• Journal of Korea Technology Innovation Society
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• v.14 no.spc
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• pp.1232-1255
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• 2011

This paper proposes a model for demand forecasting that will require less effort in the process of utilizing the new product diffusion model while also allowing for more objective and timely application. Drawing upon the theoretical foundation provided by the hype cycle model and the consumer adoption model, this proposed model makes it possible to estimate the maximum market potential based solely on bibliometrics and the scale of the early market, thereby presenting a method for supplying the major parameters required for the Bass model. Upon analyzing the forecasting ability of this model by applying it to the case of the hybrid car market, the model was confirmed to be capable of successfully forecasting results similar in scale to the market potential deduced through various other objective sources of information, thus underscoring the potentials of utilizing this model. Moreover, even the hype cycle or the life cycle can be estimated through direct linkage with bibliometrics and the Bass model. In cases where the hype cycles of other models have been observed, the forecasting ability of this model was demonstrated through simple case studies. Since this proposed model yields a maximum market potential that can also be applied directly to other growth curve models, the model presented in the following paper provides new directions in the endeavor to forecast technology diffusion and identify promising technologies through bibliometrics.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2002.04a
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• pp.279-280
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• 2002

본 연구에서는 라그랑지안 확산모델(LDM; Lagrangian dispersion model)을 이용하여 평지 및 언덕지형에서의 연기확산을 수치모사하였다. 수치예측의 검증을 위하여 평지지형의 경우는 풍동실험 결과와 비교하고 언덕지형의 경우는 오일러리안 확산모델(EDM; Eulerian dispersion model)의 모사결과와 비교함으로써 언덕지형에서 오염물질의 확산특성을 연구하였다. (중략)

• Korean Journal of Food Science and Technology
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• v.27 no.3
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• pp.387-393
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• 1995

Diffusion coefficients of moisture and solid, reaction rate constants of carotene destruction, and the fitness of drying models for moisture transfer were determined to study the characteristics of mass transfer during osmotic dehydration. Moisture loss and solid gain were increased with increase of temperature and concentration; temperature had higher osmotic effect than concentration. Diffusion coefficient showed similar trend with osmotic effect. Diffusion coefficients of solids were larger than those of moisture because the movement of solid was faster than that of moisture at the high temperature. Reaction rate constants were affected to the greater extent by concentration changes than by temperature changes. Arrhenius equation was applied to determine the effect of temperature on diffusion coefficients and reaction rate constants. Moisture diffusion required high activation energy in $20^{\circ}Brix$, while relatively low in $60^{\circ}Brix$. To predict the diffusion coefficients and reaction rate constants, a model was established by using the optimum functions of temperature and concentration. The model had high $R^2$ value when applied to diffusion coefficients, but low when applied to reaction rate constants. Quadratic drying model was most fittable to express moisture transfer during drying. In conclusion, moisture content of carrots could be predictable during the osmotic dehydration process, and thereby mass transfer characteristics could be determined by predicted moisture content and diffusion coefficient.

• Fire Science and Engineering
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• v.22 no.2
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• pp.63-69
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• 2008

The characteristics of the spread of a forest fire are generally related to the attributes of combustibles, geographical features, and meteorological conditions, such as wind conditions. The most common methodology used to create a prediction model for the spread of forest fires, based on the numerical analysis of the development stages of a forest fire, is an analysis of heat energy transmission by the stage of heat transmission. When a forest fire breaks out, the analysis of the transmission velocity of heat energy is quantifiable by the spread velocity of flame movement through a physical and chemical analysis at every stage of the fire development from flame production and heat transmission to its termination. In this study, the formula used for the 1-D surface forest fire behavior prediction model, derived from a numerical analysis of the surface flame spread rate of solid combustibles, is introduced. The formula for the 1-D surface forest fire behavior prediction model is the estimated equation of the flame spread velocity, depending on the condition of wind velocity on the ground. Experimental and theoretical equations on flame duration, flame height, flame temperature, ignition temperature of surface fuels, etc., has been applied to the device of this formula. As a result of a comparison between the ROS(rate of spread) from this formula and ROSs from various equations of other models or experimental values, a trend suggesting an increasing curved line of the exponent function under 3m/s or less wind velocity condition was identified. As a result of a comparison between experimental values and numerically analyzed values for fallen pine tree leaves, the flame spread velocity reveals a prediction of an approximately 10% upward tendency under wind velocity conditions of 1 to 2m/s, and of an approximately 20% downward tendency under those of 3m/s.

• Proceedings of the Korea Society for Simulation Conference
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• 1997.04a
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• pp.115-119
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• 1997

본 논문은 해상에서 발생될 수 있는 기름 유출 사고시 효과적 방제의 지원을 위한 오염원 확산 예측 시스템의 개발을 주목적으로 한다. 이를 위하여, 격자형 공간 DEVS 모델 링 방법론을 이용한 SOS(Save Our Sea) 시스템을 개발하였다. 기존의 해양오염 예측 시스 템들이 대부분 해석적 기법에 의존하는데 비해 제안된 시스템은 격자형 공간 모델링을 이용 한 시뮬레이션 기법으로서 전체 해양을 Cell 단위의 공간으로 분할하고, Cellrks의 결합관계 는 Name-Directed Coupling을 적용함으로서 시스템 설계상의 효율성과 유연성을 제공한 다. 제안된 시스템은 기름유출사고의 발생시 오염원 확산에 영향을 주는 각종 벡터 변수값 들에 따른 해양 오염 물질의 확산 분포를 예측함과 동시에 확산에 영향을 주는 많은 벡터 값들이 모니터링 정보를 함께 제공함으로서 해양 오염 방제 및 환경 보존에 효과적으로 적 용될 수 있을 것으로 기대된다.

• Journal of the Korean Wood Science and Technology
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• v.24 no.3
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• pp.37-44
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• 1996

포수상태(包水狀態)의 루부라참나무(Quercus rubra) 시험편을 3가지 등온조건(等溫條件)에서 건조한 결과를 비정상상태(非正常狀態)의 확산(擴散)모델로 추정한 결과와 비교하였다. 표면이 충분히 젖은 상태인 건조초기에는 불안정(不安定)한 확산현상(擴散現象)이 관찰되었으나, 함수율(含水率)별 건조속도의 변이를 Fick's의 확산법칙과 비교할 때 유사한 형태를 보였다. 실험에서 얻은 건조조건별 건조곡선은 확산모델의 수치해석(數値解析) 결과와 거의 일치하였으며, 같은 평위함수율(平衛含水率) 조건에서 건조온도의 증가는 목재표면 보다 내부의 함수율 변화에 더 크게 영향하여 결과적으로 낮은 온도에서의 건조조건이 목재 내의 수분경사(水分傾斜)를 급하게 하는 것으로 밝혀졌다. 본 연구를 통해 목재 건조 중의 내부에 발생하는 수분경사를 추정하는데 비정상상태의 확산모델이 모든 함수율 범위에 걸쳐 유용하게 사용될 수 있음이 밝혀졌다.

• Composites Research
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• v.37 no.1
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• pp.40-45
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• 2024

In this research, we introduce a novel approach that employs a 3D convolutional neural network (CNN) model to predict the permeability of Gas Diffusion Layers (GDLs). For training the model, we create an artificial dataset of GDL representative volume elements (RVEs) by extracting morphological characteristics from actual GDL images obtained through X-ray tomography. These morphological attributes involve statistical distributions of porosity, fiber orientation, and diameter. Subsequently, a permeability analysis using the Lattice Boltzmann Method (LBM) is conducted on a collection of 10,800 RVEs. The 3D CNN model, trained on this artificial dataset, well predicts the permeability of actual GDLs.

• Journal of Korean Society of Environmental Engineers
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• v.27 no.8
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• pp.852-858
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• 2005

Modeling techniques for air quality are useful tools in air quality management. Especially, the air quality in urban area is significantly influenced by local surroundings such as buildings and traffic. When considering the air quality in a street canyon, which is usually filmed by a series of consecutive buildings and a street, currently available air dispersion model have a number of limitations to predict the air quality properly. In this study, it is aimed to propose an empirical model for the air quality in urban street canyons. A series of wind tunnel tests, followed by statistical analysis, were conducted. In conclusion, it is found that a wide street canyon and a perpendicular external wind to the street canyon are beneficial to achieve an enhanced air quality in street canyon environment. The model prediction using the proposed model also shows reliable correlations to the wind tunnel test results.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.22-28
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• 2021

This is a basic study on the development of deep learning-based algorithms to detect smoke before the smoke detector operates in the event of a ship fire, analyze and utilize the detected data, and support fire suppression and evacuation activities by predicting the spread of smoke before it spreads to remote areas. Proposed algorithms were reviewed in accordance with the following procedures. As a first step, smoke images obtained through fire simulation were applied to the YOLO (You Only Look Once) model, which is a deep learning-based object detection algorithm. The mean average precision (mAP) of the trained YOLO model was measured to be 98.71%, and smoke was detected at a processing speed of 9 frames per second (FPS). The second step was to estimate the spread of smoke using the coordinates of the boundary box, from which was utilized to extract the smoke geometry from YOLO. This smoke geometry was then applied to the time series prediction algorithm, long short-term memory (LSTM). As a result, smoke spread data obtained from the coordinates of the boundary box between the estimated fire occurrence and 30 s were entered into the LSTM learning model to predict smoke spread data from 31 s to 90 s in the smoke image of a fast fire obtained from fire simulation. The average square root error between the estimated spread of smoke and its predicted value was 2.74.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.379-383
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• 2008

본 연구의 목적은 3차원 수리 모델인 ELCOM(Estuary, Lake and Coastal Ocean Model)과 물질 전달모델인 CAEDYM(Computational Aquatic Ecosystem Dynamic Model)을 이용하여 성층화된 저수지로 밀도류 형태로 유입한 부유사의 이송과 확산 그리고 침강특성을 해석하는데 있다. ELCOM은 3차원 수리동력학 모델로써 시공간적인 유속과 수온변화를 예측하는데 사용되었으며, CAEDYM과 매 계산시간 마다 동적으로 연결(Dynamic coupling)되어 부유입자의 이송, 확산, 침강 과정을 모의하였다. 개발된 3차원 모델의 예측 성능은 2004년 홍수기 동안 대청호에서 실측한 자료를 사용하여 검증하였다. 모델의 모의변수는 입자크기별로 구분된 부유물질(SS) 그룹이며, 현장 실측자료인 탁도($C_T$)와 모델 변수인 SS간의 변환을 위해 저수지 지점 별로 측정한 SS-$C_T$ 상관관계를 사용함으로써 부유 입자의 크기분포의 공간적 변동 특성을 반영하였다. 모델은 탁수가 유입하는 환경에서 저수지 성층구조의 변화와 유입 탁수의 밀도류 거동특성, 유입한 부유사의 이송과 확산 그리고 침강특성을 비교적 잘 모의하였다. 저수지로 유입한 부유입자 중 입경이 $20{\mu}m$ 이상인 입자는 매우 빠른 속도로 저수지 바닥에 퇴적된 반면, $10{\mu}m$ 이하의 입자들은 중층에 오랜 시간 부유하며 장기탁수문제를 유발하는 원인이 되었다.