• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.135-135
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• 2021

In water resources management, rainfall prediction with high accuracy is still one of controversial issues particularly in countries facing heavy rainfall during wet seasons in the monsoon climate. The aim of this study is to develop an artificial neural network (ANN) for predicting future six months of rainfall data (from April to September 2020) from daily meteorological data (from 1971 to 2019) such as rainfall, temperature, wind speed, and humidity at Seoul, Korea. After normalizing these data, they were trained by using a multilayer perceptron (MLP) as a class of the feedforward ANN with 15,000 neurons. The results show that the proposed method can analyze the relation between meteorological datasets properly and predict rainfall data for future six months in 2020, with an overall accuracy over almost 70% and a root mean square error of 0.0098. This study demonstrates the possibility and potential of MLP's applications to predict future daily rainfall patterns, essential for managing flood risks and protecting water resources.

• 대한기계학회논문집B
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• 제30권12호
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• pp.1188-1195
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• 2006

This paper examines the critical air temperature at which frost formation does not occur on a cold plate in order to improve the efficiency of a heat pump. The critical air temperature on test points is obtained from numerical analysis and a correlation of the critical air temperature is derived as a function of frosting factors (air absolute humidity, air velocity, and cold plate temperature) by least square method. Experiments are carried out to verify the correlation proposed in this study, and the prediction obtained with the correlation agrees well with the experimental data. Based on the correlation, we propose the non-frosting regions according to frosting factors.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2011년도 추계학술대회 초록집
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• pp.63.1-63.1
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• 2011

To analyze the phenomenon of corrosion in the PV module, we experimented damp heat test at $85^{\circ}C$/85% relative humidity(RH) and $65^{\circ}C$/85% RH for 2,000 hours, respectively. We used 30 mini-modules designed of 6inch one cell. Despite of 2,000 hours test, measured $P_{max}$ is not reached failure which is defined less than 80% compared to initial $P_{max}$. Therefore, we calculate proper curve fitting over 2,000 hours. Data less than 80% $P_{max}$ is found and B10 lifetime is calculated by the number of failure specimens and weibull distribution. Using B10 lifetime that the point of failure rate 10% and Peck's model, the predictable equation of lifetime was derived under temperature and humidity condition.

• 한국군사과학기술학회지
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• 제13권2호
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• pp.320-327
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• 2010

The IR signature data of a ship is mainly affected by location, meteorological conditions(atmosphere temperature, wind direction and velocity, humidity etc.), atmospheric transmittance, solar position and ship surface temperature etc. The IR signatures received by a remote sensor at a given temperature and wavelength region is consisted of the self-emitted component directly from the object surface, the reflected component of the solar irradiation at the object surface, and the scattered component by the atmosphere without ever reaching the object surface. Computer simulations for prediction of the IR signatures of ships are very useful to examine the effects of various sensor positions. In this paper, we have acquired the IR signature for different sensor positions by using computer program for prediction of the IR signatures. The numerical results show that the IR signature contrast as compared to the background sea considering the meteorological conditions, solar and sky irradiations.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2020년도 봄 학술논문 발표대회
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• pp.58-59
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• 2020

The change of temperature and humidity in early-age concrete has a great influence on the durability of the structure. In this study, a reliable wireless sensor network system and a concrete embedded type Compressive strength prediction sensor were designed using the Arduino platform. The accuracy of the compressive strength prediction sensor was verified through a mock-up experiment, and it was confirmed that the experiment had sufficient accuracy to be used in the field environment.

• 건설안전기술
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• 통권41호
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• pp.88-101
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• 2007

Recently, the condensation of walls often occurring in domestic high-rise apartment buildings is an important problem. The main purpose of this study is to develop the prediction method for the surface condensation on curtain wall in high-rise apartment buildings. Therefore, in this study, we first analyzed exterior climate factors through the analysis of the Seoul climate data and predicted the change of indoor temperature by using Apache program to find the cause of the condensation state and to prevent condensation. Also, according to this result, exterior climate factors and interior factors, which caused the condensation, was examined. The thermal performance of the curtain wall and the range of potential condensation were analyzed to focus on high-rise apartment buildings through computer simulation programs. The results are as $follows;^1$) The frame edge of curtain wall has a higher U-value than in the center by $30%^2$) Because of stack effect, the rooms on the higher floor have a lower external ventilation rate resulting to a higher relative humidity3) Installing a ventilation system($20m^3$/h. person) makes it possible to have a higher external ventilation rate, resulting to a lower relative humidity.

• 한국정보통신학회논문지
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• 제19권6호
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• pp.1506-1514
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• 2015

본 논문에서는 상황 인식 센서를 활용한 화재 발생 예측 및 탐지 방법을 제안한다. 기존 기상 및 비전 센서 기반의 산불 방재 시스템의 경우 카메라 센서로 획득한 영상을 조명변화에 강인한 색상공간인 HSI(Hue, Saturation, Intensity) 모형으로 변환시켜 처리하여 산불영역에 대한 특징을 추출하고 있다. 그러나 이 경우 단일 카메라 센서가 넓은 범위에 화재를 감지하기 때문에 넓은 범위의 화재가 발생하기 전까지는 화재발생을 감지하는데 어려움이 있다. 따라서 본 논문에서는 센서를 활용하여 실시간으로 온도, 습도, Co2, 불꽃유무정보를 습득하여 화재를 판단하는 알고리즘과 그에 따른 화재의 확산경로와 속도예측 및 안전구역 확보 알고리즘을 제안한다. 제안된 알고리즘은 복합적 인 상황에 따라 부여된 가중치를 수집된 데이터에 부여하여 화재를 판단하고, 시간에 따른 상황인식 분석을 통해 화재 이동방향과 속도를 예측하여 안전구역을 확보하는 기법이다.

• 한국환경생태학회지
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• 제32권4호
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• pp.413-424
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• 2018

본 연구에서는 경주 남산을 대상으로 지형구조 및 해발고도가 음이온 발생량에 미치는 영향을 분석하였다. 분석결과, 기온은 능선부($9.82^{\circ}C$) > 계곡부($8.44^{\circ}C$), 상대습도는 계곡부(59.01%) > 능선부(58.64%), 풍속은 능선부(0.63m/s) > 계곡부(0.37m/s), 일사량은 능선부($34.40W/m^2$) > 계곡부($14.69W/m^2$)로 나타났다. 음이온의 경우 계곡부($636.81ea/cm^3$) > 능선부($580.04ea/cm^3$)로 계곡부가 더 높은 음이온 발생량을 보였다. 해발고도와의 상관성 분석 결과, 계곡부에서는 기온, 상대습도, 일사량, 음이온 발생량과의 상관성이 검증되었으며, 상대습도, 일사량, 음이온 발생량과는 정의 상관관계, 기온과 부의 상관관계가 나타났다. 능선부에서는 기온, 상대습도, 풍속, 일사량, 음이온 발생량과의 상관성이 검증되었으며, 상대습도, 일사량, 음이온 발생량과는 정의 상관관계, 기온, 풍속과는 부의 상관관계가 나타났다. 회귀분석 결과, 기온의 경우 계곡부는 y= -0.006x+9.663 (x=해발고도, y=기온), 능선부의 경우 y= -0.009x+11.595(x=해발고도, y=기온)의 예측식을 얻었다. 상대습도의 경우 계곡부는 y= 0.027x+53.561 (x=해발고도, y=상대습도), 능선부의 경우 y= 0.008x+56.646 (x=해발고도, y=상대습도)의 예측식을 얻었다. 음이온 발생량의 경우 계곡부는 y= 0.577x+521.508 (x=해발고도, y=음이온 발생량), 능선부의 경우 y= 0.605x+549.068 (x=해발고도, y=음이온 발생량)의 예측식을 얻었다.

• 대기
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• 제28권3호
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• pp.263-272
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• 2018

The high-resolution ocean surface wind vector produced by scatterometer was assimilated within the Local Ensemble Transform Kalman Filter (LETKF) in Korea Institute of Atmospheric Prediction Systems (KIAPS). The Advanced Scatterometer (ASCAT) on Metop-A/B wind data was processed in the KIAPS Package for Observation Processing (KPOP), and a module capable of processing surface wind observation was implemented in the LETKF system. The LETKF data assimilation cycle for evaluating the performance improvement due to ASCAT observation was carried out for approximately 20 days from June through July 2017 when Typhoon Nepartak was present. As a result, we have found that the performance of ASCAT wind vector has a clear and beneficial effect on the data assimilation cycle. It has reduced analysis errors of wind, temperature, and humidity, as well as analysis errors of lower troposphere wind. Furthermore, by the assimilation of the ASCAT wind observation, the initial condition of the model described the typhoon structure more accurately and improved the typhoon track prediction skill. Therefore, we can expect the analysis field of LETKF will be improved if the Scatterometer wind observation is added.

• 한국산림과학회지
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• 제94권6호
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• pp.481-487
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• 2005

이 연구에서는 지표화 중심의 산불확산예측 알고리즘을 기반으로 GIS 환경에서 운용이 가능한 지표화 확산예측모델을 개발하였다. 이 모델은 지형, 연료, 기상 등 산불환경인자를 분석하고 입력하는 부분과 시간에 따라 확산속도, 화선에서의 산불강도, 연소면적을 예측하는 지표화 확산예측 부분, 마지막으로 예측결과를 사용자에게 제시하는 출력 부분으로 구성되었다. 산불확산속도를 계산하기 위해서 산불행동에 영향을 미치는 산불환경인자중에서 지형인자는 경사, 기상인자는 풍속, 풍향, 실효습도를 고려하였다. 또한 연료인자는 수치임상도를 이용하여 연료깊이, 연료량, 소화습도를 계산할 수 있는 연료모듈을 개발하여 입력되도록 하였다. 연료습도는 실효습도, 최고온도, 강수량, 일일 적산량의 함수관계로 추정하였다. 모델을 2002년 청양에서 발생한 산불에 적용한 결과 확산속도에 대해 61%의 일치도를 보였다.