The conventional multi-scale modelling approach that predicts carbon nanotube (CNT) growth region in heterogeneous flame environment is computationally exhaustive. Thus, the present study is the first attempt to develop a zero-dimensional model based on existing multi-scale model where mixture fraction z and the stoichiometric mixture fraction zst are employed to correlate burner operating conditions and CNT growth region for diffusion flames. Baseline flame models for inverse and normal diffusion flames are first established with satisfactory validation of the flame temperature and growth region prediction at various operating conditions. Prior to developing the correlation, investigation on the effects of zst on CNT growth region is carried out for 17 flame conditions with zst of 0.05 to 0.31. The developed correlation indicates linear ( zlb=1.54zst +0.11) and quadratic ( zhb=zst(7-13zst )) models for the zlb and zhb corresponding to the low and high boundaries of mixture fraction, respectively, where both parameters dictate the range of CNT growth rate (GR) in the mixture fraction space. Based on the developed correlations, the CNT growth in mixture fraction space is optimum in the flame with medium-range zst conditions between 0.15 and 0.25. The stronger relationship between growth-region mixture-fraction (GRMF) and zst at the near field region close to the flame sheet compared to that of the far field region away from the flame sheet is due to the higher temperature gradient at the former region compared to that of the latter region. The developed models also reveal three distinct regions that are early expansion, optimum, and reduction of GRMF at varying zst.

Recently, traffic accidents have continued to occur due to the failure to secure a safe distance for trucks. Unlike passenger cars, freight cars have a large fluctuation in the weight of the vehicle's shaft depending on the load, and the fatality of accidents and the possibility of accidents are high. In this study, a braking distance prediction model according to the driving speed and loading weight of a three-axis truck was implemented to prevent a forward collision accident. Learning data was generated based on simulation, and a prediction model based on machine learning was implemented to finally verify accuracy. The extra trees algorithm was selected based on the most frequently used R2 Score among regression analyses, and the accuracy of the braking distance prediction model was 98.065% through 10 random scenarios.

Because the inner environment of greenhouse has a direct impact on crop production, many studies have been performed to develop technologies for controlling the environment in the greenhouse. However, it is difficult to apply the technology developed to all greenhouses because those studies were conducted through empirical experiments in specific greenhouses. It takes a lot of time and cost to develop the models that can be applicable to all greenhouse in real situation. Therefore studies are underway to solve this problem using computer-based simulation techniques. In this study, a model was developed to predict the inner environment of glass greenhouse using CFD simulation method. The developed model was validated using primary and secondary heating experiment and daytime greenhouse inner temperature data. As a result of comparing the measured and predicted value, the mean temperature and uniformity were 2.62°C and 2.92%p higher in the predicted value, respectively. R2 was 0.9628, confirming that the measured and the predicted values showed similar tendency. In the future, the model needs to improve by applying the shape of the greenhouse and the position of the inner heat exchanger for efficient thermal energy management of the greenhouse.

국내 시설 농업의 99.2%를 차지하는 플라스틱온실의 내부 환경인자는 외부 환경의 변화에 민감하게 반응하고 온실 공간 내부에서 편차가 발생한다. 온도, 습도, CO2, 광도의 환경인자를 계측하기 위한 지점을 3 × 3 × 5로 구성하여 데이터를 취득하고 내부 공간을 수직, 수평적인 측면으로 분할하여 환경 인자의 분포를 확인하였다. 계측지점의 최적점을 선정하고자 계측 공간을 수직, 수평적인 방향으로 분할하고, 측정 데이터와 이를 활용한 예측지점의 선형회귀분석 결과로 성능평가를 실시하였다. 일반적인 상황에서는 온도와 습도 인자의 경우 1개의 센서로 플라스틱온실 내부 환경의 계측이 가능할 수 있으나, 특정 구간의 경우 다수의 센서를 활용하여 내부공간의 정밀성을 확보하는 것이 필요하다. CO2의 경우 실험기간 내의 계측 매트릭스의 증가에도 불구하고 변이를 정의하는데 한계가 있음을 발견하였다. 조도 분포의 경우 일출 이후 지속적으로 회귀분석 결과가 작아짐을 발견하였다. 구조물의 간섭 등을 고려해 동일한 수평적인 방향에서 미계측 지점의 결정계수가 감소하였고, 센서 매트릭스 배치를 작물 높이 위로 위치하여 다수의 센서 노드 설치로 개선 가능하다고 예상된다. 외부 환경의 변화에 따라 온실 내부 환경이 불규칙하게 변화되며, 이 구간은 시설의 규격을 고려하여 계측 매트릭스를 구성해야 한다. 반대로 안정적인 구간에서는 최소한의 센서 노드로 내부 환경의 예측이 가능한 것을 확인할 수 있었다. 결과적으로 측정하고자 하는 환경인자와 시설의 구조 등 연구 및 재배자의 목적에 맞는 계측 매트릭스 위치 선정의 유동성이 요구되며, 덕트의 개폐위치를 조절하여 필요한 곳에 에너지를 투입하는 국소냉난방 및 생육제어 모델링 설계에 적용 가능하다고 판단된다.

본 연구에서는 월성 중₩저준위방사성폐기물 처분시설의 내구성 및 한계수명을 예측하였다. 처분시설은 6개의 사일로로 구 성되어 있으며 지하수 포화대에 위치하고 있어 주변 지하수와 화학적 침식 등에 의한 열화에 노출되어 있으며, 장시간이 흐 르면 수리적 방벽으로서의 역할을 상실할 것으로 예상된다. 각각의 인자에 대한 열화시간을 평가한 결과 황산염 및 마그네 슘에 의한 콘크리트 열화속도는 1.308×10-3 cm/yr로 48,000 년 이상인 것으로 나타났으며, 수산화칼슘 침출에 의한 영향은 1,000 년의 기간 경과에서 수산화칼슘 유출 깊이는 1.5 cm이하로 상당히 오랜 시간이 소요되는 것으로 나타났다. 마지막으 로 염해에 의한 철근 부식의 경우 철근 부식개시기간이 1,648 년으로, 최종적으로 구조물이 한계수명 상태에 도달하는 시간 은 2,288 년인 것으로 예측되어 가장 민감한 인자로 평가되었다.

A new prediction scheme has been proposed for the robust teleoperation in a non-visible environment. The positioning error caused by the time delay in the non-visible environment has been compensated for by the Smith predictor and the sensory data have been estimated by the Grey model. The Smith predictor is effective for the compensation of the positioning error caused by the time delay with a precise system model. Therefore the dynamic model of a mobile robot has been used in this research. To minimize the unstable and erroneous states caused by the time delay, the estimated sensor data have been sent to the operator. Through simulations, the possibility of compensating the errors caused by the time delay has been verified using the Smith predictor. Also the estimation reliability of the measurement data has been demonstrated. Robust teleoperations in a non-visible environment have been performed with a mobile robot to avoid the obstacles effective to go to the target position by the proposed prediction scheme which combines the Smith predictor and the Grey model. Even though the human operator is involved in the teleoperation loop, the compensation effects have been clearly demonstrated.

This study forecasts changes in thermal environment and microclimate change per new building construction and assignment of green space in urban area using Computational Fluid Dynamics(CFD) simulation. The analysis studies temperature, humidity and wind speed changes in 4 different given conditions that each reflects; 1) new building construction; 2) no new building construction; 3) green spaces; and 4) no green spaces. Daily average wind speed change is studied to be; Case 2(2.3 m/s) ＞ Case 3. The result of daily average temperate change are; Case 3(26.5℃) ＞ Case 4(24. 6℃) ＞ Case 2(23.9℃). This result depicts average of 2.5℃ temperature rise post new building construction, and decrease of approximately 1.8℃ when green space is provided. Daily average absolute humidity change is analysed to be; Case 3(15.8 g/kg') ＞ Case 4(14.1 g/kg') ＞ Case 2(13.5 g/kg'). This also reveals that when no green spaces is provided, 2.3 g/kg' of humidity change occurs, and when green space is provided, 0.6 g/kg change occurnd 4(1.8 m/s), which leads to a conclusion that daily average wind velocity is reduced by 0.5 m/s per new building construction in a building complex.

해양환경 하에서 염화물의 침투를 억제하여 부식 위험을 최소화함으로써 콘크리트 구조물의 공용기간을 연장할 수 있다. 효과적으로 구조물을 관리하기 위해 적절하게 유지관리하는 것이 필요하다. 본 연구에서는 효과적인 유지관리 전략을 세우기 위한 보수된 구조물의 유지관리비용 평가와 연계하여 구조물의 사용수명을 정량적으로 평가하는 방법을 제안하였다. Fick의 제2법칙으로부터Crank-Nicolson법에 기초한 유한 차분법을 제안하여 보수되지 않은 콘크리트 구조물과 보수된 콘크리트 구조물의 염화물 이온 분포를 예측하였다. 이를 이용하여 보수에 의해 연장 가능한 사용수명과 목표한 공용기간 동안에 필요한 보수 횟수를 평가하였다. 게다가보수 횟수와 콘크리트 교체 비용을 고려하여 총 유지관리 비용을 산출하였다. 마지막으로 제안된 방법의 적용성 검토를 위해 수치해석예제를 제시하였다.

Numerical simulation is essential to indicate the flow of the atmosphere in the region with a complicated topography which consists of many mountains in the inland while it is neighboring the seashore. Such complicated topography produces land and sea breeze as the mesoscale phenomenon of meteorology which results from the effect of the sea and inland. In the mesoscale simulation examines, the change of the temperature in relation to the one of the sea surface for the boundary condition and, in the inland, the interaction between the atmosphere and land surface reflecting the characteristic of the land surface. This research developed and simulated PNULSM to reflect both the SST and vegetation effect as a bottom boundary for detailed meteorological numerical simulation in coastal urban area. The result from four experiments performed according to this protocol revealed the change of temperature field and wind field depending on each effect. Therefore, the lower level of establishment of bottom boundary suitable for the characteristic of the region is necessary to figure out the atmospheric flow more precisely, and if the characteristic of the surface is improved to more realistic conditions, it will facilitate the simulation of regional environment.

Interior space in most buildings is divided into several zones. The most important factors relating to the indoor air environment are temperature, airflow, humidity, and contaminant concentration. An integrated multizone model to predict these environmental factors simultaneously was developed. Also, a computer program for this model was written by the language of VISUAL BASIC. The proposed model was applied to a apartment with five rooms that had been tested by Chung11). Comparison of predicted results by this study with measured results by Chung showed that their variations were within 14% for airflow rates, 1% for temperatures, 12% for humidities, and 5% for concentrations. It was seen that the opening operation schedule of building has a significant effect on the air moisture and contaminant removal. Thus, this model may be available for predicting the indoor air environment and may be contributed to design the ventilation plan for controling of indoor air quality.