Early warnings have been developed to provide rapid earthquake information, allowing people to prepare as much time as possible. However, since it takes several seconds for an earthquake warning to be issued, the blind zone is inevitable. To reduce the blind zone, information from a single observatory is used to operate an on-site earthquake warning. However, false and missed alarms are still high, requiring continued research and validation. This study predicted Peak Ground Acceleration (PGA) using the characteristic data to reduce false and missed alarms in on-site earthquake warnings. A machine learning prediction model was created using the initial P-wave parameters developed from the characteristic data to achieve this. Then, the model was used to predict the maximum ground acceleration in the southeastern region of the Korean Peninsula. The expected results for six target earthquakes were confirmed to have a standard deviation within 0.3 compared to the observed PGA and the values within ±2 sigma. This method is expected to help develop an on-site early warning system for earthquakes.

A seismic intensity map, which describes ground motion distribution due to an earthquake, is crucial for disaster evaluation after the event. The ShakeMap system, developed and disseminated by the USGS, is widely used to generate intensity maps in many countries. The system utilizes a semi-variogram model to interpolate the measured intensities at seismic stations spatially. However, the default semi-variogram model embedded in ShakeMap is based on data from high seismic regions, which may not be suitable for the Korean Peninsula, categorized as a low-to-moderate seismic region. To address this discrepancy, this study aims to develop the region-specific semi-variogram model using local records and a region-specific ground motion model (GMM). To achieve this, we followed these steps: 1) collected records from significant earthquake events in South Korea, 2) calculated residuals between the observed intensities and predictions by the GMM, and 3) created semi-variogram models using weighted least squares regression to better fit short separation distances for PGA, PGV, SA0.2, and SA1.0. We compared the developed semi-variogram models with conventional models embedded in ShakeMap. Validation tests showed that the region-specific semi-variogram model reduced the mean squared error of intensity predictions by approximately 3.5% compared to the conventional model.

While the subduction zone earthquakes have long ground motion durations, the effects are also not covered in seismic design provisions. Additionally, the collapse risk of steel frame buildings subjected to long-duration ground motions from subduction earthquakes remains poorly understood. This paper presents the influence of ground motion duration on the collapse risk of steel frame buildings with special concentrically braced frames in chevron configurations. The steel buildings considered in this paper are designed at a site in Seattle, Washington, according to the requirements of modern seismic design provisions in the United States. For this purpose, the nonlinear dynamic analyses employ two sets of spectrally equivalent long and short-duration ground motions. Based on the use of high-fidelity structural models accounting for both geometric and material nonlinearities, the estimated collapse capacity for the modern code-compliant steel frame buildings is, on average, approximately 1.47 times the smaller value when considering long-duration ground motion record, compared to the short-duration counterpart. Due to the sensitivity to destabilizing P-Delta effects of gravity loads, the influence of ground motion duration on collapse risk is more profound for medium-to-high-rise steel frame buildings compared to the low-rise counterparts.

광릉숲은 생물권보전지역 중 하나로써 생물다양성이 높은곳이며, 낙엽활엽수림으로써 550년 동안 관리되어 왔다. 이 연구는 2016년부터 2017년까지 생물권보전지역(포천)과 비생물권보전지역(울진, 영주)에서 신갈나무림과 소나무림의 딱정벌레 군집구조와 다양성을 비교하는것이 목적이다. 이 조사에서 딱정벌레과에 속하는 9아과 25속 73종을 채집하였다. 생물권보전지역 소나무림에서 25종 11속 6아과 그리고 신갈나무림에 서 22종 9속 4아과를 채집하였다. 비생물권보전지역 신갈나무림과 소나무림에서 23종 10속 5아과 그리고 59종 21속 9아과를 채집하였다. 생물권 보전지역의 소나무림과 신갈나무림에서 우점종은 윤납작먼지벌레(77.2%, 78.7%)이며, 비생물권보전지역의 소나무림과 신갈나무림에서 우점종 은 각각 Synuchus sp. 3(47.9%)와 Synuchus sp. 2(17.6%)이다. 종 다양도, 종 풍부도, 종 균등도는 도로와 가장 가까운 비생물권지역의 신갈나무림 에서 가장 높았으며, 산림에서 종 다양성은 채집지에서 도로까지의 거리가 가까울수록 증가하는 것으로 판단된다. 이러한 연구 결과는 생물권보전 지역에서 생물다양성 보존을 위한 중요한 자료가 될 것으로 기대된다.

Being in a stable continental region (SCR) with a limited history of instrumentation, South Korea has not collected sufficient instrumental data for data-driven ground motion models. To address this limitation, we investigated the suitability of the hybrid ground motion simulation method that Graves and Pitarka (2010, 2015) proposed for simulating earthquake ground motions in South Korea. The hybrid ground motion simulation method used in this study relies on region-specific parameters to accurately model phenomena associated with the seismic source and the wave propagation. We initially employed relevant models and parameters available in the literature as a practical approach. We incorporated a three-dimensional velocity model developed by Kim et al. (2017) and a one-dimensional velocity model presented by Kim et al. (2011) to account for the crustal velocity structure of the Korean peninsula. To represent the earthquake source, we utilized Graves and Pitarka’s rupture generator algorithm along with a magnitude-area scaling relationship developed for SCR by Leonard (2014). Additionally, we assumed the stress and attenuation parameters based on studies of regional seismicity. Using the implemented platform, we simulated the 2016 Mw5.57 Gyeongju earthquake and the 2017 Mw5.4 Pohang earthquake. Subsequently, we compared results with recorded accelerations and an empirical ground motion prediction equation at strong motion stations. Our simulations had an overall satisfactory agreement with the recorded ground motions and demonstrated the potential of broadband hybrid ground motion simulation for engineering applications in South Korea. However, limitations remain, such as the underestimation of long-period ground motions during the 2017 Pohang earthquake and the lack of a model to predict the ground motion amplification associated with the near-surface site response accurately. These limitations underscore the importance of careful validation and refinement of region-specific models and parameters for practically implementing the simulation method.

In stable continental regions, selecting appropriate ground motions for seismic design and dynamic response analysis presents significant challenges. This study evaluates the liquefaction potential of the Nakdonggang delta region, South Korea, by generating synthetic ground motion scenarios and applying a scenario-based liquefaction assessment approach. We utilized a hybrid broadband ground motion simulation method proposed by Graves and Pitarka (2010, 2015) to create bedrock ground motions for three hypothetical earthquakes (Mw 6.2 and 6.0) occurring along the Dongrae and Miryang faults. The generated synthetic ground motions were used as input for onedimensional nonlinear site response analyses, incorporating shear wave velocity profiles derived from surface wave inversion. The simulated ground motions demonstrated higher responses at short periods and relatively weaker responses at long periods compared to the Korean design spectra. This amplification of long-period components was attributed to the dynamic response of deep sedimentary layers, while high-frequency components were generally deamplified due to damping effects in shallow silty layers. Liquefaction susceptibility was assessed using surface ground motions derived from the site response analyses, following the SPT-based simplified method proposed by Idriss and Boulanger (2008). Results indicated high liquefaction potential across most sites for the Dongrae earthquake scenario, while liquefaction was unlikely for all sites under the Miryang-1 scenario. For the Miryang-2 scenario, liquefaction was predicted at some sites. Overall, liquefaction is expected at PGA values of approximately 0.13 g or higher, with sites exhibiting lower shear wave velocities being more vulnerable to liquefaction

대기 경계층은 특히 마찰로 인한 난류 운동 에너지 소산이 점성 하위층(VS)을 지배하는 표면 근처에서 대기의 자유 전단과 표면 마찰 사이의 복잡한 상호 작용에 의해 결정된다. 또한 로그 프로파일이 공존하며 마찰에 의해 난류가 재생되기도 한다. 현재 일 반적으로 공학적 목적으로 대기 경계층 내의 평균 풍속 프로파일은 표면 근처의 일정한 풍속을 가정하여 지수 법칙 또는 로그 법칙을 사용하여 모델링되는 경우가 많다. 그러나 증발, 복사 등의 열역학적 과정 외에 지표 부근 대기의 움직임에 의해 크게 영향을 받는 현 상을 분석하기 위해서는 지표 부근 풍속 프로파일에 대한 정의가 요구된다. 이에 본 연구에서는 난류 경계층에 대한 이전 연구의 이론 및 실험 결과를 활용하여 표면 거칠기를 고려한 VS 및 완충층 내의 풍속 프로파일을 제안하였다.

본 연구는 SCGPA(Spent Coffee Grounds Pellet Ash)를 활용하여 다양한 혼합비율로 시멘트 복합체를 제작함으로써 SCGPA 의 신규 건설 재료로서의 적용 가능성을 확인하는 것을 목적으로 한다. 강도 시험 결과, 28일 압축강도 36.31 MPa 및 휨강도 12 MPa 를 나타낸 혼합비가 최적 혼합비로 도출되었으며, SCGPA의 시멘트 치환율이 증가함에 따라 복합체의 전반적인 강도 특성이 감소하는 경향성을 발견하였다. SEM 및 XRD 분석 결과, SCGPA는 최대 10%의 적절한 치환율을 적용할 경우 큰 강도의 저하를 일으키지 않고 시멘트 대체재로 기능할 수 있음이 확인되었다. 본 연구 결과를 바탕으로, 고품질의 굵은 골재를 함께 사용하여 콘크리트를 생산할 경 우, 30 MPa 이상의 압축강도를 가진 구조용 콘크리트도 제조할 수 있을 것으로 기대된다.

펄스형 지진은 구조물에 손상을 크게 유발한다. 펄스지표의 계산에 의해 지진 가속도 기록에 대한 속도펄스의 존재 유무와 그 세기 의 평가가 가능하다. 입사각의 변화에 따른 펄스지표 값이 동일 지진에 대하여 대략 20 정도 차이가 난다. 지진파의 입사각의 변화에 따른 펄스지표를 평가하고, 5가지 펄스지표 백분위수(0, 25, 50, 75, 100 백분위수)에 따른 한 쌍의 40개 지진파를 사용하여 교량구조 물의 지진응답과 지진취약도 평가를 수행하였다. 펄스지표가 큰 지진파일수록 가속도응답스펙트럼 또한 이에 비례하여 증가하는 경 향을 나타냄을 알 수 있다. 지진파의 펄스지표(PI)가 증가할수록 교량의 지진응답을 증가시켜 지진취약도를 증가시키는 경향을 나타 냄을 알 수 있다. 최대 펄스지표의 지진파의 경우가 최소 펄스지표의 지진파의 경우에 비하여 교각의 지진취약도를 대략 평균적으로 25~27% 정도 증가시키는 경향이 있다.

국내 콘크리트 구조물의 노후화가 진행됨에 따라 안전관리를 위한 효과적인 보수 및 보강이 요구되고 있다. 특히, 교량 바닥판은 교통하중과 염화물 침투 등 다양한 유해환경에 직접 노출되어 지속적인 열화가 발생하고 있다. 국내외에서는 교량 바닥판 유지보수 의사결정을 위해 비파괴 조사 방법 중 하나인 지표투과레이더(Ground Penetrating Radar, GPR) 탐사가 주로 활용되고 있다. 차량형 다채널 GPR 장비를 통해 취득된 방대한 양의 탐사자료는 해석하는 데 많은 시간이 소요되며 분석가의 주관이나 숙련도에 따라 해석결과가 달라질 수 있다. 이러한 문제를 해결하기 위해 최근에는 딥러닝 (Deep Learning) 기반의 GPR 자료해석 기법들이 제안되고 있다. 본 연구에서는 교량 바닥판 상태 평가 작업 효율 향상 을 위해 딥러닝 기반 GPR 자료해석 기법을 적용하였다. 현장자료 예제로는 영동대교 정밀안전진단 과업에서 교량 바닥 판 상태조사를 위해 취득한 GPR 자료를 사용하였으며 딥러닝 기법 적용 결과를 분석가의 해석결과와 비교하여 예측 성 능을 평가하였다.

Seismic fragility curves present the conditional probability of damage to target structures due to external seismic load and are widely used in various ways. When constructing such a seismic fragility curve, it is essential to consider various types and numbers of ground motions. In general, the earthquake occurrence characteristics of an area where the target structure of the seismic fragility curve exists are analyzed, and based on this, appropriate ground motions are selected to derive the seismic fragility curve. If the number of selected ground motions is large, the diversity of ground motions is considered, but a large amount of computational time is required. Conversely, if the number of ground motions is too small, the diversity of ground motions cannot be considered, which may distort the seismic fragility curve. Therefore, this study analyzed the relationship between the number of ground motions considered when deriving the seismic fragility curve and the parameters of the seismic fragility curve. Using two example structures, numerical analysis was performed by selecting a random number of ground motions from a total of two hundred, and a seismic fragility curve was derived based on the results. Analysis of the relationship of the parameter of the seismic fragility curve and the number of selected ground motions was performed. As the number of ground motions considered increases, uncertainty in ground motion selection decreases, and when deriving seismic fragility curves considering the same number of ground motions, uncertainty increases relatively as the degree of freedom of the target structure increases. However, considering a relatively large number of ground motions, uncertainty appeared insignificant regardless of increased degrees of freedom. Finally, it is possible that the increase in the number of ground motions could lower the epistemic uncertainty and thus improve the reliability of the results.

The damage to structures during an earthquake can be varied depending on the frequency characteristics of seismic waves and the geological properties of the ground. Therefore, considering such attributes in the design ground motions is crucial. The Korean seismic design standard (KDS 17 10 00) provides design response spectra for various ground classifications. If required for time-domain analysis, ground motion time series can be either selected and adjusted from motions recorded at rock sites in intraplate regions or artificially synthesized. Ground motion time series at soil sites should be obtained from site response analysis. However, in practice, selecting suitable ground motion records is challenging due to the overall lack of large earthquakes in intraplate regions, and artificially synthesized time series often leads to unrealistic responses of structures. As an alternative approach, this study provides a case study of generating ground motion time series based on the hybrid broadband ground motion simulation of selected scenario earthquakes at sites in the Nakdonggang delta region. This research is significant as it provides a novel method for generating ground motion time series that can be used in seismic design and response analysis. For large-magnitude earthquake scenarios close to the epicenter, the simulated response spectra surpassed the 1000-year design response spectra in some specific frequency ranges. Subsequently, the acceleration time series at each location were used as input motions to perform nonlinear 1D site response analysis through the PySeismoSoil Package to account for the site response characteristics at each location. The results of the study revealed a tendency to amplify ground motion in the mid to long-period range in most places within the study area. Additionally, significant amplification in the short-period range was observed in some locations characterized by a thin soil layer and relatively high shear wave velocity soil near the upper bedrock.

To analyse the relationship between above-ground carbon stocks, species diversity and broadleaved forests structural diversity of South Korean forests, we collected vegetation inventories from environmental impact assessment projects over the past 10 years. The available data were selected and organised including tree species, DBH and area each projects. The data was classified by forest type, aboveground carbon stocks were calculated and compared, and the correlation between aboveground carbon stocks and biodiversity and structural diversity was analysed. The results showed that above-ground carbon stocks were higher in mixed forests and broadleaved forests and lower in needleleaved forests, similar to previous studies. However aboveground carbon stocks of mixed forests were higher in natural forests than in plantations. Aboveground carbon stocks in broadleaved forests were higher in plantations than natural forests, and there was no statistical different of between natural and plantations in needleleaved forest. This could be the result of a variety influences including biological and environmental factors in the study area, and further research is needed to analyse the effects on carbon sequestration. Correlation analysis showed no correlation between biodiversity and above-ground carbon stocks, but a positive correlation between structural diversity and above-ground carbon stocks. This indicates that above-ground carbon stocks in forests are associated with unevenness diameters and the proportion and evenness of tree species by diameter. In addition, it has been analysed that the high succession stages in forest have higher species diversity and structural diversity, and greater efficiency in the utilization of resources required for plant growth, leading to increased plant productivity and storage. Considering that the study sites were young forests with an average DBH of 14.8~23.7 cm, it is expected that carbon stocks will increase as biodiversity and structural diversity increase. Further research is needed to develop techniques to quantitatively assess the relationship of diversity to carbon stocks for policy use in assessing and increasing carbon stocks in forests.

Black ice, a thin and nearly invisible ice layer on roads and pavements, poses a significant danger to drivers and pedestrians during winter due to its transparency. We propose an efficient black ice detection system and technique utilizing Global Positioning System (GPS)-reflected signals. This system consists of a GPS antenna and receiver configured to measure the power of GPS L1 band signal strength. The GPS receiver system was designed to measure the signal power of the Right-Handed Circular Polarization (RHCP) and Left-Handed Circular Polarization (LHCP) from direct and reflected signals using two GPS antennas. Field experiments for GPS LHCP and RHCP reflection measurements were conducted at two distinct sites. We present a Normalized Polarized Reflection Index (NPRI) as a methodological approach for determining the presence of black ice on road surfaces. The field experiments at both sites successfully detected black ice on asphalt roads, indicated by NPRI values greater than 0.1 for elevation angles between 45o and 55o. Our findings demonstrate the potential of the proposed GPS-based system as a cost-effective and scalable solution for large-scale black ice detection, significantly enhancing road safety in cold climates. The scientific significance of this study lies in its novel application of GPS reflection signals for environmental monitoring, offering a new approach that can be integrated into existing GPS infrastructure to detect widespread black ice in real-time.

This study proposes a soil moisture retrieval method from ground reflection signals received by Global Positioning System (GPS) antenna modules consisting of an up-looking (UP) right-hand circular polarization (RHCP) and two down-looking (DW) RHCP and left-hand circular polarization (LHCP) signals. Field experiments at four different surface types (asphalt, grassland, dry soil, and moist soil) revealed that the DW RHCP and LHCP signals are affected by antenna height and multipath interference signals. The strength differences between the DW LHCP and UP RHCP signals were in good agreement with the DW LHCP signals. Methodologically, this study applied a spectrum analysis to the detrended surface-reflected signals for RHCP and LHCP. The study indicated that the down-looking antenna exhibited greater sensitivity to reflected GPS signals than the up-looking antenna. We demonstrated the feasibility of estimating soil moisture using GPS signals, by comparing LHCP signals received by the down-looking antenna with theoretical values. This study presents a novel method for estimating soil moisture in vegetated areas, leveraging the advantage of crosspolarization comparisons to achieve stronger signal strength than single-polarization reflection signals. With further research, including long-term observations and detailed analysis, the proposed method has the potential to enhance performance significantly.

Accurate seismic vulnerability assessment requires high quality and large amounts of ground motion data. Ground motion data generated from time series contains not only the seismic waves but also the background noise. Therefore, it is crucial to determine the high-pass cut-off frequency to reduce the background noise. Traditional methods for determining the high-pass filter frequency are based on human inspection, such as comparing the noise and the signal Fourier Amplitude Spectrum (FAS), f2 trend line fitting, and inspection of the displacement curve after filtering. However, these methods are subject to human error and unsuitable for automating the process. This study used a deep learning approach to determine the high-pass filter frequency. We used the Mel-spectrogram for feature extraction and mixup technique to overcome the lack of data. We selected convolutional neural network (CNN) models such as ResNet, DenseNet, and EfficientNet for transfer learning. Additionally, we chose ViT and DeiT for transformer-based models. The results showed that ResNet had the highest performance with R2 (the coefficient of determination) at 0.977 and the lowest mean absolute error (MAE) and RMSE (root mean square error) at 0.006 and 0.074, respectively. When applied to a seismic event and compared to the traditional methods, the determination of the high-pass filter frequency through the deep learning method showed a difference of 0.1 Hz, which demonstrates that it can be used as a replacement for traditional methods. We anticipate that this study will pave the way for automating ground motion processing, which could be applied to the system to handle large amounts of data efficiently.

정원치유 확산과 원예치료에 관한 관심이 높아짐에 따라 원예치료프로그램에 이용되고 있는 식물소 재인 지피초화류의 이용과 재배현황을 파악하였다. 지피초화류의 원예치료프로그램 이용품목을 정 리하고 이용전문가와 재배농가의 의견을 반영한 결과를 도출하였다. 이를 바탕으로 지피초화류의 치 유프로그램에 이용품목을 계절별로 분류 체계화하고 공급과 이용에 유의미한 기초자료를 제공하고자 하는 것이 본 연구의 목적이다. 원예치료전문가 대상으로 지피초화류의 치유프로그램 이용 관련 설문 지를 배포 130부 회수하였고 재배농가 대상으로 지피초화류의 재배품목 관련 설문지를 배포하여 20부 를 회수하여 이용과 재배품목 현황, 추천식물, 이용과 재배의향을 빈도분석과 비교분석을 실시하여 연 구결과를 도출하였다. 연구결과 원예치료전문가들은 다양한 종류의 지피초화류를 이용하고 있었으 며, 최근 들어서는 주로 꽃꽂이 용도로 이용하고 있는 절화류나 그라스류를 이용하기 시작한 것으로 나타났다. 추천식물로 이용자·재배자 모두 허브를 1순위로 추천하였다. 또한 원예치료전문가와 재배 농가의 이용과 재배의향은 동일한 의향을 보이는 지피초화류도 있었지만 상이한 의향을 보이는 지피 초화류도 있는 것으로 파악되어 이용자·재배자간의 관심도와 이용도에 차이점도 분명히 나타나고 있 었다. 따라서 지피초화류의 치유프로그램 적용 시에는 원예치료전문가에게 식물 선택의 용이성을 제 공하고 원예치료전문가와 재배농가의 정보교류를 통한 소비와 공급의 상호 불일치 품목에 대해 보완 해 나갈 수 있는 좋은 기초자료를 제공할 수 있는 연구결과를 도출한 것이 본 연구의 성과라 할 수 있다.

The cultural heritage of fortresses is often exposed to external elements, leading to significant damage from stone weathering and natural disasters. However, due to the nature of cultural heritage, dismantling and restoration are often impractical. Therefore, the stability of fortress cultural heritage was evaluated through non-destructive testing. The durability of masonry cultural heritages is greatly influenced by the physical characteristics of the back-fille material. Dynamic characteristics were assessed, and endoscopy was used to inspect internal fillings. Additionally, a finite element analysis model was developed considering the surrounding ground through elastic wave exploration. The analysis showed that the loss of internal fillings in the target cultural heritage site could lead to further deformation in the future, emphasizing the need for careful observation.

Recent earthquakes in Korea, like Gyeongju and Pohang, have highlighted the need for accurate seismic hazard assessment. The lack of substantial ground motion data necessitates stochastic simulation methods, traditionally used with a simplistic point-source assumption. However, as earthquake magnitude increases, the influence of finite faults grows, demanding the adoption of finite faults in simulations for accurate ground motion estimates. We analyzed variations in simulated ground motions with and without the finite fault method for earthquakes with magnitude (Mw) ranging from 5.0 to 7.0, comparing pseudo-spectral acceleration. We also studied how slip distribution and hypocenter location affect simulations for a virtual earthquake that mimics the Gyeongju earthquake with Mw 5.4. Our findings reveal that finite fault effects become significant at magnitudes above Mw 5.8, particularly at high frequencies. Notably, near the hypocenter, the virtual earthquake’s ground motion significantly changes using a finite fault model, especially with heterogeneous slip distribution. Therefore, applying finite fault models is crucial for simulating ground motions of large earthquakes (Mw ≥ 5.8 magnitude). Moreover, for accurate simulations of actual earthquakes with complex rupture processes having strong localized slips, incorporating finite faults is essential even for more minor earthquakes.