the selection and simulation of optimal remediation methods, ultimately offering the estimated amounts of radioactive waste and its disposal costs. Therefore, these key factors offer foundational insights for designing the site remediation strategies according the sitespecific information such as the distribution coefficient (Kd) and hydrogeological characteristics.

The site used for a nuclear facility can be released after decommissioning if the results of dose estimation meet the regulatory requirements and the site release is approved by the regulatory body. RESRAD-ONSITE, developed by the Argonne National Laboratory, is a computer code used to estimate the dose to the residents on radiologically contaminated sites. The dose estimation for site release should consider various exposure pathways, including inhalation, ingestion, and external exposure. This study used RESRAD-ONSITE to evaluate the internal exposure dose and identify radionuclides due to the intake of food produced on radiologically contaminated sites. The upper limit of the clearance level of radionuclides expected to remain at the site was used as the source terms for the dose evaluation. In addition, the amount of food intake per capita was obtained from eight countries using nuclear power generation as of 2020. The default values of RESRAD were used for other parameters except for intake by type of food and source terms. As a result of the dose evaluation, the contaminated water and vegetables showed a great contribution to the exposure dose. The dose due to tritium in drinking water was highest in the third year. In addition, regarding the intake of vegetables, the internal exposure due to 90Sr was the highest in the first year.

The effects of an individual effective dose from radioactive contamination that will remain during site reuse after the decommissioning of nuclear facilities is generally assessed using the RESRAD code. The calculated results should meet the site reuse criteria presented by regulators, 0.25 mSv/yr in the United States and 0.1 mSv/yr in Korea. After completion of decommissioning, the dose is not subject to measurement, resulting in Derived Concentration Guideline Level (DCGL) remaining at the site that is practically consistent with the dose criteria. In order to assess dose using the RESRAD code, various requirements will need to be considered and determined, where the selection of input parameters is one of the important factors in the dose assessment. In addition, appropriate selection of site-specific parameters is important to reflect the site characteristics of each decommissioned Nuclear Power Plant (NPP). Therefore, this study intends to analyze the impact of site-specific parameters by referring to the cases of overseas decommissioned NPPs. In order to evaluate doses using RESRAD code, a site reuse scenario must first be selected. In general, in the case of unrestricted reuse, the resident farmer scenario can be applied, so the resident farmer scenario was also selected in this study. In addition, once a resident farmer scenario is selected, input parameters are selected according to the scenario, and the input parameter inputs a single value or distribution according to the deterministic or probabilistic evaluation method. Therefore, since this study is to evaluate the effect on site-specific parameters, a single value was applied as a deterministic evaluation method. For the 10 site-specific parameters considered in overseas cases, the difference was set twice using the F9 function key in the RESRAD code and the results were analyzed. In this study, we used prior research data targeting domestic nuclear facility for sensitivity analysis. Related parameters include the category of contamination layer, soil, water transport, ingestion, and occupancy. The parameters that appeared as the greatest influence among the 10 parameters were different in radionuclide on the contaminated zone. We showed the changes according to the difference in input parameters was presented using the graph provided by the RESRAD code. As a result, in the evaluation for Co-60 in this study, no significant change was observed. However, in case of H-3, several parameters values were changed, indicating that the effect on dose will be different depending on the site characteristics of the nuclear facilities.

The decommissioning of Korea’s nuclear power facilities is expected to take place starting with the Kori Unit 1 followed by the Wolsong Unit 1. In Korea, since there is no experience of decommissioning, considerations of site selection for the waste treatment facilities and reasonable selection methods will be needed. Only when factors to be considered for construction are properly selected and their effects are properly analyzed, it will be possible to operate a treatment facility suitable for future decommissioning projects. Therefore, this study aims to derive factors to be considered for the site selection of treatment facilities and present a reasonable selection methodology through evaluation of these factors. In order to select a site for waste treatment facilities, three virtual locations were applied in this study: warehouse 1 to warehouse 3. Such a virtual warehouse could be regarded as a site for construction warehouses, material warehouses, annexed building sites, and parking lots in nuclear facilities. If the selection of preliminary sites was made in the draft, then it is necessary to select the influencing factors for these sites. The site of the treatment facility shall be suitable for the transfer of the waste from the place where the dismantling waste is generated to the treatment facility. In addition, in order for construction to take place, interference with existing facilities and safety should not be affected, and it should not be complicated or narrow during construction. Considering the foundation and accessibility, the construction of the facility should be economical, and the final dismantling of the facility should also be easy. In order to determine one final preferred plan with three hypothetical locations and five influencing factors, there will be complex aspects and it will be difficult to maintain consistency as the evaluation between each factor progresses. Therefore, we introduce the Analytic Hierarchical Process (AHP) methodology to perform pairwise comparison between factors to derive an optimal plan. One optimal plan was selected by evaluating the three virtual places and five factors of consideration presented in this study. Given the complexity and consistency of multiple influencing factors present and prioritizing them, AHP tools help users make decisions easier by providing simple and useful features. Above all, it will be most important to secure sufficient grounds for pairwise comparison between influencing factors and conduct an evaluation based on this.

The Kori Unit 1 and Wolsong Units 1, commercial reactors in South Korea, were permanently shut down due to the expiration of their design lifetime. Therefore, nuclear power plants that have been permanently shut down must be dismantled, and the site must be finally released after removing the remaining radionuclides. Domestic regulatory standards for site remediation should not exceed 0.1 mSv per year based on effective dose. In addition, it is necessary to calculate the preliminary Derived Concentration Guideline Levels (DCGL) to prove that the conditions are met. Therefore, in this study, the input factor considering the geological characteristics of the site of Kori Unit 1 was investigated, and the preliminary Derived Concentration Guideline Levels were calculated and compared with the results of previous studies. As a result of comparative analysis, 60Co, 134Cs, and 137Cs, which are gamma-ray emitting radionuclides, had similar values to DCGL of previous studies A and B. However, 63Ni, a beta-rayemitting nuclide, was 5.94×104 Bq·g−1 in this study and 8.47×101 Bq·g−1in previous study B, resulting in a difference of about 700 times. In addition, in the case of 90Sr, this study and previous study A were derived similarly, but this study was 5.34×101 Bq·g−1 and previous study B was 1.18×10−1 Bq·g−1, resulting in a difference of about 450 times. This difference is judged to be because, unlike this study using only the industrial worker scenario, in the case of previous study B, the resident farmer scenario was mixed and used, which considers the internal exposure caused by ingestion of food produced in the contaminated area. In this study, it was confirmed that DCGL according to the change of geological factors of the site did not have a significant effect on gamma-ray-emitting nuclides. However, it was confirmed that considering the intake of food affects the DCGL of beta-ray-emitting nuclides. Therefore, there is a need to conduct future studies applying intake input factors that meet domestic conditions.

It is important to ensure worker’s safety from radiation hazard in decommissioning site. Real-time tracking of worker’s location is one of the factors necessary to detect radiation hazard in advance. In this study, the integrated algorithm for worker tracking has been developed to ensure the safety of workers. There are three essential techniques needed to track worker’s location, which are object detection, object tracking, and estimating location (stereo vision). Above all, object detection performance is most important factor in this study because the performance of tracking and estimating location is depended on worker detection level. YOLO (You Only Look Once version 5) model capable of real-time object detection was applied for worker detection. Among the various YOLO models, a model specialized for person detection was considered to maximize performance. This model showed good performance for distinguishing and detecting workers in various occlusion situations that are difficult to detect correctly. Deep SORT (Simple Online and Realtime Tracking) algorithm which uses deep learning technique has been considered for object tracking. Deep SORT is an algorithm that supplements the existing SORT method by utilizing the appearance information based on deep learning. It showed good tracking performance in the various occlusion situations. The last step is to estimate worker’s location (x-y-z coordinates). The stereo vision technique has been considered to estimate location. It predicts xyz location using two images obtained from stereo camera like human eyes. Two images are obtained from stereo camera and these images are rectified based on camera calibration information in the integrated algorithm. And then workers are detected from the two rectified images and the Deep SORT tracks workers based on worker’s position and appearance between previous frames and current frames. Two points of workers having same ID in two rectified images give xzy information by calculating depth estimation of stereo vision. The integrated algorithm developed in this study showed sufficient possibility to track workers in real time. It also showed fast speed to enable real-time application, showing about 0.08 sec per two frames to detect workers on a laptop with high-performance GPU (RTX 3080 laptop version). Therefore, it is expected that this algorithm can be sufficiently used to track workers in real decommissioning site by performing additional parameter optimization.

Large amounts of concrete waste are likely to arise from the decommissioning of a Kori-1 nuclear power plant. Several studies have been conducted on decommissioning concrete waste in recent decades, however, they have been limited to contaminated concrete issues or were small pilot-scale experiments. This study constructed two industrial-scale models of on-site concrete waste management for clean as well as contaminated concrete. To evaluate the performance of both the models, simulations were conducted using the Flexsim software. The concrete particle size distribution of Kori-1 and concrete processor properties based on widely used construction equipment were used as sources of input data for the simulations. It was observed that it may take over two years to complete the on-site concrete management processes owing to the performance of existing processors. In addition, it was demonstrated that it is essential to identify bottlenecks in the system and enhance the performance of the relevant processors to avoid delays of the decommissioning schedule. Our results suggest that this novel approach can contribute to developing schedules or expediting delayed activities in the Kori-1 decommissioning project.