• Proceedings of the Computational Structural Engineering Institute Conference
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• 2010.04a
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• pp.171-174
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• 2010

적절한 근사화 과정을 통하여 구축된 축소 시스템은 전체 시스템의 거동을 적은 수의 정보를 통하여 효과적으로 표현할 수 있다. 효과적인 시스템 축소를 위하여 본 연구에서는 주파수 영역 Karhunen-Loeve (Frequency-domain Karhunen-Loeve, FDKL) 기법과 시스템 등가 확장 축소 과정(System equivalent expansion reduction process, SEREP)을 연동한 축소 기법을 제안한다. 적합직교분해(Proper orthogonal decomposition)의 한 방법인 FDKL기법을 통하여 최적모드(Optimal mode)를 구하고 이에 SEREP을 적용하여 자유도 변환 행렬을 구한다. 이때 주자유도 선정은 2단계 축소기법을 적용한다. 최종적으로 제안된 기법은 수치예제를 통하여 검증한다.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.1
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• pp.1-7
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• 2020

The wind responses of twin buildings are determined by the characteristics of wind loads and the dynamic characteristics of the structural systems of the buildings. In this study, the characteristics of wind pressure that influence wind responses were identified for two different spacings between the twin buildings using a wind tunnel test and the proper orthogonal decomposition (POD) method. Structural dynamic characteristics were also identified using 3D structural system modeling. The double modal transformation method was utilized to evaluate the characteristics of wind pressure for across-wind and along-wind conditions and the effect of the dynamic characteristics of each structure on the wind responses. The channeling and vortex effects were identified through the POD method. Across-wind loads were significantly affected by the spacings between the twin buildings, whereas along-wind loads were minimally affected. Similarly, while using the double modal transformation method, a significant difference was noticed in case of the cross-participation coefficients in the across-wind direction condition for the different spacings between the buildings; however, the along-wind direction condition showed negligible difference. Therefore, the spacing between the two buildings plays a more important role in across-wind responses compared to along-wind responses.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.6
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• pp.309-314
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• 2018

The wind load and structural characteristics of a twin building are more complex than those of conventional high-rise buildings. The pressure load due to wind on a twin building was therefore measured via wind tunnel experiments to analyze such characteristics. The wind pressure pattern was then deduced from measured data using proper orthogonal decomposition. Channeling and vortex shedding were observed in the first and second modes, respectively. The along-wind loads on the two buildings featured a positive correlation and the cross-wind loads featured no correlation. Such a correlation affected the wind-induced displacement. The structural member connecting the two buildings had an insignificant effect on the positive correlation, but it notably reduced the wind-induced displacement with a negative correlation.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.04a
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• pp.177-178
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• 2014

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.11
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• pp.1073-1079
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• 2009

The proper orthogonal decomposition (POD) method can identify principal modes that optimally capture the energy content from large multi-dimensional data set. In this study unsteady pressure fields on the rotor blade surface of a helicopter in forward flight are expressed by a reduced order model based on the POD method. Special modes containing high energy are analyzed to investigate the aerodynamic characteristics in more efficient way. The CFD simulation of flowfields around helicopter rotor blade in hovering motion is also conducted to validate its prediction with experimental result. In the process 7 modes containing energy ratio 99% from 240 snapshots information are identified and utilized to construct a reduced order model.

• Journal of computational fluids engineering
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• v.22 no.1
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• pp.59-66
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• 2017

The guideline of selecting the number of snapshot dataset, $N_s$ in proper orthogonal decomposition(POD) was presented via the analysis of Eigen values based on the singular value decomposition(SVD). In POD, snapshot datasets from the solutions of Euler or Navier-Stokes equations are utilized to SVD and a reduced order model(ROM) is constructed as the combination of Eigen vectors. The ROM is subsequently applied to reconstruct the flowfield data with new set of flow conditions, thereby enhancing the computational efficiency. The overall computational efficiency and accuracy of POD is dependent on the number of snapshot dataset; however, there is no reliable guideline of determining $N_s$. In order to resolve this problem, the order of maximum to minimum Eigen value ratio, O(R) from SVD was analyzed and presented for the decision of $N_s$; in case of steady flow, $N_s$ should be determined to make O(R) be $10^9$. For unsteady flow, $N_s$ should be increased to make O(R) be $10^{11\sim12}$. This strategy of selecting the snapshot dataset was applied to two dimensional NACA0012 airfoil and vortex flow problems including steady and unsteady cases and the numerical accuracies according to $N_s$ and O(R) were discussed.

• Journal of the Korean Society of Visualization
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• v.6 no.1
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• pp.34-40
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• 2008

The flow characteristics in a confined slot jet impinging on a flat plate were investigated in low Reynolds number regime (Re$\leq$1,000) by using time-resolved particle image velocimetry technique. The jet Reynolds number was varied from 404 to 1026, where it is presumed that the transient regime exists. It is found that the vortical structures in the shear layer are developed with increasing Reynolds number and that the jet remains steady at the Reynolds number of 404. Vortical structures and their temporal evolution are verified and the results were compared with previous numerical studies.

• Journal of Aerospace System Engineering
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• v.16 no.4
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• pp.17-27
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• 2022

In this study, a deep learning-based network that can predict the aerodynamic characteristics of airfoils was designed, and the feasibility of the proposed network was confirmed by applying aerodynamic data generated by Xfoil. The prediction of aerodynamic characteristics according to the variation of airfoil thickness was performed. Considering the angle of attack, the coordinate data of an airfoil is converted into image data using signed distance function. Additionally, the distribution of the pressure coefficient on airfoil is expressed as reduced data via proper orthogonal decomposition, and it was used as the output of the proposed network. The test data were constructed to evaluate the interpolation and extrapolation performance of the proposed network. As a result, the coefficients of determination of the lift coefficient and moment coefficient were confirmed, and it was found that the proposed network shows benign performance for the interpolation test data, when compared to that of the extrapolation test data.

• 한국가시화정보학회:학술대회논문집
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• 2007.11a
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• pp.97-100
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• 2007

A new evaluation method for the performance tests of the frozen air in a refrigerator using PIV(Particle Imaging Velocimetry) and POD(Proper Orthogonal Decomposition) techniques is introduced. A two-door refrigerator model was tested for the experiments. Actual temperature measurements were carried out for the drawer No.4 in refrigerator. By evaluating the characteristics of the interior flow of the refrigerator, an optimal shape of the drawer could be suggested through the PIV evaluation test. In this research, in order to find influences the turbulent kinetic energy contribution associated with the dynamic structures, we executed a POD analysis using the method of snapshots and the instantaneous fluctuating velocity field.

• Journal of the Korean Society of Visualization
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• v.15 no.2
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• pp.59-67
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• 2017

To verify floatability of ABB (Air bubble barrier), we compared bubble swarm behavior with and without the air-driven ejector. Experiment was conducted using the fabricated air-driven ejector with 5 mm nozzle on the bottom of 1 m3 water tank. Reynolds number of air in the nozzle was ranged 1766-13248. We analyzed data with statistical method using image processing, particle mage velocimetry (PIV) and proper orthogonal decomposition (POD) analysis. As a result of POD analysis, there was no significant eigenmode in bubbly flow generated from the ejector. It means that more complex turbulent flows were formed by the ejector, thereby (1) making bubbles finer, (2) promoting three-dimensional energy transfer between bubble and water, and (3) making evenly distributed velocity profile of water. It is concluded that the air-driven ejector could enhance the performance of ABB.