There are growing concerns that the recently implemented Earthquake Early Warning service is overestimating the rapidly provided earthquake magnitudes (M). As a result, the predicted damages unnecessarily activate earthquake protection systems for critical facilities and lifeline infrastructures that are far away. This study is conducted to improve the estimation accuracy of M by incorporating the observed S-wave seismograms in the near source region after removing the site effects of the seismograms in real time by filtering in the time domain. The ensemble of horizontal S-wave spectra from at least five seismograms without site effects is calculated and normalized to a hypocentric target distance (21.54 km) by using the distance attenuation model of Q(f)=348f0.52 and a cross-over distance of 50 km. The natural logarithmic mean of the S-wave ensemble spectra is then fitted to Brune’s source spectrum to obtain the best estimates for M and stress drop (SD) with the fitting weight of 1/standard deviation. The proposed methodology was tested on the 18 recent inland earthquakes in South Korea, and the condition of at least five records for the near-source region is sufficiently fulfilled at an epicentral distance of 30 km. The natural logarithmic standard deviation of the observed S-wave spectra of the ensemble was calculated to be 0.53 using records near the source for 1~10 Hz, compared to 0.42 using whole records. The result shows that the root-mean-square error of M and ln(SD) is approximately 0.17 and 0.6, respectively. This accuracy can provide a confidence interval of 0.4~2.3 of Peak Ground Acceleration values in the distant range.

Bee traffic at the hive entrance can be used as an important indicator of foraging activity. We investigated patterns of honeybees and bumblebees near their hives as a basis for calculating bee traffic using the image deep learning. The flight pattern near the hive differed significantly according to bee at entering and leaving the hive. Honeybees mainly showed flight that changed flight direction more than once (69.5%), whereas bumblebees mainly performed straight flight (48.7%) or had a single turn (36.5%) in flight. When bees entered the hive, honeybees primarily showed one-turn or two-turn flight patterns(88.5%), and bumblebees showed a one-turn flight pattern (48.0%). In contrast, when leaving the hive, honeybees primarily showed a straight flight pattern (63.0%), and bumblebees primarily showed a straight or one-turn pattern (90.5%). There was a significant difference in flight speed according to the flight pattern. The speed of straight flight (0.89±0.47 m/s) was 1.5 to 2.1 times faster than flight where direction changed. Therefore, our results can help determine the capturing and recognizing the flying image of bees when calculating bee traffic by image deep learning.

The large copper butterfly Lycaena dispar (Haworth, 1803; Lepidoptera: Lycaenidae) has been categorized as a near-threatened species (NT) in South Korea from 2012 mainly due to limited distribution. In this study, we visited 36 sites spread across all South Korean provinces to verify the distributional range of the species and sequenced mitochondrial COI for 53 individuals from nine sites. We observed L. dispar at 15 sites in six provinces, including the two previously known provinces, indicating a southward range expansion. The in-field monitoring and genetic data collectively suggested that L. dispar does not have a limited distribution nor is it isolated, indicating that it should be reclassified as less vulnerable. Our study demonstrates that the combination of field and genetic data can provide a more reliable assessment of the stability of a species.

As climate change and population growth raise the likelihood of natural disasters, it becomes crucial to comprehend and mitigate these risks in vital infrastructure systems, especially nuclear power plants (NPPs). This research addresses the necessity for evaluating multiple hazards by concentrating on slope failures triggered by earthquakes near NPPs over a timeframe extending up to a return period of 100,000 years. Utilizing a Geographical Information System (GIS) and Monte Carlo Simulation (MCS), the research conducts a comprehensive fragility assessment to predict failure probability under varying ground-shaking conditions. According to the Newmark displacement method, factors such as Peak Ground Acceleration (PGA), slope angle, soil properties, and saturation ratio play significant roles in determining slope safety outcomes. The investigation aims to enhance understanding seismic event repercussions on NPP-adjacent landscapes, providing insights into long-term dynamics and associated risks. Results indicate an increase in slope vulnerability with longer return periods, with distinct instances of slope failures at specific return periods. This analysis not only highlights immediate seismic impacts but also underscores the escalating risk of slope displacement across the extended return period scales, crucial for evaluating long-term stability and associated hazards near nuclear infrastructure.

목적 : 현재 주목받고 있는 스마트 글라스와 같은 증강현실 기술은 배터리, 발열, 착용감 문제 등으로 사용자의 불편을 야기시킨다. 본 연구는 이러한 문제들을 해결하고 사용자 편의성을 극대화할 수 있는 새로운 NED 광학계 를 설계하고자 한다. 방법 : Waveguide 타입과 비구면 구성을 적용한 허상광학계로 NED 광학계를 설계하였다. Code V 소프트웨어 를 사용하였고, 경량화, 높은 시야각, 낮은 왜곡 수차 및 우수한 이미지 품질을 설계 목표로 하여 비순차 광학계를 구성하였다. 결과 : 설계된 광학계는 배율 증가, 포커싱, 수차 감소에 초점을 맞춘 첫 번째 파트와 빛의 손실을 최소화하는 Waveguide 타입의 두 번째 파트로 구성하여 고효율성과 높은 해상도를 나타내었다. 사용자에게 선명하고 편안한 시각적 경험을 보장하고, 컴팩트한 디자인으로 휴대성과 사용자 편의성이 동시에 고려된 광학계를 설계하였다. 결론 : 본 연구에서 개발된 Waveguide 타입과 비구면 광학계는 빛의 손실을 최소화하여 망막까지 효율적으로 전달함으로써 NED 기술의 성능을 크게 향상시켰다. 이는 사용자에게 더 높은 선명도와 생동감 있는 시각적 경험 을 제공하며, 향후 고해상도 광학 응용 분야에 큰 기여를 할 것으로 판단된다.

To ensure the safety of disposal facilities for radioactive waste, it is essential to quantitatively evaluate the performance of the waste disposal facilities by using safety assessment models. This paper addresses the development of the safety assessment model for the underground silo of Wolseong Low-and Immediate-Level Waste (LILW) disposal facility in Korea. As the simulated result, the nuclides diffused from the waste were kept inside the silo without the leakage of those while the integrity of the concrete is maintained. After the degradation of concrete, radionuclides migrate in the same direction as the groundwater flow by mainly advection mechanism. The release of radionuclides has a positive linear relationship with a half-life in the range of medium half-life. Additionally, the solidified waste form delays and reduces the migration of radionuclides through the interaction between the nuclides and the solidified medium. Herein, the phenomenon of this delay was implemented with the mass transfer coefficient of the flux node at numerical modeling. The solidification effects, which are delaying and reducing the leakage of nuclides, were maintained the integrity of the nuclides. This effect was decreased by increasing the half-life and the mass transfer coefficient of radionuclides.

Over the years, in the field of safety assessment of geological disposal system, system-level models have been widely employed, primarily due to considerations of computational efficiency and convenience. However, system-level models have their limitations when it comes to phenomenologically simulating the complex processes occurring within disposal systems, particularly when attempting to account for the coupled processes in the near-field. Therefore, this study investigates a machine learning-based methodology for incorporating phenomenological insights into system-level safety assessment models without compromising computational efficiency. The machine learning application targeted the calculation of waste degradation rates and the estimation of radionuclide flux around the deposition holes. To develop machine learning models for both degradation rates and radionuclide flux, key influencing factors or input parameters need to be identified. Subsequently, process models capable of computing degradation rates and radionuclide flux will be established. To facilitate the generation of machine learning data encompassing a wide range of input parameter combinations, Latin-hypercube sampling will be applied. Based on the predefined scenarios and input parameters, the machine learning models will generate time-series data for the degradation rates and radionuclide flux. The time-series data can subsequently be applied to the system-level safety assessment model as a time table format. The methodology presented in this study is expected to contribute to the enhancement of system-level safety assessment models when applied.

Long-term climate and surface environment changes can influence the geological subsurface environment evolution. In this context, a fluid flow pathway developing and connection possibility can be increased between the near-surface zone and deep depth underground. Thus, it is necessary to identify and prepare for the overall fluid flow at the entire geological system to minimize uncertainty on the spent nuclear fuel (SNF) disposal safety. The fluid flow outside the subsurface environment is initially penetrated through the surface and then the unsaturated area. Thus, the previously proved reports, POSIVA in Finland, suggested that sequential research about the fluid infiltration experiment (INEX) and the investigation is necessary. Characterizing the unsaturated zone can help predict changes and ensure the safety of SNFs according to geological long-term evolution. For example, the INEX test was conducted at the upper part of ONKALO, about 50 to 100 m depth, to understand the geochemical evolution of the groundwater through the unsaturated zone, to evaluate the main flow of groundwater that can approach the SNF disposal reservoir, and to estimate the decreasing progress of the buffering capacity along the pathway through the deep geological disposal. In the present study, a preliminary test was performed in the UNsaturated-zone In-situ Test (UNIT) facility near the KAERI underground research tunnel to design and establish a methodology for infiltration experiments consistent with the regional characteristics. The results represented the methodological application is possible for characterizing unsaturated-zone to perform infiltration experiments. The scale of the experiment will be expanded sequentially, and continuous research will be conducted for the next application.

The bioreduction process from soluble U(VI) to insoluble U(IV) has been extensively studied in the field of radionuclides migration. Since acetic acid (AcOH) is widely used as an electron donor for bioreduction of U(VI), it is necessary to understand the effect of U(VI)-AcOH complexes that exist in different species depending on pH on this process. Changes in samples before and after bioreduction can be compared using time-resolved laser luminescence spectroscopy (TRLLS), which measures the characteristic luminescence spectra of different U(VI) species. Although luminescence properties of U(VI)-AcOH species were reported, experiments were conducted under conditions below pH 4.5. In this study, spectrophotometry and TRLLS for U(VI)-AcOH species (10−100 μM U(VI) and 20 mM AcOH) were performed in pH ranges extending to neutral and alkaline pH regions similar to groundwater conditions as well as acidic pH region. Two different complexes (UO2(AcO)+, UO2(AcO)2 with U(VI) and acetate ratios of 1:1, 1:2) were observed in the acidic pH region. The 1:1 complex, which appears as the pH increases, has no luminescence properties, but its presence can be confirmed because it serves to reduce the luminescence intensity of UO2 2+. In contrast, the 1:2 complex exhibits distinct luminescence properties that distinguish it from UO2 2+. The 1:3 complex (UO2(AcO)3 -) expected to appear with increasing pH was not observed. Two different complexes ((UO2)3(OH)5 +, (UO2)3(OH)7 - with U(VI) and OH ratios of 3:5, 3:7) were observed as the major species in the neutral pH region, but their luminescence lifetimes are remarkably short compared those in the absence of AcOH. Solid U(VI) particles were observed in the alkaline pH region, and they also had completely different luminescence properties from the aforementioned U(VI)-AcOH and U(VI)-hydrolysis species. Based on these results, the effect of pH in the presence of AcOH on the bioreduction process from U(VI) to U(IV) will be discussed.

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.

본 연구에서는 울진군 대형산불 발생이 연안해역에 미치는 영향을 파악하기 위하여 울진군 나곡(F-1), 후정(F-2), 봉평(F-3), 공세 항(F-C)에서 수질과 함께 해조류의 종조성, 우점종 및 군집 특성을 분기별로 조사하였다. 수질 분석 결과, 산불에 대한 영향을 판단하기 위한 수소이온농도(pH)는 표․저층에서 각각 8.07~8.30과 8.12~8.48 이었다. 본 연구의 pH 값은 동해의 연안 해수에 있는 일반적인 농도 범 위에 포함된 값으로 산불로 인한 직접적인 영향으로 볼 수 없었다. 연안 조하대에서 조사한 해조류의 분석 결과, 전 시기에 대한 해조류 의 종조성 비율은 홍조류(58.1%) > 대롱편모조류(갈조류, 25.8%) > 녹조류(14.5%) > 현화식물(1.6%) 순이었다. 시기별 해조류의 우점종은 3 월과 6월에 나곡(F-1)과 후정(F-2) 해역에서 대롱편모조류(Ochrophyta, 갈조류)의 미역(Undaria pinnatifida)이 가장 우점하였다. 9월과 11월은 봉평(F-3) 해역과 공세항(F-C)에서 각각 홍조류(Rhodophyta)인 우뭇가사리(Gelidium elegans)와 혹돌잎류(Lithophyllum sp.)가 가장 우점하였다. 군집분석에서는 그룹이 계절에 따른 특정 해조류의 출현 유무에 따라 2개(A, B)로 나누어졌다. 우점종은 그룹 A에서 미역, 우뭇가사리, 미 끈뼈대그물말, 그룹 B는 주로 혹돌잎류가 출현하였다. 따라서, 연구지역의 해조류 종조성과 군집구조는 전형적인 수온에 따른 계절변화 와 함께 대조구와의 유의미한 차이도 보이지 않아서 산불에 의한 영향은 나타나지 않았다.