• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.156-159
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• 2008

Proper orthogonal decomposition is a statistical pattern analysis technique for finding the dominant components, called the proper orthogonal modes, in ensembles of spatially distributed data. We present recent ideas based on proper orthogonal decomposition (POD) and detailed experiments that yield new perspectives into the microscale structures. The linearized modeling technique based on POD is very useful to show the principal characteristics of the complex dynamic responses.

• Journal of Industrial Technology
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• v.28 no.B
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• pp.135-141
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• 2008

In this paper, the Proper Orthogonal Decomposition (POD) method, which is a statistical analysis technique to find the modal characteristics of a structure, is adapted to identify the modal parameters of a tall chimney structure. A wind force time history, which is applied to the structure, is obtained by a wind tunnel test of a scale down model. The POD method is applied on the wind force induced responses of the structure, and the true normal modes of the structure can be obtained. The modal parameters including, natural frequency, mode shape, damping ratio and kinetic energy of the structure can be estimated accurately. With these results, it may be concluded that the POD method can be applied to obtain accurate modal parameters from the wind-induced building responses.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2009.04a
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• pp.151-154
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• 2009

본 연구에서는 Proper Orthogonal Decomposition (POD)를 이용하여 공력축소모델을 구축하였다. 일반적으로 Euler equations과 같은 높은 정확도를 가지는 공력해석을 수행할 경우 많은 계산 비용이 발생하게 된다. 특히 공탄성 해석과 같이 수차례의 공력해석이 필요한 경우 그 비용은 더 증가하게 된다. 이러한 문제를 줄이기 위해서 축소모델(Reduced Order Model; ROM)의 개발은 반드시 필요하다. 공력축소모델을 구하는 방법 중 하나인 POD는 snapshot 데이터로부터 기저벡터를 구하고, 이들의 선형결합을 통하여 축소된 공간에서 해를 찾는 방법이다. 본 연구에서는 POD 기저벡터를 이용한 공력축소모델을 구축하고, 이를 전투기 날개문제에 적용하여 구하여진 정상상태 해와 Euler 해석 결과를 비교해 보았다. 또한 진동하는 익형문제에 적용하여 봄으로써 공탄성 해석에 적용 가능성 여부를 확인하였다.

• Wind and Structures
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• v.10 no.2
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• pp.153-176
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• 2007

The Proper Orthogonal Decomposition (POD) is a statistical method particularly suitable and versatile for dealing with many problems concerning wind engineering and several other scientific and humanist fields. POD represents a random process as a linear combination of deterministic functions, the POD modes, modulated by uncorrelated random coefficients, the principal components. It owes its popularity to the property that only few terms of the series are usually needed to capture the most energetic coherent structures of the process, and a link often exists between each dominant mode and the main mechanisms of the phenomenon. For this reason, POD modes are normally used to identify low-dimensional subspaces appropriate for the construction of reduced models. This paper provides a state-of-the-art and some prospects on POD, with special regard to its framework and applications in wind engineering. A wide bibliography is also reported.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1773-1777
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• 2008

The proper orthogonal decomposition(POD) is used to the modal analysis of microcantilever of dynamic mode atomic force microscopy(AFM). The proper orthogonal modes(POM) are extracted from vibrating signals of microcantilever when it resonates and taps the sample. We present recent ideas based on POD and detailed experiments that yield new perspectives into the microscale structures. The linearized modeling technique based on POD is very useful to show the principal characteristics of the complex dynamic responses.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.4
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• pp.414-421
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• 2010

The proper orthogonal decomposition(POD) is used to the vibration analysis of microcantilever in tapping mode atomic force microscopy(AFM). The proper orthogonal modes (POM) are extracted from vibrating signals of microcantilever when it resonates and taps the sample. We present recent ideas based on POD and detailed experiments that yield new perspectives into the microscale structures such as the tapping cantilever. The linearized modeling technique based on POD is very useful to show the principal characteristics of the complex dynamic responses of the AFM microcantilever.

• 한국전산유체공학회:학술대회논문집
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• 2010.05a
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• pp.40-42
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• 2010

Unsteady CFD results of the backward facing step (BFS) flow field is reconstructed by the low-dimenstional modes using the POD (Proper Orthogonal Decomposition) technique. Flow responses to the blowing or suction with various frequencies and amplitudes applied at the edge of the BFS can also be analysed using the same technique. The present technique can be effectively applied to the feedback flow control device.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.7
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• pp.535-540
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• 2019

The coupling between different models for MDO (Multi-disciplinary Optimization) greatly increases the complexity of the computational framework, while at the same time increasing CPU time and memory usage. To overcome these difficulties, POD (Proper Orthogonal Decomposition) and RBF (Radial Basis Function) are used to solve the optimization problem of determining the thickness of composites and sandwich cores when composite sandwich structures are used as aircraft wing skin materials. POD and RBF are used to construct surrogate models for the wing shape and the load data. Optimization is performed using the objective function and constraint function values which are obtained from the surrogate models.

• Wind and Structures
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• v.38 no.1
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• pp.1-13
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• 2024

In order to effectively simulate nonstationary stochastic turbulent wind fields, four separation hybrid (SEP-H) models are proposed in the present study. Based on the assumption that the lateral turbulence component at one single-point is uncorrelated with the longitudinal and vertical turbulence components, the fluctuating wind is separated into 2nV-1D and nV1D nonstationary stochastic vector processes. The first process can be expressed as double proper orthogonal decomposition (DPOD) or proper orthogonal decomposition and spectral representation method (POD-SRM), and the second process can be expressed as POD or SRM. On this basis, four SEP-H models of nonstationary stochastic turbulent wind fields are developed. In addition, the orthogonal random variables in the SEP-H models are presented as random orthogonal functions of elementary random variables. Meanwhile, the number theoretical method (NTM) is conveniently adopted to select representative points set of the elementary random variables. The POD-FFT (Fast Fourier transform) technique is introduced in frequency to give full play to the computational efficiency of the SEP-H models. Finally, taking a long-span bridge as the engineering background, the SEP-H models are compared with the dimension-reduction DPOD (DR-DPOD) model to verify the effectiveness and superiority of the proposed models.

• Journal of Industrial Technology
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• v.24 no.B
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• pp.29-36
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• 2004

The wind and wind-induced dynamic wind pressures fluctuate irregularly according to time and space. In this study, the proper orthogonal decomposition(POD) technique is applied to wind pressures acting on a tall tower model, and the following results are found: the along-wind and across-wind forces can be reconstructed by only four dominant POD modes, and the reconstructed errors are 4.71% and 22%, respectively for across-wind and along-wind directions. The physical meanings for dominant modes are also presented in the paper. The POD analysis can compress complex wind pressure data only by a few dominant modes and interpret spatio-temporal characteristics of wind pressure by novel way while existing statistical methods do not have such benefits.