• 한국신뢰성학회지:신뢰성응용연구
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• 제16권4호
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• pp.338-346
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• 2016

Purpose: The purpose of this research is to improve the reliability of the composite material blades used for the wind power generator, by applying the phased array ultrasonic testing technique out of the many nondestructive test into the blades. Method: The wind power generation composite blades are used, as a case study, in order to evaluate the reliability of the phased array ultrasonic testing technique. Defects that are most likely occurred in the field are injected into the different locations of the three different types of artificial test pieces and then phased array ultrasonic testing technique are applied to evaluate the reliability of its effectiveness. Result: As a result of the analysis of the defect signals by applying the A scan and B scan simultaneously, depth and width of the defect could be obtained. An area of defect was proportional to the amount of energy by color in B scan image. The larger amount of energy, reflected amount of energy was appeared in the order of red, orange, yellow, blue color. Conclusion: The most reliable testing method to detect the defect in composite blades for wind power generation is considered to be the combination of the other destructive testing technique with the phased array ultrasonic testing since the PAUT alone could not detect all range of the defects in the blades.

• 한국재난정보학회 논문집
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• 제10권2호
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• pp.244-252
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• 2014

본 연구에서는 버켓기초로 지지된 해상풍력타워의 지진응답을 지반-구조물 상호작용을 고려하여 해석하였다. 해석프로그램으로는 SASSI를 사용하였으며 연약지반에 대해 생성된 인공지진파를 입력으로 사용하였다. 버켓기초의 형상과 강도를 매개변수로 하여 각 매개변수들의 영향을 파악하였다. 구조물의 응답은 타워의 하부와 나셀위치에서 얻어졌으며 응답스펙트럼으로 비교하였다. 해석결과 형상비, 버켓의 강도, 지반의 강도에 따라서 기초부와 나셀부에서 다른 경향의 응답을 보였다. 그러나 이러한 모든 지반-구조물상호작용의 고려는 암반으로 가정한 거동에 비하여 월등히 큰 응답 값을 보여 이의 고려가 버켓기초를 가진 해상풍력타워의 지진거동에 큰 영향을 미치는 것을 파악할 수 있었다.

• 한국농림기상학회지
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• 제19권3호
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• pp.86-92
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• 2017

본 연구에서는 기상청 예보자료를 이용할 것을 전제로 서리가 발생하는 날과 서리가 발생하지 않는 날을 구분하는 모형을 구축하였다. 서리가 발생한 날과 서리가 발생하지 않은 날을 구분할 수 있는 기상인자로서 최저기온, 평균풍속, 평균상대습도, 평균이슬점온도로 나타났다. 기상인자별로 두 날을 비교한 결과 서리가 발생한 날이 서리가 발생하지 않은 날에 비해 최저기온, 이슬점온도, 평균풍속은 낮게 나타났고 상대습도는 높게 나타났다. 이러한 기상인자로 인공신경망, 랜덤포레스트, 서포트벡터 머신의 기계학습법을 이용한 모형을 연구한 결과 70%이상의 정확도를 나타내어 활용 가능성이 있을 것으로 판단된다.

• 한국전산유체공학회지
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• 제19권2호
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• pp.86-92
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• 2014

In this paper, prediction of separation trajectory for Two-stage-To-Orbit space launch vehicle has been numerically simulated by using an aerodynamic database based on steady state analysis. Aerodynamic database were obtained for matrix of longitudinal and vertical positions. The steady flow simulations around the launch vehicle have been made by using a 3-D RANS flow solver based on unstructured meshes. For this purpose, a vertex-centered finite-volume method was adopted to discretize inviscid and viscous fluxes. Roe's finite difference splitting was utilized to discretize the inviscid fluxes, and the viscous fluxes were computed based on central differencing. To validate this flow solver, calculations were made for the wind-tunnel experiment model of the LGBB TSTO vehicle configuration on steady state conditions. Aerodynamic database was constructed by using flow simulations based on test matrix from the wind-tunnel experiment. ANN(Artificial Neural Network) was applied to construct interpolation function among aerodynamic variables. Separation trajectory for TSTO launch vehicle was predicted from 6-DOF equation of motion based on the interpolated function. The result of present separation trajectory calculation was compared with the trajectory using experimental database. The predicted results for the separation trajectory shows fair agreement with reference[4] solution.

• 한국습지학회지
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• 제16권1호
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• pp.19-32
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• 2014

본 연구에서는 우량계로 측정한 강우량이 실제 지표면에 떨어지는 강우 값에 근접하도록 보정함으로써, 유출해석 및 기타 수문분석에 적용할 경우 신뢰도 높은 결과를 얻는데 목적이 있다. 지상우량계로 관측한 강우량에 대한 바람의 영향을 분석하기 위하여, 표준기상관측소인 추풍령기상대에 설치된 바람막이의 유(有) 무(無)에 따른 우량계와 기준우량계의 자료를 획득하였다. 획득한 강우를 단순선형회귀 모형과 신경망 모형을 이용하여 지상강우를 보정하였으며, $Vflo^{TM}$모형을 이용한 유출모의를 통하여 자료의 신뢰도를 검증하였다. 단순선형회귀 모형을 사용한 보정 강우량은 실제 관측된 강우량보다 5%~18%가 큰 강우량을 나타냈으며, 강우획득에 있어 바람의 영향은 1.6~3.3m/s의 풍속구간에서 가장 큰 것을 확인하였다. 또한 회귀모형에서는 풍속구간 5.5m/s이상일 경우 자료의 개수가 전체자료의 0.7%로 매우 작고, 이상치가 획득됨으로써 회귀모형 적용의 어려움이 있었다. 반면에 신경망 기법을 이용한 지상강우의 보정은 전체적으로 관측 값보다 10~20% 가량 강우가 적게 추정되었다. 통계분석결과, 전체적으로 편차가 크고 평균 강우획득량이 클수록 신경망 모형의 적용성이 높게 나타났으며, 획득한 강우량의 극치값이 크게 나타날수록 선형회귀 모형의 적용성이 높게 나타나는 것을 확인하였다. 본 연구결과로 신뢰성 높은 강우보정을 위해서는 지역별 강우 특성에 따른 적합한 보정방법을 선택해야 할 것으로 판단되며, 앞으로의 수문해석에 있어 본 논문에서 제시하는 강우 보정방법을 적용함으로써 신뢰도 높은 수문해석 결과를 기대할 수 있을 것으로 사료된다.

• 한국항행학회논문지
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• 제23권6호
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• pp.597-604
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• 2019

인공신경망은 뇌의 뉴런들에서 상호 작용과 경험을 통해 학습해 나가는 것을 모사해 만든 알고리즘으로, 데이터의 특성이 반영된 학습을 통하여 정확한 결과를 산출하는데 사용할 수 있는 방법이다. 본 연구에서 기상 역학 모델에서 예측된 풍속 값의 개선을 위하여 심층신경망을 이용한 모델을 제시하였다. 연구에서 제시한 심층신경망을 이용한 풍속 예측 개선 모델은 기상 역학 모델의 예측 값을 재 보정하는 모델을 구축하고 이에 대한 검증과 시험 과정 후 별도의 데이터를 통한 예측의 정확도를 높일 수 있는 것을 확인하였다. 풍속 예측의 개선을 위하여 예측 시간, 온도, 기압, 습도, 대기상태변수, 풍속 등과 같은 일반적 기상 현상 자료의 예측 값을 활용한 심층신경망을 구축하였고, 전체 데이터 중 일부 데이터는 모델의 적정성 확인용 데이터로 구분하여, 모델 구축 및 학습에 사용하지 않고 별도의 정확도를 확인하여 연구에서 제시한 방법의 적합성을 확인하였다.

• 대한원격탐사학회지
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• 제36권1호
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• pp.41-53
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• 2020

The production of near- and off-shore fisheries in South Korea is decreasing due to rapid changes in the fishing environment, particularly including higher sea temperature in recent years. To improve the competitiveness of the fisheries, it is necessary to provide fish catch information that changes spatiotemporally according to the sea state. In this study, artificial intelligence models that predict the CPUE (catch per unit effort) of mackerel, anchovies, and squid (Todarodes pacificus), which are three major fish species in the near- and off-shore areas of South Korea, on a 15-km grid and daily basis were developed. The models were trained and validated using the sea surface temperature, rainfall, relative humidity, pressure,sea surface wind velocity, significant wave height, and salinity as input data, and the fish catch statistics of Suhyup (National Federation of Fisheries Cooperatives) as observed data. The 10-fold blind test results showed that the developed artificial intelligence models exhibited accuracy with a corresponding correlation coefficient of 0.86. It is expected that the fish catch models can be actually operated with high accuracy under various sea conditions if high-quality large-volume data are available.

• Asian Journal of Atmospheric Environment
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• 제9권1호
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• pp.12-21
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• 2015

Air pollution is a challenging issue in some of the large cities in developing countries. In this regard, data interpretation is one of the most important parts of air quality management. Several methods exist to analyze air quality; among these, we applied the Multilayer Perceptron (MLP) and Radial Basis Function (RBF) methods to predict the hourly air concentration of benzene in 14 districts in the municipality of Tehran. Input data were hourly temperature, wind speed and relative humidity. Both methods determined reliable results. However, the RBF neural network performance was much closer to observed benzene data than the MLP neural network. The correlation determination resulted in 0.868 for MLP and 0.907 for RBF, while the Index of Agreement (IA) was 0.889 for MLP and 0.937 for RBF. The sensitivity analysis related to the MLP neural network indicated that the temperature had the greatest effect on prediction of benzene in comparison with the wind speed and humidity in the study area. The temperature was the most significant factor in benzene production because benzene is a volatile liquid.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 1995년도 추계 학술대회논문집
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• pp.55-63
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• 1995

The flow field around a high-speed train including cross-wind effects has been simulated. This study solves 3-D unsteady incompressible Navier-Stokes equations in the inertial frame using the iterative time marching scheme. The governing equations are differenced with 1st-order accurate backward difference scheme for the time derivatives, 3th-order accurate QUICK scheme for the convective terms and 2nd-order accurate central difference scheme for the viscous terms. The Marker-and-Cell concept was applied to efficiently solve continuity equation, which is differenced with 2nd-order accurate central difference scheme. The 4th-order artificial damping is added to the continuity equation for numerical stability. A C-H type of elliptic grid system is generated around a high-speed train including ground. The Baldwin-Lomax turbulent model was implemented to simulate the turbulent flows. To validate the present procedure, the flow around a high speed train at constant yaw angle of $45^{\circ}\;and\;90^{\circ}$ has been simulated. The simulation shows 3-D vortex generation in the lee corner. The flow separation is also observed around the rear of the train. It has concluded that the results of present study properly agree with physical flow phenomena.

• 한국실내디자인학회논문집
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• 제19권3호
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• pp.22-29
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• 2010

Recent days, transition to ecological thought is being accelerating by environmental impact with a sustainable development. This symptom is no exception in architecture area. So is vernacular design affecting on modern architecture in many ways in terms of economical aspect and eco-friendly environment as well. Natural energy like solar power, environment, and terrestrial heat that applied in vernacular architecture is also widely accepted in name of 'sustainable energy' of which a design applied with ventilation and airing of natural wind is very useful & pragmatic in terms of economical reason. Accordingly, this study examined a relation between vernacular architecture and natural wind and compared it with traditional type and its feature of ventilation & airing. Ventilation & airing applied in the past can be divided into three categories: methods by convection, natural element, and architectural type. All these methods gave some pleasant felling indoors when there were no artificial energies. Even in modern age, such a ventilation & airing is being used with traditional type in different variety of materials, and it will be developed with modern technology without any extra cost in terms of sustainable expansion, and opened for further researches.