• Journal of Climate Change Research
• /
• v.9 no.4
• /
• pp.423-433
• /
• 2018

Particulate matter air pollution is a serious problem affecting human health and visibility. The variations in $PM_{10}$ concentrations are influenced by not only local emission sources, but also atmospheric circulation conditions. In this study, we investigate the temporal features of $PM_{10}$ concentrations in South Korea and the atmospheric circulation patterns associated with high concentration episodes of $PM_{10}$ during winter (December-January-February) 2001-2016. Based on those analyses, a Korea Particulate matter Index (KPI) is developed to represent the large-scale atmospheric pattern associated with high concentration episodes of $PM_{10}$. The atmospheric patterns are characterized by persistent high-pressure anomalies, weakened lower-level north-westerly anomalies, and northward shift of the upper-level meridional wind anomalies near the Korean Peninsula. To evaluate the change in occurrence of high concentration episodes of $PM_{10}$ under a possible future warmer climate, we apply KPI analysis to CMIP5 climate simulations. Here, historical and two representative concentration pathway (RCP) scenarios (RCP 4.5 and RCP 8.5) are used. It is found that the occurrence of atmospheric conditions favorable for high $PM_{10}$ concentration episodes tends to increase over South Korea in response to climate change. This suggests that large-scale atmospheric circulation changes under future warmer climate can contribute to increasing high $PM_{10}$ concentration episodes in South Korea.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.8 no.4
• /
• pp.325-334
• /
• 2006

Understanding the airflow characteristics within the canopy structure installed between closely adjacent tunnels either for light adaptation or for protection from snow hazards is required for the normal ventilation as well as safety system design. Grade, horizontal alignment, cross-sectional area and shape are known to substantially influence the fire smoke behavior and their influences raise great concern for the safety design. This paper aims at studying the effects of tunnel geometrical characteristics and canopy installation on the ventilation and fire propagation through CFD analysis. In the case of 145m long canopy, 50% opening ratio is preferred with respect to the airflow pattern and ventilation efficiency. When a 20MW fire occurs in a 1.8km-long tunnel and four 1250mm reversible jet fans are instantly turned on, smoke concentration at 40m downstream of the fire decrease 13% for the upgrade tunnel with 2% gradient and increases 20% for -2% gradient, compared to the standard horizontal tunnel. Backlayering is observed within 45m-long segment toward the entrance in 2% down-graded tunnel. In a rectangular tunnel, there is no significant difference of smoke concentration as well as velocity profile from the standard crown tunnel. Three-laned tunnel shows lower level of both profiles and backlayering is detected up to 50m upstream of the fire, while the risky situation rapidly disappears thereafter.

• Fire Science and Engineering
• /
• v.28 no.6
• /
• pp.13-21
• /
• 2014

Forest fire has a number of variables and since the effects of wind fields are bigger than any other variables, it is essential to know wind direction and velocity for the forest fire extinguishing techniques and the prediction of fire spread. With regards to the local area that has a high chance of forest fire, the data from meteorological observatory in the area is used for the estimation of wind velocity. It is relatively easy to obtain automatic weather station (AWS) data which are available for the whole nation. There is a chance that the data from the weather station may be different with the actual data at the mountain areas. In this study simply shaped hills (Sae-byeol hill of Jeju Island and port Ma-geum in An-myeon Island in the sea side) were selected as the experimental locations to minimize the distortion of the wind field by the adjacent geographic features. Spot measurements and analysis of computational fluid dynamics (CFD) for the given geographic features were conducted to examine and compare their consistency. As a conclusion It is possible to predict wind patterns in these simple locations.

• Journal of Conservation Science
• /
• v.34 no.5
• /
• pp.387-396
• /
• 2018

Exposure to the natural environment can cause damage to domestic wooden cultural assets, such as temples. Deterioration is accelerated by biological damage and various environmental factors. In this study, meteorological factors were monitored by equipment installed at Beopjusa temple of Boeun province and Seonamsa temple of Suncheon province. A statistical model was applied to these data to predict the meteorological factors and to compare the predictive performance of each meteorological factor. The resulting correlation coefficient between air and dew point temperatures was highest, at 0.95, while the correlation coefficient for relative humidity had a moderate value(0.65) at both the Beopjusa and Seonamsa temples. Thus, a general linear model was found to be suitable for predicting air and dew point temperatures. An analysis of correlation between meteorological factors showed that there was strong positive correlation between air temperature and dew point temperature, and between solar radiation and evaporation at both sites. There was a weak positive correlation between air temperature and evaporation at Beopjusa temple. Wind speed was negatively correlated with both air temperature and relative humidity at Seonamsa temple. The wind speed at this location is higher than average in winter and lower than average in summer, and it was hypothesized that the low wind speed plays a role in reducing water evaporation in summer, when both air temperature and relative humidity are high. As a result, damage to the wooden buildings of Seonamsa temple is accelerated.

• Korean Journal of Remote Sensing
• /
• v.11 no.2
• /
• pp.17-27
• /
• 1995

One of the world widely used methods in determining the intensity of a typhoon is Dvorak's technique. By applying the Dvorak's method to the typhoons which affected our country in various degress and extents without regard to their individual severity, we estimated their intensity for six different cases of typhoons. We have derived a regression equation of estimating the central pressures and maximum wind speeds for the six selected typhoons. Their intensity was estimated from the Dvork's method using GMS satellite image data. The derived equation has tested to typhoon ORCHID and the computed values have been compared with the direct observations in its central pressure and maximum wind speed. The computed values in the Dvork's method are smaller in their magnitudes than the observed corresponding values. But their relative magnitudes do not change so much at each different time step. But our results are significantly different from those of NOAA and JMA. The cause of differences are not investigated in depth in this analysis.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.88-88
• /
• 2021

최근 수자원과 수질관리 분야에 자료기반 머신러닝 모델과 딥러닝 모델의 활용이 급증하고 있다. 그러나 딥러닝 모델은 Blackbox 모델의 특성상 고전적인 질량, 운동량, 에너지 보존법칙을 고려하지 않고, 데이터에 내재된 패턴과 관계를 해석하기 때문에 물리적 법칙을 만족하지 않는 예측결과를 가져올 수 있다. 또한, 딥러닝 모델의 예측 성능은 학습데이터의 양과 변수 선정에 크게 영향을 받는 모델이기 때문에 양질의 데이터가 제공되지 않으면 모델의 bias와 variation이 클 수 있으며 정확도 높은 예측이 어렵다. 최근 이러한 자료기반 모델링 방법의 단점을 보완하기 위해 프로세스 기반 수치모델과 딥러닝 모델을 결합하여 두 모델링 방법의 장점을 활용하는 연구가 활발히 진행되고 있다(Read et al., 2019). Process-Guided Deep Learning (PGDL) 방법은 물리적 법칙을 반영하여 딥러닝 모델을 훈련시킴으로써 순수한 딥러닝 모델의 물리적 법칙 결여성 문제를 해결할 수 있는 대안으로 활용되고 있다. PGDL 모델은 딥러닝 모델에 물리적인 법칙을 해석할 수 있는 추가변수를 도입하며, 딥러닝 모델의 매개변수 최적화 과정에서 Cost 함수에 물리적 법칙을 위반하는 경우 Penalty를 추가하는 알고리즘을 도입하여 물리적 보존법칙을 만족하도록 모델을 훈련시킨다. 본 연구의 목적은 대청호의 수심별 수온을 예측하기 위해 역학적 모델과 딥러닝 모델을 융합한 PGDL 모델을 개발하고 적용성을 평가하는데 있다. 역학적 모델은 2차원 횡방향 평균 수리·수질 모델인 CE-QUAL-W2을 사용하였으며, 대청호를 대상으로 2017년부터 2018년까지 총 2년간 수온과 에너지 수지를 모의하였다. 기상(기온, 이슬점온도, 풍향, 풍속, 운량), 수문(저수위, 유입·유출 유량), 수온자료를 수집하여 CE-QUAL-W2 모델을 구축하고 보정하였으며, 모델은 저수위 변화, 수온의 수심별 시계열 변동 특성을 적절하게 재현하였다. 또한, 동일기간 대청호 수심별 수온 예측을 위한 순환 신경망 모델인 LSTM(Long Short-Term Memory)을 개발하였으며, 종속변수는 수온계 체인을 통해 수집한 수심별 고빈도 수온 자료를 사용하고 독립 변수는 기온, 풍속, 상대습도, 강수량, 단파복사에너지, 장파복사에너지를 사용하였다. LSTM 모델의 매개변수 최적화는 지도학습을 통해 예측값과 실측값의 RMSE가 최소화 되로록 훈련하였다. PGDL 모델은 동일 기간 LSTM 모델과 동일 입력 자료를 사용하여 구축하였으며, 역학적 모델에서 얻은 에너지 수지를 만족하지 않는 경우 Cost Function에 Penalty를 추가하여 물리적 보존법칙을 만족하도록 훈련하고 수심별 수온 예측결과를 비교·분석하였다.

• Journal of the Korean association of regional geographers
• /
• v.11 no.5
• /
• pp.383-390
• /
• 2005

The purpose of this study is to show distribution pattern of comfortable Indoor-Temperature in South Korea based on 10-days normal data(June 3rd, July 2nd, August 1st). Comfortable Indoor-Temperature values and Heat flow equation values for the 68 stations are constructed to show how man tend to feel in various areas. In the early summer, comfortable Indoor-Temperature is very low in Taegwallong regions and the Southern interior regions due to the influence of the orographic effects or the altitude. In the hot summer, All regions except Taegwallong and Central interior regions have been the high value. These are largely derived from the low Clo-values due to the stable weather with the highest insolation, humidity and strong radiation heat by the North Pacific Anticyclone appears in Eastern Asia.

• Journal of Korean Society of Transportation
• /
• v.34 no.5
• /
• pp.394-408
• /
• 2016

This study aims to study the impact of weather conditions and locational characteristics of bike stations on the usage of public bike sharing system for efficient deployment and operation of public bike systems. Linear regression analysis is used to estimate the usage of public bikes of Goyang city. The statistical analysis shows that the usage rate increases with average temperature and decreases under high wind (over 7m/s) or high temperature (over $29^{\circ}$) condition. The usage rate of public bike sharing system can be differentiated by locational characteristics of bike station such as residential area, commercial area, park, school, and metro station. The usage rate increases in park and commercial areas from 10 AM to 3 PM, while it increases in school areas from 3 PM to 5 PM. Public bikes are highly used near the metro station from 5 PM to 8 PM. The stations in parks are highly used in late night, and the usage rate in CBD area increases after the midnight.

• Fire Science and Engineering
• /
• v.31 no.4
• /
• pp.52-58
• /
• 2017

This study investigated the pressure difference distribution and the flow characteristics among room, ancillary room, and stair case by carrying out the numerical simulations on the air flow inside the pressurized air supply smoke control system. Numerical simulations were conducted to analyze pressure and velocity distribution of compartments by pressurized air supply for the air-leakage test facility which was built to measure the effective leakage area. In this study, the leakage of air was considered by locating the narrow slit onto fire door and window of room. Simulated results using this method precisely followed the previous experimental results for the pressure differences between the stair case and ancillary room. Predicted results showed that the local leakage of air rarely affected the overall flow pattern and pressure distribution. Although the average velocity over the door between room and ancillary room satisfied the regulation for fire safety, it was certified the unsafe outflow to ancillary room could be occurred in the local position such as the upper part of the door.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2019.05a
• /
• pp.100-100
• /
• 2019

최근 대기 중 미세먼지의 농도가 높은 일수가 급증하면서, 미세먼지를 저감하고자 하는 연구가 활발히 이루어지고 있다. 미세먼지는 주로 자동차 혹은 공장 등 인간 활동에 의한 오염물질 배출에 의해 발생하는 것으로 알려져 있으며, 태양복사에너지, 토양수분, 강우, 풍속 등의 수문기상학적 인자에 의해 발생, 이동, 소멸의 과정을 거친다. 현재 우리나라에서는 미세먼지 농도를 관측하기 위해 지점 기반의 관측소를 운영하고 있으며, 관측소가 위치하지 않은 지역의 미세먼지 농도는 선형 보간법 등을 활용한 내삽 기법을 통해 제공하고 있다. 그러나 미세먼지 농도는 다양한 수문기상인자들의 영향에 의한 차이가 크게 나타나기 때문에 지점 기반의 자료로는 해당 지역의 미세먼지 농도를 추정하는 데 어려움이 많다. 본 연구에서는 미세먼지의 공간적인 분포를 추정하고자 MODerate resolution Imaging Spectroradiometer (MODIS) 에어로졸 자료와 Global Land Data Assimilation System (GLDAS) 수문기상인자를 활용하여 미세먼지 농도에 영향을 주는 것으로 판단되는 다양한 수문기상인자들과의 상관성을 분석하였다. 미세먼지와 각 인자간의 상관성을 분석하여 높은 상관성을 갖는 수문기상인자들을 도출하고 최적의 선형회귀분석 모델을 구축하기 위해 베이지안 모델 평균(Bayesian Model Averaging, BMA)을 사용하였으며, 지점 데이터와의 비교를 통해 활용성을 검증하였다. 전체적으로 수문기상인자를 사용한 선형회귀분석 결과에서는 미세먼지농도 변화의 경향을 반영하고 있는 것을 확인할 수 있었으나, 계절별, 지역별 등 대기 특성을 고려하지 않아 각 기간의 급격한 농도 변화를 감지하기에 어려움이 있었다. 이러한 연구를 바탕으로 수문기상인자와 미세먼지 농도의 패턴이 더욱 정확히 분석된다면, 미세먼지 농도 모니터링과 정확한 예보 시스템의 구축에 효과적으로 활용 될 것으로 기대된다.