• 한국태양에너지학회 논문집
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• 제39권6호
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• pp.93-112
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• 2019

In this paper, a very new web-based software for renewable energy system (RES) design and economic evaluation was introduced. This solution would provide the precise RES estimation service including not only photovoltaic (PV), wind turbine (WT) and fuel cell (FC) individually but also energy storage system (ESS) as combined forms with PV or WT. The three reasons why we ought to develop it are: First, the standardized tool suitable to the domestic environment for estimating power generation from RES facilities and economic evaluation is required. Secondly, the standardized tool is needed to spread domestic RES supply policy and to promote the new industry in the micro-grid field. The last, the reliability of economic evaluation should be enhanced more for new facilities. To achieve those aims, the weather database of one hundred locations have established and the RES facility database has also constructed. For the energy management, mathematical models for PV, WT, ESS and FC were developed. As a final phase, the analytical process to evaluate economics has performed with field data verification.

• 한국음향학회지
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• 제37권5호
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• pp.292-299
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• 2018

자동차 외장 디자인은 차량의 첫인상을 만들지만, 엔지니어링 입장에서는 공력 및 바람소리 성능에 중요한 요소이다. 외장 디자인은 차량의 프로토 타입 시점에 변경하기는 불가능하기 때문에 차량 초기 디자인 단계에서 외장 디자인을 점검하고, 바람소리 수준을 예측하는 것이 중요하게 된다. 외장 디자인 요소 중 차량 바람소리에 중요한 A필라와 와이퍼에 대한 바람소리 해석 기법은 개발되어 적용되고 있으나, 해석 및 모델링 과정이 복잡하고 시간이 많이 소모되기 때문에 엔지니어입장에서 디자이너 및 설계자와 함께 A필라 및 와이퍼 형상별 기여도를 검토하기엔 시간적인 여유가 부족하게 된다. 본 논문에서는 최적화를 위하여 A필라 형상 및 와이퍼 형상에 따라 바람소리 해석 S/W인 PowerFLOW(PowerClay 모델링 S/W, SEA-Baced(Statistical Energy Analysis-Based) 실내소음 해석툴, Turbulent Acoustic Power 해석툴)를 이용하여 실내소음을 해석적으로 예측하고, 예측한 결과를 이용하여 반응 표면법을 이용하는 최적화 S/W인 modeFRONTIER를 이용하여 디자인 요소에 대한 반응면을 구축하여, 디자인 요소와 실내 소음간의 상관성을 구성하여, 디자인 단계에서 A필라와 와이퍼에 의한 바람소리 수준을 예측하였다. 최적화 결과 및 반응면 구축 예측 결과에 대하여 실제 시험을 통하여 예측 경향성을 판단하고, 해석 및 예측에 대한 신뢰성을 확인하였다. 최종적으로 해석 및 반응면 구축 과정을 통하여 A필라 및 와이퍼에 대한 차종별 CAT(Computer Aided Test) 분석툴을 개발하고, 실제 차량 개발 과정에 적용하여 효용성을 확인하였다.

• Wind and Structures
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• 제31권4호
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• pp.351-362
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• 2020

In this study, the impact of roof slope on the flow characteristics over low-sloped gable roofs was investigated using steady computational fluid dynamics (CFD) simulations based on a k-ω SST turbulence model. A measurement database of the flow field over a scaled model of 15° was created using particle image velocimetry (PIV). Sensitivity analyses for the grid resolutions and turbulence models were performed. Among the three common Reynolds-averaged Navier-Stokes equations (RANS) models, the k-ω SST model exhibited a better performance, followed by the RNG model and then the realizable k-ε model. Next, the flow properties over the differently sloped (0° to 25°) building models were determined. It was found that the effect of roof slope on the flow characteristics was identified by changing the position and size of the separation bubbles, 15° was found to be approximately the sensitive slope at which the distribution of the separation bubbles changed significantly. Additionally, it is suggested additional attention focused on the distributions of the negative pressure on the windward surfaces (especially 5° and 10° roofs) and the possible snow redistribution on the leeward surfaces.

• 한국자동차공학회논문집
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• 제13권1호
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• pp.1-8
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• 2005

The spray prepared for direct fuel injection into cylinder is of great importance in a DISI(Direct Injection Spark Ignition) engine. The interaction between air flow and fuel spray was investigated in a steady flow system embodied in a wind tunnel to simulate the variety of in-cylinder flow conditions in the DISI engine. The Mie-scattering images presented the macroscopic view of the liquid spray fields interacting with cross-flow Particle sizes of fuel droplets were measured with phase Doppler anemometer(PDA) system. A faster cross-flow field made SMD larger and $D_10$ smaller. The atomization and evaporation processes with a DISI injector were observed and consequently utilized to construct the database on the spray and fuel-air mixing mechanism as a function of the flow characteristics.

• Steel and Composite Structures
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• 제49권2호
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• pp.181-196
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• 2023

Marine structures including offshore wind turbines (OWTs) always work under cyclic loads, which arouses much attention on the fatigue design. The tripod substructure is one of the typical foundation forms for fixed OWTs. The three-planar tubular Y-joint (3Y joint) is one of the important components in fatigue design as it is most likely to have cracks. With the existence of the multiplanar interaction effect, calculating the hot spot stress (HSS) of 3Y joints is complicated. To assist with fatigue design, the distributions of stress concentration factor (SCF) and multiplanar interaction factor (MIF) along weld toe curves induced by the out-of-plane bending moment are explored in this study. An FE analysis method was first developed and verified against experimental results. This method was applied to build a numerical database including 1920 FE models covering common ranges of geometric parameters. A parametric study has been carried out to reveal the distribution patterns of SCF and MIF. After multidimensional nonlinear fittings, SCF and MIF distribution formulas have been proposed. Accuracy and reliability checking prove that the proposed formulas are suitable for calculating the HSS of 3Y joints.

• 한국인터넷방송통신학회논문지
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• 제12권6호
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• pp.285-289
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• 2012

본 논문에서는 유비쿼터스 컴퓨팅에 의한 농장 정보화 시스템을 설계하였다. 이를 위하여 임산물 생육을 위한 관수시설을 설치하였고 레이더 센서를 장착한 통합 센싱 시스템을 온도와 습도, 풍향 등을 측정하기 위해 구축하였다. 또한 현장 근무자들이 임산물의 생육 조건들을 직접 제어하고 모니터링할 수 있도록 관리 프로그램을 제공하였으며, 데이터베이스를 구축하여 모든 센서들을 연결한 모니터링 시스템과 관리 시스템에서 획득한 정보로 생육 환경을 분석하기 위해 저장하도록 하였다.

• 한국항공우주학회지
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• 제37권12호
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• pp.1252-1257
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• 2009

항공기의 외부장착물 분리해석이 가능한 Off-line 6-DOF 시뮬레이션 프로그램을 개발 하였다. 개발한 프로그램은 풍동시험이나 CFD 해석을 통해 구축된 공력 데이터베이스를 이용하여 외부장착물의 분리 궤적을 예측할 수 있다. 공력 계수의 계산에는 flow angle 방법을 적용하였으며 분리 궤적 계산에는 사출력과 구속 조건의 적용이 가능하도록 하였다. 개발한 프로그램을 이용하여 군용항공기의 분리 궤적을 계산하였으며 이를 CTS 시험 결과와 비교하였다.

• International Journal of Computer Science & Network Security
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• 제23권3호
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• pp.10-16
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• 2023

The ever-increasing amount of data generated by various industries and systems has led to the development of data mining techniques as a means to extract valuable insights and knowledge from such data. The electrical energy industry is no exception, with the large amounts of data generated by SCADA systems. This study focuses on the analysis of historical data recorded in the SCADA database of the Libyan Electricity Company. The database, spanned from January 1st, 2013, to December 31st, 2022, contains records of daily date and hour, energy production, temperature, humidity, wind speed, and energy consumption levels. The data was pre-processed and analyzed using the WEKA tool and the Apriori algorithm, a supervised machine learning technique. The aim of the study was to extract association rules that would assist decision-makers in making informed decisions with greater efficiency and reduced costs. The results obtained from the study were evaluated in terms of accuracy and production time, and the conclusion of the study shows that the results are promising and encouraging for future use in the Libyan Electricity Company. The study highlights the importance of data mining and the benefits of utilizing machine learning technology in decision-making processes.

• 한국가시화정보학회지
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• 제21권2호
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• pp.83-90
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• 2023

The shape of an airfoil is a critical factor in determining aerodynamic characteristics such as lift and drag. Aerodynamic properties of an airfoil have a decisive impact on the performance of various engineering applications, including airplane wings and wind turbine blades. Therefore, it is essential to analyze the aerodynamic characteristics of airfoils. Various analytical tools such as experiments, computational fluid dynamics, and Xfoil are used to perform these analyses, but each tool has its limitation. In this study, airfoil parameterization, image recognition, and artificial intelligence are combined to overcome these limitations. Image and coordinate data are collected from the UIUC airfoil database. Airfoil parameterization is performed by recognizing images from image data to build a database for deep learning. Trained model can predict the aerodynamic characteristics not only of airfoil images but also of sketches. The mean absolute error of untrained data is 0.0091.

• 천문학회보
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• 제38권2호
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• pp.93.1-93.1
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• 2013

The Earth's radiation belts consist of an inner belt and an outer belt, being separated by the slot region. It is well known that the variations of the inner edge of the outer belt and the location of the plasmapause (Lpp) are closely related to each other. Different waves exist inside and outside the plasmasphere, playing different roles in the particle dynamics. The plasmapause is well known to be influenced by solar wind conditions and geomagnetic disturbances. Therefore, it is important to precisely determine the location of the plasmapause and develop a prediction scheme. In this study, we identified the location of the plasmapause using the plasma density data from the Time History of Events and Macroscale Interactions During Substorms (THEMIS). The plasmapause is determined by requiring density gradient of a factor of 15 within L-change = 0.5. We statistically determined Lpp as a function of preceding geomagnetic indices. Also, we determined the relations between Lpp and preceding solar wind conditions by estimating correlation coefficients. These relations give us predicting models of Lpp as a function of preceding solar wind parameters and geomagnetic indices. As our database covers a period over the ascending phase from near-sunspot minimum, our statistical results differ somewhat from previous works that cover near-sunspot maximum. Finally, we give some comparative examples obtained from the Van Allen Probes data.