• 대기
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• 제29권2호
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• pp.183-196
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• 2019

High-quality and high-resolution meteorological information is essential to reduce damages due to disastrous weather phenomena such as flash flood, strong wind, and heat/cold waves. There are many meteorological observation stations operated by Korea Meteorological Administration (KMA) in Seoul Metropolitan Area (SMA). Nonetheless, they are still not enough to represent small-scale weather phenomena like convective storm cells due to its poor resolution, especially over urban areas with high-rise buildings and complex land use. In this study, feasibilities to use additional pre-existing networks (e.g., operated by local government and private company) are tested by investigating the effects of network density on the gridded horizontal distribution of two meteorological variables (temperature and precipitation). Two heat wave event days and two precipitation events are chosen, respectively. And the automatic weather station (AWS) networks operated by KMA, local-government, and SKTechX in Incheon area are used. It is found that as network density increases, correlation coefficients between the interpolated values with a horizontal resolution of 350 m and observed data also become large. The range of correlation coefficients with respect to the network density shows large in nighttime rather than in daytime for temperature. While, the range does not depend on the time of day, but on the precipitation type and horizontal distribution of convection cells. This study suggests that temperature and precipitation sensors should be added at points with large horizontal inhomogeneity of land use or topography to represent the horizontal features with a resolution higher than 350 m.

• Nuclear Engineering and Technology
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• 제54권10호
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• pp.3855-3863
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• 2022

An evaluation of the radiation shielding performance of high-Z-particle-loaded polylactic acid (PLA) composite materials was pursued. Specimens were produced via fused deposition modeling (FDM) using copper-PLA, steel-PLA, and BaSO₄-PLA composite filaments containing 82.7, 75.2, and 44.6 wt% particulate phase contents, respectively, and were tested under broad-band flash x-ray conditions at the Sandia National Laboratories HERMES III facility. The experimental results for the mass attenuation coefficients of the composites were found to be in good agreement with GEANT4 simulations carried out using the same exposure conditions and an atomistic mixture as a model for the composite materials. Further simulation studies, focusing on the Cu-PLA composite system, were used to explore a shield design parameter space (in this case, defined by Cu-particle loading and shield areal density) to assess performance under both high-energy photon and electron fluxes over an incident energy range of 0.5-15 MeV. Based on these results, a method is proposed that can assist in the visualization and isolation of shield parameter coordinate sets that optimize performance under targeted radiation characteristics (type, energy). For electron flux shielding, an empirical relationship was found between areal density (AD), electron energy (E), composition and performance. In cases where ${\frac{E}{AD}}{\geq}2MeV{\bullet}cm{\bullet}g^{-1}$, a shield composed of >85 wt% Cu results in optimal performance. In contrast, a shield composed of <10 wt% Cu is anticipated to perform best against electron irradiation when ${\frac{E}{AD}}<2MeV{\bullet}cm{\bullet}g^{-1}$.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.145-145
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• 2022

Availability of abundant water resources data in developing countries is a great concern that has hindered the adoption of deep learning techniques (DL) for disaster prevention and mitigation. On the contrary, over the last two decades, a sizeable amount of DL publication in disaster management emanated from developed countries with efficient data management systems. To understand the current state of DL adoption for solving water-related disaster management in developing countries, an extensive bibliometric review coupled with a theory-based analysis of related research documents is conducted from 2003 - 2022 using Web of Science, Scopus, VOSviewer software and PRISMA model. Results show that four major disasters - pluvial / fluvial flooding, land subsidence, drought and snow avalanche are the most prevalent. Also, recurrent flash floods and landslides caused by irregular rainfall pattern, abundant freshwater and mountainous terrains made India the only developing country with an impressive DL adoption rate of 50% publication count, thereby setting the pace for other developing countries. Further analysis indicates that economically-disadvantaged countries will experience a delay in DL implementation based on their Human Development Index (HDI) because DL implementation is capital-intensive. COVID-19 among other factors is identified as a driver of DL. Although, the Long Short Term Model (LSTM) model is the most frequently used, but optimal model performance is not limited to a certain model. Each DL model performs based on defined modelling objectives. Furthermore, effect of input data size shows no clear relationship with model performance while final model deployment in solving disaster problems in real-life scenarios is lacking. Therefore, data augmentation and transfer learning are recommended to solve data management problems. Intensive research, training, innovation, deployment using cheap web-based servers, APIs and nature-based solutions are encouraged to enhance disaster preparedness.

• 한국재료학회지
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• 제34권5호
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• pp.223-234
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• 2024

This review explores the potential of pillared bentonite materials as solid acid catalysts for synthesizing diethyl ether, a promising renewable energy source. Diethyl ether offers numerous environmental benefits over fossil fuels, such as lower emissions of nitrogen oxides (NO_x) and carbon oxides (CO_x) gases and enhanced fuel properties, like high volatility and low flash point. Generally, the synthesis of diethyl ether employs homogeneous acid catalysts, which pose environmental impacts and operational challenges. This review discusses bentonite, a naturally occurring alumina silicate, as a heterogeneous acid catalyst due to its significant cation exchange capacity, porosity, and ability to undergo modifications such as pillarization. Pillarization involves intercalating polyhydroxy cations into the bentonite structure, enhancing surface area, acidity, and thermal stability. Despite the potential advantages, challenges remain in optimizing the yield and selectivity of diethyl ether production using pillared bentonite. The review highlights the need for further research using various metal oxides in the pillarization process to enhance surface properties and acidity characteristics, thereby improving the catalytic performance of bentonite for the synthesis of diethyl ether. This development could lead to more efficient, environmentally friendly synthesis processes, aligning with sustainable energy goals.

• 한국화재소방학회논문지
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• 제26권5호
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• pp.21-27
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• 2012

본 연구에서는 그라스울 샌드위치패널의 연소특성을 판단하기 위하여 밀도와 두께가 다른 총 6종류(밀도: 48/64 K, 두께: 50/75/100 T)의 시편을 선정하여, KS F ISO 9705 시험법을 준용하여 실물화재 시험을 실시하였다. 실물화재 시험은 $2.4(L){\times}3.6(W){\times}2.4(H)m$ 크기의 화재실 내부에 시험체를 설치하여 프로판 버너에 의해 시편을 화염에 노출시켜 연소특성을 판단하게 된다. 총 25분에 시험 시간 동안 프로판 버너는 100 kW(10분), 300 kW(10분)로 출력되며, 시험을 통해 열방출률, 열류량, 내부 온도가 측정된다. 실물화재 시험을 실시한 결과, 버너 열량을 포함하여 각 시편의 최대 열방출률은 333.2~365.5 kW, 최대 열류량은 12.4~12.9 kW/$m^2$로 나타났으며, 최대 내부온도는 모든 시편에서 $500^{\circ}C$를 초과하지 않았다. 실물화재 시험 중에 플래시오버 현상은 발생하지 않았으며, 각 시편의 열방출률, 열류량, 내부 온도 측정결과 시편의 밀도 및 두께에 따른 차이점은 나타나지 않았다.

• 한국자원식물학회지
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• 제29권1호
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• pp.128-135
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• 2016

귀리 종자에 감마선을 조사한 후 발아율과 생존율 및 초기 생장 특성을 조사하여 돌연변이 유도를 위한 적정 방사선량을 구명하고, DNA 손상 정도를 평가 하였다. 연구의 결과, 발아율은 500 Gy 이상의 선량에서 급격히 감소하였고, 단순회귀분석으로 평가한 LD50 선량은 392 Gy였다. 감마선 조사 30일 후 초장, 생체중, 근장, 분얼수를 조사한 결과 대조구와 100∼200 Gy 처리구간 차이가 없었으며, RD₅₀ 선량은 초장과 생체중은 411 Gy로 동일하였고, 근장 403 Gy, 분얼수 394 Gy였다. LD₅₀과 RD₅₀ 선량을 바탕으로 결정한 귀리의 적정 조사선량은 300~400 Gy였다. Comet assay로 DNA 손상 정도를 측정한 결과, 파종 7일 후에는 모든 감마선 처리구가 대조구와 비교하여 DNA 손상이 크게 나타났으며, 파종 30일 후에는 300 Gy 이상의 처리구에서 대조구보다 유의성 있는 DNA 손상이 관찰되어 생육형질과 동일한 경향이었다. 선량과 생장, 코멧분석 결과간의 상관관계를 분석한 결과, 머리의 비율을 제외한 다른 조사 항목에서 높은 상관관계를 나타내었다. M₂ 세대의 생육특성은 400 Gy 이상에서 생육이 감소하였고, 돌연변이 양상은 주로 고선량에서 단간, 불임이었다.

• 정보처리학회논문지A
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• 제16A권5호
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• pp.357-368
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• 2009

플래시 메모리와 하드디스크의 저장 공간 제약을 문제를 극복하기 위한 방법으로 모바일 IP 스토리지가 제안되었다. 모바일 IP 스토리지는 무선 IP 네트워크를 통하여 모바일 장치에 거의 무제한적인 저장 공간을 제공한다. 하지만, 모바일 IP 스토리지를 이용한 멀티미디어 컨텐츠 스트리밍 시 무선랜 장치의 지속적인 전력소모로 인해 모바일 장치의 배터리 수명이 급격히 감소하는 문제가 발생한다. 본 논문에서는 모바일 IP 스토리지를 통하여 멀티미디어 컨텐츠를 실행할 시에 무선랜 장치의 전력을 효율적으로 제어할 수 있는 기법을 제안한다. 제안된 기법은 선반입 버퍼 입출력 모듈, 무선랜 장치 전력제어 모듈, 선반입 버퍼 재구성 모듈로 구성되어 있다. 또한, 제안된 기법은 멀티미디어 컨텐츠의 품질에 적응적으로 선반입 버퍼의 크기를 자동적으로 결정하고 멀티미디어 컨텐츠가 실행되는 동안 On-Off 동작을 기반으로 무선랜 장치 전력 상태를 동적으로 제어한다. 제안된 기법의 성능을 임베디드 리눅스 2.6.11, 인텔 iSCSI 참조코드, 무선랜 장치를 이용하는 PXA270기반 모바일 장치 상에서 평가한다. 다양한 실험을 통하여 제안된 기법이 전력제어를 하지 않을 때에 비해 QVGA급 멀티미디어 컨텐츠 실행 시 무선랜 카드의 에너지 소모를 최대 8.5배 정도 감소시킴을 보인다.

• 방사선산업학회지
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• 제8권2호
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• pp.89-95
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• 2014

This study was conducted to determine the optimal dose of gamma-ray on the growth and nucleus DNA damage for mutation breeding in licorice. Gamma-rays irradiated to dry seeds with various doses (0 to 1000 Gy). Significant decreases in germination rate (%), survival rate (%) and growth characteristics (plant height, number of leaves, root length and fresh weight) were observed by dose of increased. $LD_{50}$ (lethal dose) was approximately 400 Gy to 500 Gy. Also, reduction doses ($RD_{50}$) of plant height, number of leaves, root length and flash weight were 428 Gy, 760 Gy, 363 Gy and 334 Gy, respectively. It is supplest that the optimal dose of gamma irradiation for licorice mutation induction might be about 400 Gy in this study. We also conducted comet assay to observe nucleus DNA damage due to gamma irradiation. In comet assay, a clear difference was identified over 300 Gy treatments. With increasing doses of gamma-ray in the range of 100 to 1000 Gy, the rate of head DNA was decreased significantly from 92.88% to 73.09%. Tail length(${\mu}m$) was increased as the dose of increased over 300 Gy. Growth characteristics (Germination rate, Survival rate, plant height, number of leaves, root length and fresh weight) were highly negatively ($P{\leq}0.01$) correlated with dose. While the tail length was highly positively ($P{\leq}0.01$) correlated with dose.

• 대한전자공학회논문지SD
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• 제46권3호
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• pp.75-85
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• 2009

본 논문에서는 two-carrier W-CDMA 응용과 같이 고해상도, 저전력 및 소면적을 동시에 요구하는 3G 통신 시스템 응용을 위한 13비트 100MS/s 0.13um CMOS ADC를 제안한다. 제안하는 ADC는 4단 파이프라인 구조를 사용하여 고해상도와 높은 신호처리속도와 함께 전력 소로 및 면적을 최적화하였다. 입력 단 SHA 회로에는 면적 효율성을 가지멸서 고속 고해상도로 동작하는 게이트-부트스트래핑 회로를 적용하여 1.0V의 낮은 전원 전압동작에서도 신호의 왜곡없이 Nyquist 대역 이상의 입력 신호를 샘플링할 수 있도록 하였다. 입력 단 SHA 및 MDAC에는 낮은 임피던스 기반의 캐스코드 주파수 보상 기법을 적용한 2단 증폭기 회로를 사용하여 Miller 주파수 보상 기법에 비해 더욱 적은 전력을 소모하면서도 요구되는 동작 속도 및 안정적인 출력 조건을 만족시키도록 하였으며, flash ADC에 사용된 래치의 경우 비교기의 입력 단으로 전달되는 킥-백 잡음을 줄이기 위해 입력 단과 출력 노드를 클록 버퍼로 분리한 래치 회로를 사용하였다. 한편, 제안하는 시제품 ADC에는 기존의 회로와는 달리 음의 론도 계수를 갖는 3개의 전류만을 사용하는 기준 전류 및 전압 발생기를 온-칩으로 집적하여 잡음을 최소화하면서 시스템 응용에 따라 선택적으로 다른 크기의 기준 전압 값을 외부에서 인가할 수 있도록 하였다. 제안하는 시제품 ADC는 0.13um 1P8M CMOS 공정으로 제작되었으며, 측정된 DNL 및 INL은 13비트 해상도에서 각각 최대 0.70LSB, 1.79LSB의 수준을 보이며, 동적 성능으로는 100MS/s의 동작 속도에서 각각 최대 64.5dB의 SNDR과 78.0dB의 SFDR을 보여준다. 시제품 ADC의 칩 면적은 $1.22mm^2$이며, 1.2V 전원 전압과 100MS/s의 동작 속도에서 42.0mW의 전력을 소모하여 0.31pJ/conv-step의 FOM을 갖는다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2002년도 학술발표회 논문집(I)
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• pp.43-50
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• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict streamflow and flash floods. Previously, neural networks were used to develop a Quantitative Precipitation Forecasting (QPF) model that highly improved forecasting skill at specific locations in Pennsylvania, using both Numerical Weather Prediction (NWP) output and rainfall and radiosonde data. The objective of this study was to improve an existing artificial neural network model and incorporate the evolving structure and frequency of intense weather systems in the mid-Atlantic region of the United States for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as life time, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. The new Quantitative Flood Forecasting (QFF) model was applied to predict streamflow peaks with lead-times of 18 and 24 hours over a five year period in 4 watersheds on the leeward side of the Appalachian mountains in the mid-Atlantic region. Threat scores consistently above .6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 4％ and up to 6％ were attained for the 24 hour lead-time forecasts. This work demonstrates that multisensor data cast into an expert information system such as neural networks, if built upon scientific understanding of regional hydrometeorology, can lead to significant gains in the forecast skill of extreme rainfall and associated floods. In particular, this study validates our hypothesis that accurate and extended flood forecast lead-times can be attained by taking into consideration the synoptic evolution of atmospheric conditions extracted from the analysis of large-area remotely sensed imagery While physically-based numerical weather prediction and river routing models cannot accurately depict complex natural non-linear processes, and thus have difficulty in simulating extreme events such as heavy rainfall and floods, data-driven approaches should be viewed as a strong alternative in operational hydrology. This is especially more pertinent at a time when the diversity of sensors in satellites and ground-based operational weather monitoring systems provide large volumes of data on a real-time basis.