• Journal of computational fluids engineering
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• v.11 no.4 s.35
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• pp.62-66
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• 2006

High-speed flight vehicle have various cavities. The supersonic cavity flow is complicated due to vortices, flow separation, reattachment, shock waves and expansion waves. The general cavity flow phenomena includes the formation and dissipation of vortices, which induce oscillation and noise. The oscillation and noise greatly affect flow control, chemical reaction, and heat transfer processes. The supersonic cavity flow with high Reynolds number is characterized by the pressure oscillation due to turbulent shear layer, cavity geometry, and resonance phenomenon based on external flow conditions. The resonance phenomena can damage the structures around the cavity and negatively affect aerodynamic performance and stability. In the present study, we performed numerical analysis of cavities by applying the unsteady, compressible three dimensional Reynolds-Averaged Navier-Stokes(RANS) equations with the ${\kappa}-{\omega}$ turbulence model. The cavity model used for numerical calculation had a depth(D) of 15mm cavity aspect ratio (L/D) of 3, width to spanwise ratio(W/D) of 1.0 to 5.0. Based on the PSD(Power Spectral Density) and CSD(Cross Spectral Density) analysis of the pressure variation, the dominant frequency was analyzed and compared with the results of Rossiter's Eq.

• The Korean Journal of Applied Statistics
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• v.21 no.3
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• pp.547-560
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• 2008

It is well known that spectral density function determines auto-covariance function of stationary time-series data and smoothed periodogram is a consistent estimator of spectral density function. Recently, Kim and Park (2007) showed that smoothed- periodogram based distances performs very well for the classification. In this paper, we introduce classification methods with smoothed periodogram and apply the approaches to the monthly precipitation measurements obtained from January, 1987 through December, 2007 at 22 locations in South Korea.

• Smart Structures and Systems
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• v.15 no.1
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• pp.15-40
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• 2015

This paper proposes a structural damage identification approach based on the power spectral density transmissibility (PSDT), which is developed to formulate the relationship between two sets of auto-spectral density functions of output responses. The accuracy of response reconstruction with PSDT is investigated and the damage identification in structures is conducted with measured acceleration responses from the damaged state. Numerical studies on a seven-storey plane frame structure are conducted to investigate the performance of the proposed damage identification approach. The initial finite element model of the structure and measured acceleration measurements from the damaged structure are used for the identification with a dynamic response sensitivity-based model updating method. The simulated damages can be identified accurately without and with a 5% noise effect included in the simulated responses. Experimental studies on a steel plane frame structure in the laboratory are performed to further verify the accuracy of response reconstruction with PSDT and validate the proposed damage identification approach. The locations of the introduced damage are detected accurately and the stiffness reductions in the damaged elements are identified close to the true values. The identification results demonstrated the accuracy of response reconstruction as well as the correctness and efficiency of the proposed damage identification approach.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1A
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• pp.59-67
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• 2008

Acceleration time history used in the seismic analysis of nuclear power plant structures should envelop a target power spectral density (PSD) function in addition to the design response spectrum in order to have sufficient energy at each frequency for the purpose of ensuring adequate load. The safety for complex long-span highway bridges cannot be over-emphasize. An alternative method to improve the seismic capacity is to ensure the minimum PSD function of the applied seismic load. This study proposes a technical scheme to obtain the reference power spectral density function by using artificial earthquakes which are compatible with the highway bridge design spectrum.

• Earthquakes and Structures
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• v.4 no.4
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• pp.383-396
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• 2013

In earthquake engineering area, the critical excitation method is an approach to find the most severe earthquake subjected to the structure. However, given some earthquake constraints, such as intensity and power, the critical excitations have spectral density functions that often resonate with the first modes of the structure. This paper presents a non-stationary critical excitation that is capable of exciting the main modes of the structure using a non-uniform power spectral density (PSD) that is similar to natural earthquakes. Thus, this paper proposes a new method to estimate the power and intensity of earthquakes. Finally, a new method for the linear seismic design of structures using a modified non-stationary critical excitation is proposed.

• Journal of the Korean Statistical Society
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• v.23 no.1
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• pp.79-88
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• 1994

This paper concerns the problem of estimating the spectral density function in the analysis of stationary time series data. A kernel type estimate is considered, which entails choice of bandwidth. A data-driven bandwidth choice is proposed, and it is obtained by plugging some suitable estimates into the unknown parts of a theoretically optimal choice. A theoretical justification is give for this choice in terms of how far it is from the theoretical optimum. Furthermore, an empirical investigation is done. It shows that the data-driven choice yields a reliable spectrum estimate.

• Journal of applied mathematics & informatics
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• v.28 no.1_2
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• pp.515-521
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• 2010

In multivariate analysis, the inversion formula of the Stieltjes transform is used to find the density of a spectral distribution of random matrices of sample covariance type. Let $B_n\;=\;\frac{1}{N}Y_nY_n^TT_n$ where $Y_n\;=\;[Y_{ij}]_{n\;{\times}\;N}$ is with independent, identically distributed entries and $T_n$ is an $n\;{\times}\;n$ symmetric non-negative definite random matrix independent of the $Y_{ij}$'s. In the present paper, using the inversion formula of the Stieltjes transform, we will find that the limiting distribution of $B_n$ has a continuous density function away from zero.

• Structural Engineering and Mechanics
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• v.68 no.1
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• pp.39-51
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• 2018

In this study, a frequency domain model updating method is presented using power spectral density (PSD) data. It uses the sensitivity of PSD function with respect to the unknown structural parameters through a decomposed form of transfer function. The stiffness parameters are captured with high accuracy through solving the sensitivity equations utilizing the least square approach. Using numerically noise polluted data, the model updating results of a truss model prove robustness of the method against measurement and mass modelling errors. Results prove the capabilities of the method for parameter estimation using highly noise polluted data of low ranges of excitation frequency.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.6C
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• pp.569-574
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• 2006

We derive the general power spectral density of functions of ultra-wide bandwidth (UWB) systems using a pulse position modulation. We propose a new UWB system with a preferable line spectrum properies and a good bit error rate performance.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.298-303
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• 2003

The eccentric rotor system has various problems by vibration of unbalance mass. Specially, it is difficult to analyze vibration problem for the drum washing machine due to correlation of transmission paths. We analyze the mechanical structure by multidimensional spectral density to identify the maximum vibration magnitude at the frequency domain. It estimates the coherence function of the signals to pass the transmission paths. In case of the drum washing machine, because the transmission paths are correlated partially it needs to determinate the priority ranking. And the correlated parts are eliminated using conditioned spectral density function. Finally the shielding effect method confirms the reasonability of the modeling.