• 자원ㆍ환경경제연구
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• 제11권3호
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• pp.447-463
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• 2002

The heat demand prediction is an essential issue in management of district heating system. Without an accurate prediction through the lead-time period, it might be impossible to make a rational decision on many issues such as heat production scheduling and heat exchange among the plants which are very critical for the district heating company. The heat demand varies with the temperature as well as the time nonlinearly. And the parametric specification of the heat demand model would cause a misspecification bias in prediction. A nonparametric model for the short-term heat demand prediction has been developed as an alternative to avoiding the misspecification error and tested with the actual data. The prediction errors are reasonably small enough to use the model to predict a few hour ahead heat demand.

• 태양에너지
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• 제7권2호
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• pp.37-53
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• 1987

This study has been prepared for the purpose of developing the system performance prediction method of natural circulation solar hot water system. The storage tank of the natural circulation solar hot water system equipped with flat-plate solar collector is located at higher elevation than the solar collectors. Therefor, the storage tank temperature distribution formed accordance with configuration of storage tank by flow rate of circulating fluid affect system collection efficiency. In this study measure the storage tank temperature distribution with various experimental system under real sun condition and present the theoretical prediction method of the storage tank temperature. Moreover measure the flow rate not only day-time but also night-time reverse flow rate with die injection visual flow meter. Main conclusion obtain from the present study is as follows; 1) The storage tank temperature distribution above the connecting pipe connection position is the same as that of the fully mixed tank and below the connection position is the same as that of stratified tank. 2) The system performance sensitive to the storage tank temperature distribution. Therefore detailed tank model is necessary. Average storage tank temperature can be calculate 3% and storage tank temperature profile can get less than 10% difference with this model system.

• 한국정보기술학회논문지
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• 제17권9호
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• pp.11-17
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• 2019

최근 들어 동해안에서 너울성 파도에 의한 손실이 빈번히 발생하고 있다. 너울성 파도는 다양한 요인들이 결합되어 발생하기 때문에 예측이 어렵다. 본 연구에서는 머신러닝 기술에 기초하여 동해안에서 너울성 파도의 발생을 예측하는 모델을 제안하였다. 모델 개발을 위해 포항 신항의 하역중단 데이터 및 신항 부근의 기압, 풍속, 풍향, 수온 등의 기상자료를 수집하였다. 수집한 데이터로부터 너울발생에 중요한 영향을 미치는 변수들을 선별하였으며, 모델 개발을 위해 다양한 머신러닝 예측 알고리즘들을 테스트 하였다. 그 결과 조위, 수온, 기압이 너울 발생 예측을 위한 주요 변수로 확인이 되었고, Random Forest 모델이 가장 우수한 성능을 보였으며. 모델의 예측 정확도는 88.6%이다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.136-136
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• 2022

This study investigates the possibility of coupling empirical mode decomposition (EMD) for runoff prediction from machine learning (ML) models. Here, support vector regression (SVR) and convolutional neural network (CNN) were considered for ML algorithms. Precipitation (P), minimum temperature (Tmin), maximum temperature (Tmax) and their intrinsic mode functions (IMF) values were used for input variables at a monthly scale from Jan. 1973 to Dec. 2020 in the Grand river basin, Canada. The support vector machine-recursive feature elimination (SVM-RFE) technique was applied for finding the best combination of predictors among input variables. The results show that the proposed method outperformed the individual performance of SVR and CNN during the training and testing periods in the study area. According to the correlation coefficient (R), the EMD-SVR model outperformed the EMD-CNN model in both training and testing even though the CNN indicated a better performance than the SVR before using IMF values. The EMD-SVR model showed higher improvement in R value (38.7%) than that from the EMD-CNN model (7.1%). It should be noted that the coupled models of EMD-SVR and EMD-CNN represented much higher accuracy in runoff prediction with respect to the considered evaluation indicators, including root mean square error (RMSE) and R values.

• 한국가시화정보학회지
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• 제19권1호
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• pp.62-67
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• 2021

Selective catalytic reduction(SCR) is an exhaust gas reduction device to remove nitro oxides (NOx). SCR operation of ship can be controlled through valves for minimizing economic loss from SCR. Valve in SCR-high pressure (HP) system is directly connected to engine exhaust and operates in high temperature and high pressure. Long-term thermal deformation induced by engine heat weakens the sealing of the valve, which can lead to unexpected failures during ship sailing. In order to prevent the unexpected failures due to long-term valve thermal deformation, a failure prediction system using autoregressive integrated moving average (ARIMA) was proposed. Based on the heating experiment, virtual data mimicking temperature range around the SCR-HP valve were produced. By detecting abnormal temperature rise and fall based on the short-term ARIMA prediction, an algorithm determines whether present temperature data is required for failure prediction. The signal processed by the data collection algorithm was interpolated for the failure prediction. By comparing mean average error (MAE) and root mean square error (RMSE), ARIMA model and suitable prediction instant were determined.

• 대기
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• 제31권3호
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• pp.327-340
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• 2021

In this study, the impact of soil moisture initialization in GloSea5, the operational climate prediction system of the Korea Meteorological Administration (KMA), has been investigated for the period of 1991~2010. To overcome the large uncertainties of soil moisture in the reanalysis, JRA55 reanalysis and CMAP precipitation were used as input of JULES land surface model and produced soil moisture initial field. Overall, both mean and variability were initialized drier and smaller than before, and the changes in the surface temperature and pressure in boreal summer and winter were examined using ensemble prediction data. More realistic soil moisture had a significant impact, especially within 2 months. The decreasing (increasing) soil moisture induced increases (decreases) of temperature and decreases (increases) of sea-level pressure in boreal summer and its impacts were maintained for 3~4 months. During the boreal winter, its effect was less significant than in boreal summer and maintained for about 2 months. On the other hand, the changes of surface temperature were more noticeable in the southern hemisphere, and the relationship between temperature and soil moisture was the same as the boreal summer. It has been noted that the impact of land initialization is more evident in the summer hemispheres, and this is expected to improve the simulation of summer heat wave in the KMA's operational climate prediction system.

• 응용통계연구
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• 제15권2호
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• pp.213-222
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• 2002

이 논문에서는 서울지역 기온에 대한 향후 48시간까지 3시간 간격 예보 모델 개발 결과이 다. 동적 변화패턴과 수치모델의 체계적 오차를 제거하기 위하여 동적 선형모형으로 적합하였으며 , 수치모델 예측치와 관측치를 입력 변수로 사용하였다. 동적 선형모형에 의한 예측모델은 수치모델의 체계적 오차를 성공적으로 제거하였으며, 예측 정확도를 향상시키고 있다.

• 한국도로학회논문집
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• 제16권4호
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• pp.87-95
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• 2014

PURPOSES: Evaluation of thermal conductivity and convection properties of asphalt mixture by using thermodynamics. METHODS: In this research, temperature prediction model based on thermodynamics is derived for asphalt mixture in transient state and it is verified with laboratory test results. RESULTS: The derived temperature prediction model shows good agreement with laboratory test results. CONCLUSIONS: It is concluded that the derived model based on thermodynamics and thermal properties in the literature are good enough to capture temperature variation in laboratory test. The approach based on thermodynamics can be applied to more complex temperature simulations.

• 대한기계학회논문집B
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• 제30권10호
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• pp.950-956
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• 2006

A mathematical heat transfer model for the prediction of heat flux on the slab surface and temperature distribution in the slab has been developed by considering the thermal radiation in the furnace and transient conduction governing equations in the slab, respectively. The furnace is modeled as radiating medium with spatially varying temperature and constant absorption coefficient. The slab is moved with constant speed through non-firing, charging, preheating, heating, and soaking zones in the furnace. Radiative heat flux which is calculated from the radiative heat exchange within the furnace modeled using the FVM by considering the effect of furnace wall, slab, and combustion gases is applied as the boundary condition of the transient conduction equation of the slab. Heat transfer characteristics and temperature behavior of the slab is investigated by changing such parameters as absorption coefficient and emissivity of the slab. Comparison with the experimental work shows that the present heat transfer model works well for the prediction of thermal behavior of the slab in the reheating furnace.

• 한국강구조학회 논문집
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• 제9권3호통권32호
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• pp.431-440
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• 1997

본 논문에서는 교량 단면 내의 시간 종속적 온도 분포를 결정하기 위해, 기존의 열 전달 이론 및 태양 에너지 전달에 대한 이론을 바탕으로 기상관측소 및 현장에서 측정한 기상 자료로부터 교량 온도의 예측에 관한 이론적 모델에 대해 기술하였다. 특히 이 모텔에서는 주간에 교량의 온도 상승에 지배적인 영향을 미치는 태양일사(solar radiation)에 대해 태양 에너지 관련 분야의 여러 실험적 연구 결과를 바탕으로 태양일사량의 계산에 대해 기존에 연구되어 있는 식들 중에서 가장 적합한 식을 제시하였다. 이 해석 모델의 타당성은 사당 고가차도의 장기 계측된 온도 측정 결과와 비교 검토되었다. 또한 장기간 측정된 온도 결과로부터 교량 온도 예측에 대한 해석적 기준(analytical criteria)을 제시하기 위해, 교량의 축 방향 신축의 원인이 되는 단면평균온도, 그리고 곡률 변형을 유발하는 단면온도차 등 교량 단면의 온도 분포와 관련된 변수들과 대기온도, 일사량 등 기상 자료와 관련된 변수들 간의 선형 상관관계(linear correlation)에 대해 기술하였다.