본 연구는 Fuzzy-Delphi법과 DEMATEL-ANP법으로 경관평가 모형을 구축한 뒤 하북성 형태시 소재 칠리하(七裏河)를 사례로 실증 분석한 결과이다. Delphi법에 따른 1차 설문지를 이용하여 최초 54개 지표를 40개 지표로 줄인 후 전문가 Fuzzy-Delphi법에 따른 2차 설문지 및 데이터 처리 결과 모든 평가 지표는 수렴기준에 도달하였다. 평가지표 중간값이 임계값보다 낮은 지표를 삭제한 뒤 최종적으로 22개 지표를 중심으로 도시 하천 호안지역 경관 평가체계를 구성하였다. 도출된 모델은 치수, 친수, 이수, 보수 등 4개 방면의 기능분류이며, 다시 기능적 측면, 안전성 측면, 경관적 측면, 생태적 측면, 사 회경제적 측면 등 5가지 기준으로 유형화되었다. 평가지표 중 영향력이 큰 상위 5개 요인은 수역경관 (C11), 건설투자(C19), 식물피복률(C16), 호안의 친수성(C10), 시각적 조화(C9) 순이었다. 그러나 인문 경관의 다양성(C12)요인의 가중치가 최하위임을 볼 때 도시 하천의 호안경관과 인문경관은 거의 배 제된 상태이며, 자연경관과 수역경관의 상호작용에 더 많은 관심을 기울이고 있음이 확인되었다. 한편 도시 경관평가 체계에서 5개 준칙층의 순서는 경관 미학성> 생태성 > 사회경제성 > 기능성 > 안 전성 순으로 나타났는데 이는 도시 내 수로의 호안 지역 경관의 전체적인 경관 감지와 흡인력을 반영 한 결과로 평가되었다. 칠리하 호안구역의 종합적 경관 평가치는 70.93점으로 만족스러운 수준이지 만 익수사고에 대비한 구조시설(C6) 인문경관의 다양성(C12) 그리고 역사문화 풍습의 구현(C22) 항 목에 있어서는 시급한 개선이 필요한 것으로 밝혀졌다.

The Severe Disaster Punishment Act had recently been established in order to promote safety and health (OSH) management system for severe accident prevention. OSH management system is primarily designed based on risk assessments; however, companies in industries have been experiencing difficulties in hazard identification and selecting proper measures for risk assessments and accident prevention. This study intended to introduce an accident analysis method based on epidemiological model in finding hazard and preventive measures. The accident analysis method employed in this study was proposed by the U.S. Department of Energy. To demonstrate the effectiveness of the accident analysis method, this study applied it to two accident cases occurred in construction and manufacturing industries. The application process and results of this study can be utilized in improving OSH management system and preventing severe accidents.

PURPOSES : This study aims to analyze the efficiency of the safety and management of private highways. METHODS : Variables were selected based on the data and performance related to the safety of 18 private highways. The appropriateness of operations management was reviewed using Data Envelopment Analysis (DEA) analysis. Items with a scope for improvement were reviewed and adjustment measures were presented. RESULTS : To increase safety management efficiency, the degree of reduction in personnel and operating expenses was presented based on the relative efficiency group. CONCLUSIONS : It is necessary to adjust the appropriate management organization and operating costs according to the characteristics of each route. Moreover, the limitations of the study and possible improvements were presented.

PURPOSES : This study aims to conduct a sensitivity analysis to determine the major factors affecting traffic accidents involving elderly pedestrians. METHODS : In this study, a regression tree model was built based on a non-parametric statistical model using data on traffic accidents involving elderly pedestrians. Using this model, we analyzed the degree of change in the probability of pedestrian fatalities. RESULTS : Results of the model analysis show that the first major factor combination affecting traffic accidents involving elderly pedestrians is speeding, night time, and road markers. The second combination is night time and arterial roads (national and local highways). The last combination that may lead to such accidents is heavy vehicles and federally funded local highways. CONCLUSIONS : Preventive measures, such as speed control, proper lighting, median strips, designation of pedestrian protection zones, and guidance of detours, are necessary to manage high-risk combinations causing accidents of the elderly.

PURPOSES : During the summer of 2018, a heat wave (temperatures > 33°C) lasted for more than 30 days, causing blow-ups at eight different locations in South Korea. The blow-up phenomenon occurred when the internal temperature of the concrete slab increased. Simultaneously, as the concrete slab expands excessively, the length of the end of the slab increases, thus resulting in a lateral compressive force; when the slab cannot withstand this force, it rises or breaks. Blow-up is caused by a variety of factors, including increased temperature and humidity, accumulation of incompressible substances inside discontinuous surfaces, alkali–silica reactions, and aging of the concrete pavement. Several researchers have presented models to forecast blow-ups, such as the A. D. Kerr and G. Yang models, which have been applied to explain the blow-up phenomenon. However, this model has some limitations. This paper discusses a method to overcome these limitations. METHODS : Buckling, the most important theory describing the blow-up phenomenon, was reviewed, and the buckling principle was confirmed. Subsequently, the input variables of the Kerr and Yang models and the mechanism for predicting the occurrence of blow-ups were identified. The PGBA program was used to confirm the lifetime of the expansion joint and the blow-up occurrence time based on the expansion joint spacing to review the limitations of the two studied models. RESULTS : The Kerr and Yang models did not consider variables such as the expansion joint spacing or length of the integrated adjacent slab. In other words, it is necessary to reconsider the appropriateness of blow-up time predictions in relation to changes in expansion joint spacing and slab length. The expansion joint lifetime and blow-up occurrence time were predicted using the PGBA program. It was confirmed that as the expansion joint spacing increases, the expansion joint lifetime decreases. However, the blow-up occurrence time was shown to be the same (equal to 59 years), which is a limitation of the Kerr and Yang models used in the PGBA program. This resulted in a limitation in which variables for the expansion joint spacing cannot be used. CONCLUSIONS : Through blow-up simulation experiments and actual field data, an appropriate slab length should be determined, and a blow-up model should be developed based on the slab length. If a blow-up prediction based on concrete slab length and a blow-up model based on are developed, the blow-up prevention technology will be applied to the appropriate blow-up time and location to avoid traffic accidents and reduce human and property damage.

The organic complexing agents such as ethylenediaminetetraacetic acid (EDTA), nitrilotriacetic acid (NTA), and isosaccharinic acid (ISA) can enhance the radionuclides’ solubility and have the potential to induce the acceleration of radionuclides’ mobility to a far-field from the radioactive waste repository. Hence, it is essential to evaluate the effect of organic complexing agents on radionuclide solubility through experimental analysis under similar conditions to those at the radioactive waste disposal site. In this study, five radionuclides (cesium, cobalt, strontium, iodine, and uranium) and three organic complexing agents (EDTA, NTA, and ISA) were selected as model substances. To simulate environmental conditions, the groundwater was collected near the repository and applied for solubility experiments. The solubility experiments were carried out under various ranges of pHs (7, 9, 11, and 13), temperatures (10°C, 20°C, and 40°C), and concentrations of organic complexing agents (0, 10-5, 10-4, 10-3, and 10-2 M). Experimental results showed that the presence of organic complexing agents significantly increased the solubility of the radionuclides. Cobalt and strontium had high solubility enhancement factors, even at low concentrations of organic complexing agents. We also developed a support vector machine (SVM) model using some of the experimental data and validated it using the rest of the solubility data. The root mean square error (RMSE) in the training and validation sets was 0.012 and 0.016, respectively. The SVM model allowed us to estimate the solubility value under untested conditions (e.g., pH 12, temperature 30°C, ISA 5×10-4 M). Therefore, our experimental solubility data and the SVM model can be used to predict radionuclide solubility and solubility enhancement by organic complexing agents under various conditions.

Radioactive wastes, including used nuclear fuel and decommissioning wastes, have been treated using molten salts. Electrochemical sensors are one of the options for in-situ process monitoring using molten salts. However, in order to use electrochemical sensors in molten salt, the surface area must be known. This is because the surface area affects the current of the electrode. Previous studies have used a variety of methods to determine the electrode surface area in molten salts. One method of calculating the electrode surface area is to use the reduction current peak difference between electrodes with known length differences. The method is based on the reduction peak and has the benefit of providing long-term in-situ monitoring of surfaces immersed in molten salt. A number of assumptions have been made regarding this method, including that there is no mass transport by migration or convection; the reaction is reversible and limited by diffusion; the chemical activity of the deposit should be unity; and species should follow linear diffusion. For the purpose of overcoming these limitations, a variety of machine learning algorithms were applied to different voltammogram datasets in order to calculate the surface area. Voltammogram datasets were collected from multiarray electrodes, comprising a multiarray holder, two tungsten rods (1 mm diameter) working electrodes, a quasi-reference electrode, and a counter electrode. The multiarray electrode holder was connected to the auto vertical translator, which uses a servo motor, for changing the height of the rod in the molten salts. To make big and diverse data for training machine learning models, various concentrations of corrosion products (Cr, Fe) and fission products (Eu, Sm) in NaCl-MgCl2 eutectic salts were used as electrolyte; electrolyte temperatures were 500, 525, 550, 575, and 600°C. This study will demonstrate the potential of utilizing machine learning based electrochemical in situ monitoring in molten salt processing.

In the event of a radioactive release, it is essential to quickly detect and locate the source of the release, as well as track the movement of the plume to assess the potential impact on public health and safety. Fixed monitoring posts are limited in their ability to provide a complete picture of the radiation distribution, and the information they provide may not be available in real-time. This is why other types of monitoring systems, such as mobile monitoring, aerial monitoring, and personal dosimeters, are also used in emergency situations to complement the information provided by fixed monitoring posts. Also, the monitoring system can be improved by using the Kriging technique, which is one of the interpolation methods, to predict the radiation dose in the relevant districts. This can be achieved by utilizing both the GPS information and the radiation dose measured at a particular point. The Kriging method involves estimating the value between different measurement points by considering the distance between them. The model used GPS and radiation data that were measured around the Hanbit NPP. The data were collected using a radiation measuring detector on a bus that traveled around the NPP area at 2-second intervals for one day. From the collected data, 200 data points were randomly selected for analysis, excluding the data measured at the bus garage out of a total of 16,550 data points. The average dose of the daily measurement data was 117.94 nSv/h, and the average dose of the 200 randomly extracted data was 119.17 nSv/h. The GPS and radiation dose data were utilized to predict the radiation dose around the Yeonggwang area where the Hanbit NPP is located. In the event of an abnormal release of radioactive material, it can be difficult to accurately determine the dose unless a monitoring measurement point is present. This can delay the rapid evacuation of residents during an emergency situation. By utilizing the Kriging model to make predictions, it is anticipated that more accurate dose predictions can be generated, particularly during accident scenarios. This can aid in the development of appropriate resident protection measures.

In this study, we evaluate artificial neural network (ANN) models that estimate the positions of gamma-ray sources from plastic scintillating fiber (PSF)-based radiation detection systems using different filtering ratios. The PSF-based radiation detection system consists of a single-stranded PSF, two photomultiplier tubes (PMTs) that transform the scintillation signals into electric signals, amplifiers, and a data acquisition system (DAQ). The source used to evaluate the system is Cs-137, with a photopeak of 662 keV and a dose rate of about 5 μSv/h. We construct ANN models with the same structure but different training data. For the training data, we selected a measurement time of 1 minute to secure a sufficient number of data points. Conversely, we chose a measurement time of 10 seconds for extracting time-difference data from the primary data, followed by filtering. During the filtering process, we identified the peak heights of the gaussian-fitted curves obtained from the histogram of the time-difference data, and extracted the data located above the height which is equal to the peak height multiplied by a predetermined percentage. We used percentage values of 0, 20, 40, and 60 for the filtering. The results indicate that the filtering has an effect on the position estimation error, which we define as the absolute value of the difference between the estimated source position and the actual source position. The estimation of the ANN model trained with raw data for the training data shows a total average error of 1.391 m, while the ANN model trained with 20%-filtered data for the training data shows a total average error of 0.263 m. Similarly, the 40%-filtered data result shows a total average error of 0.119 m, and the 60%-filtered data result shows a total average error of 0.0452 m. From the perspective of the total average error, it is clear that the more data are filtered, the more accurate the result is. Further study will be conducted to optimize the filtering ratio for the system and measuring time by evaluating stabilization time for position estimation of the source.

RUCAS (Recycling-Underlying Computational Dose Assessment System), a dose assessment program based on the RESRAD-RECYCLE framework, is designed to evaluate dose for recycling scenarios of radioactive waste in metals and concrete. To confirm the validity of the recycling scenarios provided by RUCAS, comparative evaluations will be conducted with RESRAD-RECYCLE for metal radioactive waste recycling scenarios and with MicroShield® for concrete radioactive waste recycling scenarios. In the evaluation of metal recycling scenarios without shielding, RUCAS showed similar results when compared to both MicroShield® and RESRAD-RECYCLE. This validates the function of dose assessments using RUCAS for metal recycling scenarios. However, when shielding was present, RUCAS produced results that were comparable to MicroShield®, but differed from those of RESRAD-RECYCLE. The underestimation of dose values up to 1.66E+08 times difference by RESRAD-RECYCLE could potentially decrease reliability and safety in evaluated doses, further emphasizing the importance of RUCAS. Because validation is also necessary for the expanded calculation capabilities resulting from methodological changes of RUCAS (i.e., various radiation source geometries), based on prior validations, it was determined that additional validations are required for different radiation source materials and shielding conditions. In case where the radiation source and shielding materials were identical, RUCAS and MicroShield® produced similar results according to both the Kalos et al. (1974) and Lin and Jiang (1996) methodologies. This demonstrates that the that differences in methodology are inconsequential when considering the same source and shielding materials. However, when the atomic number of the radiation source materials was larger than that of shielding material (HZ-LZ condition), RUCAS obtained results similar to MicroShield® only for the Kalos et al. (1974) methodology. While Lin and Jiang (1996) methodology yield higher results than MicroShield®. Lastly, in case where the atomic number of the radiation source material was smaller than that of the shielding material (LZ-HZ condition,) both methodologies yielded results comparable to MicroShield®. In conclusion, the validity of RUCAS’s shielding calculations has been verified, confirming improvements in dose assessment compared to RESRAD-RECYCLE. Additionally, we observed that shielding effectiveness calculations differ depending on the methodology of build-up effect. If the validity of these methodologies is confirmed, it is expected that selecting the most advantageous methodology for each condition will enable more rational dose assessments. Consequently, in future research, we plan to evaluate the validity of Lin and Jiang (1996) methodology using particle transport codes based on the Monte Carlo method, such as MCNP and Geant 4, rather than MicroShield®.

LILW disposal repository in Gyeongju, South Korea is considered with a concrete mixture that uses Ordinary Portland Cement (OPC) partially substituted with supplementary cementitious materials (SCMs). The degradation of cementitious materials that result from chemical and physical attacks is a major concern in the safety of radioactive waste disposal. We present a reactive transport model utilized as one of the geochemical simulation approaches for the timescales of concern that range from hundreds to thousands of years. The purpose of this study is to investigate the sensitivity of parameters in concrete disposal systems and to evaluate the influence of various assumptions on the chemical degradation of the systems using a reactive transport model. A reactive transport model in the concrete disposal vault was developed to evaluate the behavior of engineered barriers composed of cementitious materials. The sensitivity analysis was performed using reactive transport models through the coupling between COMSOL and PHREEQC. The databases selected for the analysis are the Thermochimie database presented by ANDRA. Among many variables considered, two variables that can highly affect chemical degradation were selected for detailed sensitivity analysis for dealing with uncertainties. This is important because the chemical degradation mechanism is generally sensitive to precipitation and diffusion coefficient. The first factor is precipitation, which might be the most important factor in chemical degradation because it acts as a calcium leaching of cementitious materials in a disposal system in a highly alkaline environment, increasing the porosity of the system. To predict the change in annual precipitation, the measurement of the precipitation observatory station in the nearest area of Gyeongju for the past 80 years was collected. The second factor is the diffusion coefficient, which plays an essential role in the durability of the concrete disposal system, promoting the decalcification of cementitious minerals, accelerating system degradation, and increasing the porosity of its system, thereby facilitating the migration of radionuclides. The diffusion coefficient values used in studies similar to this work were calculated and evaluated using the box-and-whisker method. The results of the sensitivity analyses for the reactive transport model in the concrete disposal system will be presented. The sensitivity cases show that the results obtained are much more sensitive to changes in transport parameters.

Bentonite is a widely used buffer material in high-level radioactive waste repositories due to its favorable properties, including its ability to swell and low permeability. Bentonite buffers play an important role in safe disposal by providing a low permeability barrier and preventing radionuclides migration into the surrounding rock. However, the long-term performance of the bentonite buffer is still an area of research, and one of the main concerns is the erosion of the buffer due to swelling and groundwater flow. Erosion of the bentonite buffer can have a significant impact on repository safety by reducing the integrity of the buffer and forming colloids that can transport radionuclides through groundwater, potentially increasing the risk of radionuclide migration. Therefore, understanding the mechanisms and factors that influence the erosion of the bentonite buffer is critical to the safety assessment of high-level radioactive waste repositories. In this study, we attempted to develop the bentonite buffer erosion model using Adaptive Processbased total system performance assessment framework for a geological disposal system (APro) proposed by the Korea Atomic Energy Research Institute (KAERI). First, the erosion phenomenon was divided into two stages: bentonite buffer penetration into rock fractures and colloid formation. As an initial step in the development of the buffer erosion model, a bentonite buffer intrusion into the fracture and consequent degradation of buffer property were considered. For this purpose, a tworegion model based on the dynamic bentonite diffusion model was adopted which is one of the methods for simulating bentonite buffer intrusion. And, it was assumed that the buffer properties, such as density, porosity and permeability, thermal conductivity, modulus of elasticity, and mechanical strength, are degraded as the buffer erodes. The bentonite buffer degradation model developed in this study will serve as a foundation for the comprehensive buffer erosion model, in conjunction with the colloidal formation model in the future.

With the recent concern regarding cellulose enhancing radionuclide mobility upon its degradation to ISA, disposal of cellulosic wastes is being held off until the disposal safety is vindicated. Thus, a rational assessment should be conducted, applying an appropriate cellulose degradation model considering the disposal environment and cellulose degradation mechanisms. In this paper cellulose degradation mechanisms and the disposal environment are studied to propose the best-suitable cellulose degradation model for the domestic 1st phase repository. For the cellulose to readily degrade, the pH should be greater than 12.5. As in the case of SKB, 1BLA is excluded from the safety assessment because the pH of 1BLA remains below 12.5. Furthermore, despite cellulose degradation occurring, it does not always produce ISA. At low Ca2+ concentration, the ISA yield rate is around 25%, but at high Ca2+ concentration, the ISA yield rate increases up to 90%. Thus, for the cellulose to be a major concern, both pH and Ca2+ concentration conditions must be satisfied. To satisfy both conditions, the cement hydration must be in 2nd phase, when the porewater pH remains around 12.5 and a significant amount of Ca2+ ion is leaching out from the cement. However, according to the safety evaluation and domestic research, 2nd phase of cement hydration for silo concrete would achieve a pH of around 12.4, dissatisfying cellulose degradation condition like in 1BLA. Thus, cellulose degradation would be unlikely to occur in the domestic 1st phase repository. To derive waste acceptance criteria, a quantitative evaluation should be conducted, conservatively assuming cellulose is degraded. To conduct a safety evaluation, an appropriate degradation model should be applied to determine the degradation rate of cellulose. According to overseas research, despite the mid-chain scission being yet to be seen in the experiments, the degradation model considering mid-chain scission is applied, resulting in an almost 100% degradation rate. The model is selected because the repositories are backfilled with cement, achieving a pH greater than 13, so extensive degradation is reasonably conservative. However, under the domestic disposal condition, where cellulose degradation is unlikely to occur, applying such model would be excessively conservative. Thus, the peeling and stopping model derived by Van Loon and Haas, which suggests 10~25% degradation rate, is reasonably conservative. Based on this model, cellulose would not be a major concern in the domestic 1st phase repository. In the future, this study could be used as fundamental data for planning waste acceptance criteria.

For the performance analysis of deep geological repository systems, numerical simulation with multi-physics is required, which specifically covers Thermal (T), Hydraulic (H), and Mechanical (M) behaviors in the disposal environment. Numerous simulation models have been developed so far, each of which varies in the approach and methodology for solving THM problems. Fully-coupled THM simulation codes such as ROCMAS, THAMES, and CODE_BRIGHT were mainly developed in the initial stage of DEvelopment of COupled models and their VALidation against EXperiments (DECOVALEX), with the advantage of thorough calculations consisting of correlated several variables on different physics. Due to the difficulty of solving the complex Jacobian Matrix and the following burden for the computational calculation, weakly-coupled THM models have been suggested in recent researches: TOUGH2-MP with FLAC3D, TOUGH2 with UDEC and OpenGeoSys with FLAC3D. This methodology of loose coupling allows the practical use of computational code optimized for each physics, thereby increasing the efficiency in simulation. However, these suggested models require two different numerical codes to calculate THM behaviors, which leads to several inherent issues: compatibility during maintenance, updating and dependency between two codes. In this study, therefore, the authors build a unified code for simulating THM behaviors in the deep geological repository. The concept involves the iterative sequential coupling between TH and M for calculation efficiency. As having developed the simulation code, High-level rAdiowaste Disposal Evaluation System (HADES), to describe TH behavior based on Multi-physics Object-Oriented Simulation Environment (MOOSE) software, the authors make a milestone to develop and couple the MOOSE-based new code for M behavior as Sub-app, with the previous HADES set to be Main-app. New model for M behavior will be verified with the benchmark case of DECOVALEX-THMC Task D, comparing the mechanical simulation results: stress evolution over time, profiles of stress and vertical displacement. The existing simulation results from HADES will also be updated with the coupled calculations, with regard to temperature and saturation. Additionally, the effective stress evolution can be assessed in terms of repository’s stability with Spalling Strength and Mohr-Coulomb failure criterion. This concept for new simulation model has its meaning in that it aims to demonstrate the specific methodology of loosely coupling multi-physics in unified simulation code and analyze THM complex interactions with considering mutual influence on various physics. It is expected that HADES can be renewed as an integral simulation model for deep geological repository systems by possessing the capacity for analyzing and assessing mechanical behavior.

The Korean Nuclear Safety and Security Commission has established a general guideline for the disposal of high-level waste, which requires that radiological effects from a disposal facility should not exceed the regulatory safety indicator, a radiological risk. The post-closure safety assessment of the disposal facility aims to evaluate the radiological dose against a representative person, taking into account nuclide transport and exposure pathways and their corresponding probabilities. The biosphere is a critical component of radiation protection in a disposal system, and the biosphere model is concerned with nuclide transport through the surface medium and the doses to human beings due to the contaminated surface environment. In past studies by the Korea Atomic Energy Research Institute (KAERI), the biosphere model was constructed using a representative illustration of surface topographies and groundwater conditions, assuming that the representative surface environment would not change in the future. Each topography was conceptualized as a single compartment, and distributed surface contamination over the geometrical domain was abstracted into 0D. As a result, the existing biosphere model had limitations, such as a lack of quantitative descriptions of various transport and exposure pathways, and an inability to consider the evolution of the surface environment over time. These limitations hinder the accurate evaluation of radiological dose in the safety assessment. To overcome these limitations, recent developments in biosphere modeling have incorporated the nuclide transport process over a 2D or 3D domain, integrating the time-dependent evolution of the surface environment. In this study, we reviewed the methodology for biosphere modeling to assess the radiological dose given by distributed surface contamination over a 2D domain. Based on this review, we discussed the model requirements for a numerical module for biosphere dose assessment that will be implemented in the APro platform, a performance assessment tool being developed by the KAERI. Finally, we proposed a conceptual model for the numerical module of dose assessment.

The deep geologic repository (DGR) concept is widely accepted as the most feasible option for the final disposal of spent nuclear fuels. In this concept, a series of engineered and natural barrier systems are combined to safely store spent nuclear fuel and to isolate it from the biosphere for a practically indefinite period of time. Due to the extremely long lifetime of the DGR, the performance of the DGR replies especially on the natural geologic barriers. Assessing the safety of the DGR is thus required to evaluate the impacts of a wide range of geological, hydrogeological, and physicochemical processes including rare geological events as well as present water cycles and deep groundwater flow systems. Due to the time scale and the complexity of the physicochemical processes and geologic media involved, the numerical models used for safety evaluation need to be comprehensive, robust, and efficient. This study describes the development of an accessible, transparent, and extensible integrated hydrologic models (IHM) which can be approved with confidence by the regulators as well as scientific community and thus suitable for current and future safety assessment of the DGR systems. The IHM under development can currently simulate overland flow, groundwater flow, near surface evapotranspiration in a modular manner. The IHM can also be considered as a framework as it can easily accommodate additional processes and requirements for the future as it is necessary. The IHM is capable of handling the atmospheric, land surface, and subsurface processes for simultaneously analyzing the regional groundwater driving force and deep subsurface flow, and repository scale safety features, providing an ultimate basis for seamless safety assessment in the DGR program. The applicability of the IHM to the DGR safety assessment is demonstrated using illustrative examples.

Spent nuclear fuels should be safely stored until being disposed and dry storage system is predominantly used to retain the fuels. During long-term storage, there are several mechanisms that could result in the degradation of spent nuclear fuels, and the temperature is the most important parameter to predict and estimate the degradation behaviors. Therefore, thermal analysis to estimate temperatures of spent nuclear fuel and the storage system should be performed to evaluate whether the temperatures exceed safety limit. Recently, thermal hydraulic analysis with CFD codes is widely used to investigate the temperature of spent nuclear fuel in dry storage. Herein, Explicit CFD analysis model is introduced and validated by estimating the thermal hydraulic response of the dry storage system that is Dry Cask Simulator (DCS). Extended Storage Collaborating Program (ESCP) led by the Electric Power Research Institute (EPRI) is organized to assess degradation effects of spent nuclear fuel during long-term dry storage, and DCS is the first phase of the program. The dry storage system, containing a single BWR assembly in a canister, was designed to produce validation-quality data for thermal analysis model. ANSYS FLUENT is used to simulate DCS, and the test condition of 0.5 kW decay heat and 100 kPa helium pressure was investigated in this study. In case of peak cladding temperature (PCT), PCT from the experiment was 376 K while that of CFD was 374 K. It implies CFD simulation gives good agreement with experimental measurement. Peak temperatures of channel can, basket, canister and shell predicted by CFD simulation also show good prediction and the discrepancies were less than 7 K while measurements uncertainty was 7 K.

The damage ratio of Spent Nuclear Fuel (SNF) is a very important intermediate variable for dry storage risk assessment which require an interdisciplinary and comprehensive investigation. It is known that the pinch load applied to the cladding can lead to Mode-3 failure and the cladding becomes more vulnerable to this failure mode with the existence of radial hydrides and other forms of mechanical defects. In this study, a sensitivity analysis was performed to evaluate the importance of the damage parameters that need to be calibrated for the simulation of zircaloy-4 cladding failure using computational mechanics. The simulation model was generated from a microscopic image of the cladding with hydride. The image segmentation method was used to separate the Zircaloy-4, hydride, and hydride- Zircaloy matrix interfaces to create a pixel-based finite element model. The ring compression test (RCT) was simulated because the resistance of the cladding under pinch load can be evaluated by this test. It was assumed that the damage starts with the formation and growth of voids or small cracks in the material, which grow and combine to form larger cracks, eventually leading to the complete fracture of the material. Therefore, the ductile damage criterion was applied to all materials to simulate crack formation and propagation. The sensitivity analysis was performed based on the design of experiments using L8 orthogonal array. The effects of five factors on the fracture resistance of hydrided cladding were quantified, and they are the fracture strains describing the damage initiation in zircaloy-4 matrix, hydride, and hydride-zirconium matrix, and yield stress and Young’s modulus for hydride-zirconium matrix. Information on those parameters are hardly available in literature and experimental data which enable the estimation of those are also very rare. It is planned to build a computational model which can accurately simulate the fracture behavior of hydrided cladding by calibrating significant fracture parameters using reverse engineering. The results of this study will help to figure out those significant parameters.

Surveillance plays a crucial role in safeguards. Reviewing surveillance data requires a significant number of inspection manpower. As the number of surveillance cameras increases, the demand for such manpower is expected to grow even more. Recently, in the field of security, there has been a development of deep learning models that automatically detect abnormal events from video images, and their usage is expanding. In this study, we used an AutoEncoder-based semi-supervised learning model, which can detect unexpected abnormal events, to detect anomalies in the UCSDped2 dataset and in simulating safeguards-related event videos taken at Dry Mockup facility of KAERI. To improve the model performance, we transformed the video images into two parts: the appearance part, which are sequences of video image frames, and the motion part, which are the pixel value differences of consecutive video frames. In addition, we added memory module to the bottle neck of the AutoEncoder model, and skip connection to enhance the model performance. To evaluate the model performance, we proposed a new evaluation index, which is adequate to the video images of safeguards surveillance in addition to the widely used AUC (Area Under the ROC Curve).

대학은 끊임없이 새로운 지식을 만들고 기술혁신을 통하여 가치를 생산하는 핵심 기관이다. 본 연구에서는 삼중나선모델(Triple Helix Model)의 변화와 진화를 제시하고자 한다. 이를 위해 선진기술의 습득과 소화, 개선과 추월을 통한 과정에 요구되었던 다양한 인력양성 육성과 정책분석의 질적연구를 활용하였다. 1960년대는 기능공과 기술공 위주로 기능적역량이, 1980년 대와 1990년대는 대학원제도가 정착, 고급 인력양성과 함께 정부주도의 대학-기업연구소와의 Triple Helix Model (THM) 혁신활동에 필요한 기능과 기술역량의 인력양성이 강조되었다. 2000년대는 첨단․신산업에 요구되는 창의적 인재양성으로 진화하였고 대학 중심 THM이 본격적으로 추진되는 연구역량이 요구되었고 2010년 이후 창의와 융합역량의 인력양성 방향 성을 대학스스로 결정하는 큰 변화로 진화하였고, 이에 본 연구에서는 창조와 융합 인력양성의 지속적 수행을 위한 혁신모델로 ‘삼중나선싱크로시나리오모델’을 제시한다. 대학은 자유롭게 문제를 찾아내고 정부는 신기술을 위한 지원과, 개인경험과 기업문제를 하나의 시나리오로 엮어 이를 해결하고자 하는 도전의 장이 되어 끊임없는 혁신을 견인해야 한다.