• Title/Summary/Keyword: 강우 분포 기법

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Performance Analysis on Terrain-Adaptive Clutter Map Algorithm for Ground Clutter Rejection of Weather Radar (기상 레이다의 지형 클러터 제거를 위한 지형적응 클러터 맵 알고리듬 성능분석)

  • Kim, Hye-Ri;Jung, Jung-Soo;Kwag, Young-Kil;Kim, Ji-Won;Kim, Ji-Hyeon;Ko, Jeong-Seok
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.25 no.12
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    • pp.1292-1299
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    • 2014
  • Weather radar systems can provide weather information of the ground, sea, and air in extensive spatial coverage in near real time. However, it becomes problematic when ground clutter signal exists around precipitation because strong signals of ground can cause a false precipitation report. A large percentage of land coverage of Korea consists of mountainous regions where ground clutter needs to be mitigated for more accurate prediction. Thus, it is considered necessary to introduce a new suitable ground clutter removal technique specifically adequate for Korea. In this paper, the C-Map(Clutter Map) method using raw radar signals is proposed for removing ground clutter using a terrain-adaptive clutter map. A clutter map is generated using raw radar signals(I/Q) of clear days, then it is subtracted from received radar signals in frequency domain. The proposed method is applied to the radar data acquired from Sobaeksan rain radar and the result shows that the clutter rejection ratio is about 91.17 %.

An Impact Assessment of Climate and Landuse Change on Water Resources in the Han River (기후변화와 토지피복변화를 고려한 한강 유역의 수자원 영향 평가)

  • Kim, Byung-Sik;Kim, Soo-Jun;Kim, Hung-Soo;Jun, Hwan-Don
    • Journal of Korea Water Resources Association
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    • v.43 no.3
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    • pp.309-323
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    • 2010
  • As climate changes and abnormal climates have drawn research interest recently, many countries utilize the GCM, which is based on SRES suggested by IPCC, to obtain more accurate forecast for future climate changes. Especially, many research attempts have been made to simulate localized geographical characteristics by using RCM with the high resolution data globally. To evaluate the impacts of climate and landuse change on water resources in the Han-river basin, we carried out the procedure consisting of the CA-Markov Chain, the Multi-Regression equation using two independent variables of temperature and rainfall, the downscaling technique based on the RegCM3 RCM, and SLURP. From the CA-Markov Chain, the future landuse change is forecasted and the future NDVI is predicted by the Multi-Regression equation. Also, RegCM3 RCM 50 sets were generated by the downscaling technique based on the RegCM3 RCM provided by KMA. With them, 90 year runoff scenarios whose period is from 2001 to 2090 are simulated for the Han-river basin by SLURP. Finally, the 90-year simulated monthly runoffs are compared with the historical monthly runoffs for each dam in the basin. At Paldang dam, the runoffs in September show higher increase than the ones in August which is due to the change of rainfall pattern in future. Additionally, after exploring the impact of the climate change on the structure of water circulation, we find that water management will become more difficult by the changes in the water circulation factors such as precipitation, evaporation, transpiration, and runoff in the Han-river basin.

Quantitative Analysis of Microplastics in Coastal Seawater of Taean Peninsula using Fluorescence Measurement Technique (형광측정기법을 이용한 태안반도 연안 표층수의 미세플라스틱 정량분포 스크리닝)

  • Un-Ki Hwang;Hoon Choi;Ju-Wook Lee;Yun-Ho Park;Wonsoo Kang;Moonjin Lee
    • Journal of Marine Life Science
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    • v.8 no.1
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    • pp.68-77
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    • 2023
  • In this study, we investigated the quantitative distribution of microplastics in the surface seawater at 8 points near the Taean Peninsula using fluorescence staining. The study revealed a detection range of microplastics from 0 to 360.5 particles/l, with an average of 149.7 ± 46.0 particles/l. When classifying the microplastics by size, it was found that particles smaller than 50 ㎛ were dominant, although there were differences at Site 3. Moreover, it was not possible to identify clear correlations when comparing the number of microplastics based on collection area and particle size. Various physical and chemical factors, including plastic material, dynamic ocean conditions (such as currents, wind, waves, tides), geological characteristics (topography, slope), sediment materials including coastal organisms, human activities (fishing, development, tourism), and weather conditions (floods, rainfall), affect the behavior of microplastics. Therefore, future efforts should focus on standardizing quantitative analysis methods and conducting fundamental research on microplastic monitoring, including the analysis of environmental factors.

A Performance Comparison of Land-Based Floating Debris Detection Based on Deep Learning and Its Field Applications (딥러닝 기반 육상기인 부유쓰레기 탐지 모델 성능 비교 및 현장 적용성 평가)

  • Suho Bak;Seon Woong Jang;Heung-Min Kim;Tak-Young Kim;Geon Hui Ye
    • Korean Journal of Remote Sensing
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    • v.39 no.2
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    • pp.193-205
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    • 2023
  • A large amount of floating debris from land-based sources during heavy rainfall has negative social, economic, and environmental impacts, but there is a lack of monitoring systems for floating debris accumulation areas and amounts. With the recent development of artificial intelligence technology, there is a need to quickly and efficiently study large areas of water systems using drone imagery and deep learning-based object detection models. In this study, we acquired various images as well as drone images and trained with You Only Look Once (YOLO)v5s and the recently developed YOLO7 and YOLOv8s to compare the performance of each model to propose an efficient detection technique for land-based floating debris. The qualitative performance evaluation of each model showed that all three models are good at detecting floating debris under normal circumstances, but the YOLOv8s model missed or duplicated objects when the image was overexposed or the water surface was highly reflective of sunlight. The quantitative performance evaluation showed that YOLOv7 had the best performance with a mean Average Precision (intersection over union, IoU 0.5) of 0.940, which was better than YOLOv5s (0.922) and YOLOv8s (0.922). As a result of generating distortion in the color and high-frequency components to compare the performance of models according to data quality, the performance degradation of the YOLOv8s model was the most obvious, and the YOLOv7 model showed the lowest performance degradation. This study confirms that the YOLOv7 model is more robust than the YOLOv5s and YOLOv8s models in detecting land-based floating debris. The deep learning-based floating debris detection technique proposed in this study can identify the spatial distribution of floating debris by category, which can contribute to the planning of future cleanup work.

Analysis of Hazard Areas by Sediment Disaster Prediction Techniques Based on Ground Characteristics (지반특성을 고려한 토사재해 예측 기법별 위험지 분석)

  • Choi, Wonil;Choi, Eunhwa;Baek, Seungcheol
    • Journal of the Korean GEO-environmental Society
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    • v.18 no.12
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    • pp.47-57
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    • 2017
  • In this study, a predictive analysis was conducted on sediment disaster hazard area by selecting six research areas (Chuncheon, Seongnam, Sejong, Daejeon, Miryang and Busan) among the urban sediment disaster preliminary focus management area. The models that were used in the analysis were the existing models (SINMAP and TRIGRS) that are commonly used in predicting sediment disasters as well as the program developed through this study (LSMAP). A comparative analysis was carried out on the results as a means to review the applicability of the developed model. The parameters used in the predictions of sediment disaster hazard area were largely classified into topographic, soil, forest physiognomy and rainfall characteristics. A predictive analysis was carried out using each of the models, and it was found that the analysis using SINMAP, compared to LSMAP and TRIGRS, resulted in a prediction of a wider hazard zone. These results are considered to be due to the difference in analysis parameters applied to each model. In addition, a comparison between LSMAP, where the forest physiognomy characteristics were taken into account, and TRIGRS showed that similar tendencies were observed within a range of -0.04~2.72% for the predicted hazard area. This suggests that the forest physiognomy characteristics of mountain areas have diverse impacts on the stability of slopes, and serve as an important parameter in predicting sediment disaster hazard area.

Numerical Study for Flow Uniformity in Selective Catalytic Reduction(SCR) Process (SCR 공정에서 반응기 내부의 유동 균일화를 위한 수치적 연구)

  • Jung, Yu-Jin;Hong, Sung-Gil;Kim, Min-Choul;Lee, Jae-Jeong;Lee, Gang-Woo;Shon, Byung-Hyun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.10
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    • pp.4666-4672
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    • 2011
  • Performance of NOx removal in SCR(Selective Catalytic Reduction) process depends on such various factors as catalyst factors (catalyst composition, catalyst form, space velocity, etc.), temperature of exhaust gas, and velocity distribution of exhaust gas. Especially the flow uniformity of gas stream flowing into the catalyst layer is believed to be the most important factor to influence the performance. In this research, the flow characteristics of a SCR process at design stage was simulated, using 3-dimensional numerical analysis method, to confirm the uniformity of the gas stream. In addition, the effects of guide vanes, baffles, and perforated plates on the flow uniformity for the inside and catalyst layer of the reactor were studied in order to optimize the flow uniformity inside the SCR reactor. It was found that the installation of a guide vane at the inlet duct L-tube part and the installation of a baffle at the upper part is very effective in avoiding chaneling inside the reactor. It was also found that additional installation of a perforated plate at the lower part of the potential catalyst layer buffers once more the flow for very uniform distribution of the gas stream.

A Study of Tire Curing Bladder shaping by Using Finite Element Method (유한요소법을 이용한 타이머 Curing Bladder Shaping엔 관한 연구)

  • 김천식;김항우
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1992.10a
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    • pp.3-3
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    • 1992
  • 타이어 Curing공정은 공기압 타이어의 제조시 상당히 정교한 단계를 거쳐서 이루어지며, 이는 타이어 설계에 큰 영향을 줄 뿐만아니라, 타이어의 성능에도 관건이 있다. 본 연구에서는 유한요소법을 이용하여 타이어의 molding 공정을 분석하였다. 유한요소해석 프로그램인 MARC가 Cured 타이어 내부의 Curing Bladder 팽창과정해석에 이용되었다. 비압축성 요소로 Curing Bladder를 모형화하였으며, MARC의 접촉문제해석기법(contact option)을 이용하여 Cured 타이어 내부와 Curing Bladder 외부의 접촉부위를 Simulation하였다. 본 연구의 주요 관심내용으로서는 Curing Bladder의 형상변화에 따른 Curing Bladder의 팽창거동해석과, Cured타이어와 Curing Bladder의 접촉부위에서 얻을 수 있는 접촉압력의 비교.검토이다. 타이어 Curing시 타이어와 Bladder의 Contact과정을 해석하여, 아래와 같은 결과를 도출하였다. Bladder의 형상은 Cylinderical 형상 보다는 Toroidal 형태가 접촉압 분포의 균일성 및 크기 측면에 서 우수한 것으로 판단된다. Curing Bladder의 증심선 부위 보다 이에서 약간 떨어진 부위에서 최대 접촉압력이 발생되며, 이는 타이어 내면의 굴곡현상과 깊은 관련이 있윰 것으로 사료된다. 타이어 Bead부의 Carcass 자연평형현상이 유지된 제품을 얻기위해서는, Side-Bead구간의 접촉압력 증가가 필요하며, 이를 위하여는 Bladder 형상이 Cylinderical 보다는 Toroidal 형태가 유리하고, Bead부의 Gage Down, 전체직경의 증가 및 높이의 증가가 유리한 것으로 판단된다. 본 연구 결과를 이용하여, 타이어 Curing과정에서 발생되는 불량제품의 원인파악 및 타이어 설계자가 원하는 제품생산의 불가능한 원인을 파악하는데 도움을 줄 것이다.를 C의 structure와 pointer를 기반으로 하게끔 변경시키고 이에 따르는 제반 변경 사항을 수정 보완하여 프로그램의 분석을 용이하게 하며 기능의 변경 및 추가가 수월하게 하였고 메모리를 동적으로 관리할 수 있게 하였다. 또한 기존의 smpl에 디버깅용 함수 및 설비(facility) 제어용 함수를 추가하여 시뮬레이션 프로그램 작성을 용이하게 하였다. 예를 들면 who_server(), who_queue(), pop_Q(), push_Q(), pop_server(), push_server(), we(), wf(), printfct() 같은 함수들이다. 또한 동시에 발생되는 사건들의 순서를 조종하기 위해, 동시에 발생할 수 있는 각각의 사건에 우선순위를 두어 이 우선 순위에 의하여 사건 리스트(event list)에서 자동적으로 사건들의 순서가 결정되도록 확장하였으며, 설비 제어방식에 있어서도 FIFO, LIFO, 우선 순위 방식등을 선택할 수 있도록 확장하였다. SIMPLE는 자료구조 및 프로그램이 공개되어 있으므로 프로그래머가 원하는 기능을 쉽게 추가할 수 있는 장점도 있다. 아울러 SMPLE에서 새로이 추가된 자료구조와 함수 및 설비제어 방식등을 활용하여 실제 중형급 시스템에 대한 시뮬레이션 구현과 시스템 분석의 예를 보인다._3$", chain segment, with the activation energy of carriers from the shallow trap with 0.4[eV], in he amorphous regions.의 증발산율은 우기의 기상자료를 이용하여 구한 결과 0.05 - 0.10 mm/hr 의 범위로서 이로 인한 강우손실량은 큰 의미가 없음을 알았다.재발이 나타난 3례의 환자를 제외한 9례 (75%)에서는 현재까지 재발소견을 보이지 않고 있다. 이러한 결과는 다른 보고자들과 유사한 결과를 보이고 있지만 아직까지 증례가 많지 않기 때문에 생존율을 얻

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A Case Study of Monitored Natural Attenuation at the Petroleum Hydrocarbon Contaminated Site : II. Evaluation of Natural Attenuation by Groundwater Monitoring (유류오염부지에서 자연저감기법 적용 사례연구 II. 지하수모니터링에 의한 자연저감 평가)

  • Yun Jeong Ki;Lee Min Hyo;Lee Suk Young;Noh Hoe Jung;Kim Moon Soo;Lee Kang Kun;Yang Chang Sool
    • Journal of Soil and Groundwater Environment
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    • v.9 no.3
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    • pp.38-48
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    • 2004
  • Natural attenuation of petroleum hydrocarbon was investigated at an industrial complex about 45 Km away from Seoul. The three-years monitoring results indicated that the concentrations of DO, nitrate, and sulfate in the contaminated area were significantly lower than the background monitoring groundwater under the non-contaminated area. The results also showed a higher ferrous iron concentration, a lower redox potential, and a higher (neutral) pH in the contaminated groundwater, suggesting that biodegradation of TEX(Toluene, Ethylbenzene, Xylene) is the major on-going process in the contaminated area. Groundwater in the contaminated area is anaerobic, and sulfate reduction is the dominant terminal electron accepting process in the area. The total attenuation rate was about 0.0017∼0.0224day$^{-1}$ and the estimated first-order degradation rate constant(λ) was 0.0008∼0.0106day$^{-1}$ . However, the reduction of TEX concentration in the groundwater was resulted from not only biodegradation but also dilution and reaeration through recharge of uncotaminated surface and groundwater. The natural attenuation was, therefore, found to be an effective, on-going remedial process at the site.

Development of disaster severity classification model using machine learning technique (머신러닝 기법을 이용한 재해강도 분류모형 개발)

  • Lee, Seungmin;Baek, Seonuk;Lee, Junhak;Kim, Kyungtak;Kim, Soojun;Kim, Hung Soo
    • Journal of Korea Water Resources Association
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    • v.56 no.4
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    • pp.261-272
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    • 2023
  • In recent years, natural disasters such as heavy rainfall and typhoons have occurred more frequently, and their severity has increased due to climate change. The Korea Meteorological Administration (KMA) currently uses the same criteria for all regions in Korea for watch and warning based on the maximum cumulative rainfall with durations of 3-hour and 12-hour to reduce damage. However, KMA's criteria do not consider the regional characteristics of damages caused by heavy rainfall and typhoon events. In this regard, it is necessary to develop new criteria considering regional characteristics of damage and cumulative rainfalls in durations, establishing four stages: blue, yellow, orange, and red. A classification model, called DSCM (Disaster Severity Classification Model), for the four-stage disaster severity was developed using four machine learning models (Decision Tree, Support Vector Machine, Random Forest, and XGBoost). This study applied DSCM to local governments of Seoul, Incheon, and Gyeonggi Province province. To develop DSCM, we used data on rainfall, cumulative rainfall, maximum rainfalls for durations of 3-hour and 12-hour, and antecedent rainfall as independent variables, and a 4-class damage scale for heavy rain damage and typhoon damage for each local government as dependent variables. As a result, the Decision Tree model had the highest accuracy with an F1-Score of 0.56. We believe that this developed DSCM can help identify disaster risk at each stage and contribute to reducing damage through efficient disaster management for local governments based on specific events.