• 농업과학연구
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• 제11권2호
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• pp.270-277
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• 1984

자연공기(自然空氣)에 의(依)한 벼 건조의 요인영향(要因影響)을 시뮤레이션 모델에 의(依)하여 분석(分析)하였다. 분석(分析)된 요인(要因)들은 송풍량(送風量), 수확시기(收穫時期), 초기수분함량(初期水分含量) 그리고 기상조건(氣상條件)이었다. 시뮤레이션을 위해서는 RICEDRY model 을 이용(利用)하였다. 그리고 개발(開發)된 시뮤레이션 모델이 외국(外國)의 기상조건하(氣象條件下)에서 적용(適用)될 수 있는가와 자연공기(自然空氣)에 의(依)한 벼 건조(乾燥)가 가능(可能)한가를 중남미(中南美)의 코스타리카의 기상자료(氣상資料)를 이용(利用)하여 시험(試驗)하였다. 이상(以上)의 연구(硏究)를 통(通)하여 다음과 같은 결론(結論)을 얻을 수 있었다. 1. 송풍량(送風量)이 많을수록, 건조시간(乾燥時間)이 짧았고 건물손실(乾物損失)이 적었다. 2. 수확시기(收穫時期)에 따른 건물손실간(乾物損失間)에는 현저(顯著)한 차이(差異)가 있었다. 3. 초기수분함량(初期水分含量)이 높을수록, 건조층내(乾燥層內)에서 건물손실(乾物損失) 변화도(變化度)가 컸다. 4. 건조층(乾燥層)의 최하부(最下部)의 벼 수분함량(水分含量)은 기상변화(氣象變化)에 매우 민감(敏感)하게 변화(變化)하였으며, 중간층(中間層)과 최상층(最上層)의 수분함량(水分含量)은 비교적(比較的) 기상변화(氣象變化)에 따른 변화(變化)가 적었다. 5. 시뮤레이션 모델(RICEDRY)는 외국(外國) 기상조건하(氣象條件下)에서도 적용(適用)될 수 있었으며, 열대기후하(熱帶氣候下)에서도 자연공기(自然空氣)에 의(依)한 벼 건조(乾燥)가 가능(可能)함을 알 수 있었다.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2018년도 춘계학술대회
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• pp.318-320
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• 2018

When a ship sails on sea, it may be influenced by the environmental disturbance such as wind, wave, sea surface temperature, etc. These affect on the ship's speed, fuel consumption, safety and operating performance. It is necessary to find the optimal weather route of a ship to avoid adverse weather conditions which can put the crews in serious danger or cause structural damage to the vessel, machinery, and equipment. This study introduced how to apply A* algorithm based on sea trial test data for determining the optimal ship routes. The path cost function was modelled as a function of minimum arrival time or minimum energy depending on the time of various environment conditions. The specially modelled path-cost function and the safety constraints were applied to the A* algorithm in order to find the optimal path of the ship. The comparison of ship performances estimated by real sea trial's path and estimated optimal route during the voyage of the ship was investigated. The result of this study can be used to create a schedule to ensure safe operation of the ship with short passage time or minimum energy. In addition, the result of this study can be integrated into an on-board decision supporting expert system and displayed in Electronic Chart Display and Information System (ECDIS) to provide all the useful information to ship master.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.226-227
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• 2007

The purpose of this study for photovoltaic (PV) generation system is to keep the output power of photovoltaic cells maximized under any weather conditions. In a conventional MPPT (Maximum Power Point Tracking) control method, both voltage and current coming out from PV array have to be fedback. Thus, the system has a complex structure, and may fail to track MPP of PV array when unexpected weather conditions happen. This paper proposes a novel PV Output Senseless (POS) control method to solve the mentioned problem. The main advantage of this method is that the current flowing into load is the only one considerable factor. In case of a huge PV generation system, it can be operated much more safely than the conventional system. To verify this theory, results that compare and analyze the simulated data with experimental data under real weather condition of the manufactured PV generation system are shown in this paper. Authors vividly states that this theory uses constant resistors and variable resistors of DC-DC converter in PV system. Authors emphasize that it is a very useful method to maximize power from PV cells to load with only the feedback of load current. Authors also emphasize that this theory is applicable in case of the PCS in PV power generation system.

• The Plant Pathology Journal
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• 제31권4호
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• pp.350-362
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• 2015

A disease forecast model for bacterial grain rot (BGR) of rice, which is caused by Burkholderia glumae, was developed in this study. The model, which was named 'BGRcast', determined daily conduciveness of weather conditions to epidemic development of BGR and forecasted risk of BGR development. All data that were used to develop and validate the BGRcast model were collected from field observations on disease incidence at Naju, Korea during 1998-2004 and 2010. In this study, we have proposed the environmental conduciveness as a measure of conduciveness of weather conditions for population growth of B. glumae and panicle infection in the field. The BGRcast calculated daily environmental conduciveness, $C_i$, based on daily minimum temperature and daily average relative humidity. With regard to the developmental stages of rice plants, the epidemic development of BGR was divided into three phases, i.e., lag, inoculum build-up and infection phases. Daily average of $C_i$ was calculated for the inoculum build-up phase ($C_{inf}$) and the infection phase ($C_{inc}$). The $C_{inc}$ and $C_{inf}$ were considered environmental conduciveness for the periods of inoculum build-up in association with rice plants and panicle infection during the heading stage, respectively. The BGRcast model was able to forecast actual occurrence of BGR at the probability of 71.4% and its false alarm ratio was 47.6%. With the thresholds of $C_{inc}=0.3$ and $C_{inf}=0.5$, the model was able to provide advisories that could be used to make decisions on whether to spray bactericide at the preand post-heading stage.

• 대한교통학회지
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• 제19권6호
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• pp.65-73
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• 2001

교통량이 시간의 흐름과 관련이 있는 시계열 데이터라는 개념을 기초로 교통량 패턴을 시계열 분석을 사용하여 분해해 보고자 하였다. 교통량 패턴은 추세치(T)와 계절변동(S), 주기변동(C), 그리고 불규칙변동(I)으로 구분할 수 있었는데 본 연구에서는 불규칙변동을 기상요인을 통해 설명하려는 시도를 하였다. 왜냐하면 교통의 주체인 사람들 행태의 특성상 기상의 변화와 관련이 깊다고 판단을 내렸기 때문이었다. 기상요인으로는 일우량, 일조량, 풍속, 주야율 강설량, 기온 등 여러 가지가 있지만 교통량의 변화와 가장 관련이 깊다고 여겨지는 일우량과 최저기온을 이용하였다. 일단 시계열 성분을 분해하고 나면 이를 이용하여 AADT를 추정하게 되는데, 추정의 결과를 비교하기 위해 AADT 추정방법을 두 가지로 구분하였다. 즉, 기상요인을 사용했을 경우와 그렇지 않을 경우로 나누어 결과를 살펴보았다. 추정 결과를 비교하는 척도로는 RMSE와 U-test를 사용하였다. 결과를 보면 불규칙변동요인을 그대로 사용했을 때보다, 기상요인을 결합한 불규칙변동요인을 사용했을 때 더 추정력이 좋았다. 이것은 각 조사지점의 RMSE와 U-test값을 구한 후 그 지점의 AADT로 나누어 준 결과를 보고 알 수 있었다. 이 연구를 통해 우리는 불규칙변동요인 이용방법의 중요성에 대해 한번 더 생각해 보게 된다. 즉 그것을 설명하는 방법에 의해 기존보다 더 나은 모형을 얻을 수도 있다는 결론에 이르게 된다는 것이다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2019년도 학술발표회
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• pp.147-147
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• 2019

The Numerical Weather Prediction (NWP) models determine the future state of the weather by forcing current weather conditions into the atmospheric models. The NWP models approximate mathematically the physical dynamics by nonlinear differential equations; however these approximations include uncertainties. The errors of the NWP estimations can be related to the initial and boundary conditions and model parameterization. Development in the meteorological forecast models did not solve the issues related to the inevitable biases. In spite of the efforts to incorporate all sources of uncertainty into the forecast, and regardless of the methodologies applied to generate the forecast ensembles, they are still subject to errors and systematic biases. The statistical post-processing increases the accuracy of the forecast data by decreasing the errors. Error prediction of the NWP models which is updating the NWP model outputs or model output statistics is one of the ways to improve the model forecast. The regression methods (including linear, polynomial and scaling regression) are applied to the present study to improve the real time forecast skill. Such post-processing consists of two main steps. Firstly, regression is built between forecast and measurement, available during a certain training period, and secondly, the regression is applied to new forecasts. In this study, the WRF real-time forecast data, in comparison with the observed data, had systematic biases; the errors related to the NWP model forecasts were reflected in the underestimation of the meteorological data forecast by the WRF model. The promising results will indicate that the post-processing techniques applied in this study improved the meteorological forecast data provided by WRF model. A comparison between various bias correction methods will show the strength and weakness of the each methods.

• 한국안전학회지
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• 제33권6호
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• pp.144-156
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• 2018

Level 3 Probabilistic Safety Assessment (PSA) is performed for the risk assessment that calculates radioactive material dispersion to the environment. This risk assessment is performed with a tool of MELCOR Accident Consequence Code System (MACCS2 or WinMACCS). For the off-site consequence analysis of multi-unit nuclear power plant (NPP) accident, the single location (Center Of Mass, COM) method has been usually adopted with the assumption that all the NPPs in the nuclear site are located at the same COM point. It was well known that this COM calculation can lead to underestimated or overestimated radionuclide concentration. In order to overcome this underestimation or overestimation of radionuclide concentrations in the COM method, Multiple Location (ML) method was developed in this study. The radionuclide concentrations for the individual NPPs are separately calculated, and they are summed at every location in the nuclear site by the post-processing of radionuclide concentrations that is based on two-dimensional Gaussian Plume equations. In order to demonstrate the efficiency of the ML method, radionuclide concentrations were calculated for the six-unit NPP site, radionuclide concentrations of the ML method were compared with those by COM method. This comparison was performed for conditions of constant weather, yearly weather in Korea, and four seasons, and the results were discussed. This new ML method (1) improves accuracy of radionuclide concentrations when multi-unit NPP accident occurs, (2) calculates realistic atmospheric dispersion of radionuclides under various weather conditions, and finally (3) supports off-site emergency plan optimization. It is recommended that this new method be applied to the risk assessment of multi-unit NPP accident. This new method drastically improves the accuracy of radionuclide concentrations at the locations adjacent to or very close to NPPs. This ML method has a great strength over the COM method when people live near nuclear site, since it provides accurate radionuclide concentrations or radiation doses.

• Advances in Energy Research
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• 제8권1호
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• pp.73-93
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• 2022

Focus on climate change and extreme weather conditions has received considerable attention in recent years. Civil engineers are now focusing on designing buildings that are more eco-friendly in the face of climate change. This paper describes the research conducted to assess the impact of future climate change on energy usage and carbon emissions in a typical supermarket at multiple locations across the UK. Locations that were included in the study were London, Manchester, and Southampton. These three cities were compared against their building performance based on their respective climatic conditions. Based on the UK Climatic Projections (UKCP09), a series of energy modelling simulations which were provided by the Chartered Institute of Building Service Engineers (CIBSE) were conducted on future weather years for this investigation. This investigation ascertains and quantifies the annual energy consumption, carbon emissions, cooling, and heating demand of the selected supermarkets at the three locations under various climatic projections and emission scenarios, which further validates annual temperature rise as a result of climatic variation. The data showed a trend of increasing variations across the UK as one moves southwards, with London and Southampton at the higher side of the spectrum followed by Manchester which has the least variability amongst these three cities. This is the first study which investigates impact of the climate change on the UK supermarkets across different regions by using the real case scenarios.

• 해양환경안전학회지
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• 제23권3호
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• pp.250-257
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• 2017

This paper investigates minimum safe distances relative to a ship's four cardinal sides, as perceived by Filipino navigators when encountering dangerous elements and in adverse weather conditions when maneuvering in and around harbors. It uses a descriptive research method in the form of a questionnaire survey for experienced Filipino navigators of various ranks. During the course of research, 71 responses were colleted and the resulting data is presented in graphical and tabulated forms. Statistical methods including Pearson-product moment correlations, Cronbach's Alpha and ANOVA were used to identify internal associations, consistencies and significances, respectively. It has been proven that there are no significant differences in minimum safe distances relative to a ship's four cardinal sides, whether maneuvering while approaching a port or within an inner harbor. This study has been deemed significant for training future navigators, managing traffic in fairways, and designing harbors and maneuvering areas in the approaches to ports, among other applications. This work can also be used as a preliminary study for comparison with the well known safe domains presently in use.

• 설비공학논문집
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• 제12권4호
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• pp.404-413
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• 2000

Environmental chamber (EC) is an experimental facility used to analyze the characteristics of thermal response of testing objects by the artificial control of weather conditions. The EC in KIER can simulate the weather conditions by the control of temperature, humidity, and solar radiation. A two-storied testing building is located inside of EC. For the exact thermal response analysis of testing building, monthly or yearly scheduled operations are necessary. Although this long term operation gives the exact experimental data, it requires a high operational cost, long duration, and lots of manpower. Therefore it is necessary to perform the shortened experiments without sacrificing the validity of the obtained results. Since the characteristics of thermal response from the shortened experiments are different from the full time results, the analytical method to analyze the thermal response from the shortened experiments to estimate a full times results is developed in this study. The thermal response of testing building is performed using commercial software TRNSYS.