• Earthquakes and Structures
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• v.5 no.4
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• pp.439-459
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• 2013

Main objective of the present study is to determine the statistical properties and suitable probability distribution functions of spectral displacements from nonlinear static and nonlinear dynamic analysis within the frame work of Monte Carlo simulation for typical low rise and high rise RC framed buildings located in zone III and zone V and designed as per Indian seismic codes. Probabilistic analysis of spectral displacement is useful for strength assessment and loss estimation. To the author's knowledge, no study is reported in literature on comparison of spectral displacement including the uncertainties in capacity and demand in Indian context. In the present study, uncertainties in capacity of the building is modeled by choosing cross sectional dimensions of beams and columns, density and compressive strength of concrete, yield strength and elastic modulus of steel and, live load as random variables. Uncertainty in demand is modeled by choosing peak ground acceleration (PGA) as a random variable. Nonlinear static analysis (NSA) and nonlinear dynamic analysis (NDA) are carried out for typical low rise and high rise reinforced concrete framed buildings using IDARC 2D computer program with the random sample input parameters. Statistical properties are obtained for spectral displacements corresponding to performance point from NSA and maximum absolute roof displacement from NDA and suitable probability distribution functions viz., normal, Weibull, lognormal are examined for goodness-of-fit. From the hypothesis test for goodness-of-fit, lognormal function is found to be suitable to represent the statistical variation of spectral displacement obtained from NSA and NDA.

• Transactions of the Korean Society of Mechanical Engineers
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• v.9 no.6
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• pp.691-698
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• 1985

This paper presents a method for the identification of vibration sources in a multiple input system where the input source may be coherent with each other. Using multi-dimensional spectral analysis, it is found that one of the most significant vibration sources of a gasoline engine is the pressure variation within the cylinder. In this analysis the concepts of residual spectral analysis and the partial coherence function are applied. Finally, the overall levels of the acceleration on the cylinder block obtained by multi-dimensional spectral analysis are compared with those by the frequency response function approach. The experimental results have shown a good agreement with the results calculated by this method the input sources are coherent strongly each other.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.36T no.1
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• pp.32-40
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• 1999

The analysis of logic function is performed by the spectral coefficients which transform the function domain data into the spectral domain data. By using the spectral techniques, analysis of MVL circuits is performaed, and the fault analysis and detecting methods of multiple-valued logic circuits are proposed in this paper.

• Structural Engineering and Mechanics
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• v.75 no.3
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• pp.311-325
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• 2020

In applying the spectral stochastic finite element methods to the frequency response analysis, the conventional methods are known to give unstable and inaccurate results near the natural frequencies. To address this issue, a new sensitivity based stabilized formulation for stochastic frequency response analysis is proposed in this paper. The main difference over the conventional spectral methods is that the polynomials of random variables are applied to both numerator and denominator in approximating the harmonic response solution. In order to reflect the resonance behavior of the structure, the denominator polynomials is constructed by utilizing the natural frequency sensitivity and the random mode superposition. The numerator is approximated by applying a polynomial chaos expansion, and its coefficients are obtained through the Galerkin or the spectral projection method. Through various numerical studies, it is seen that the proposed method improves accuracy, especially in the vicinities of structural natural frequencies compared to conventional spectral methods.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.592-600
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• 2006

The pattern recognition of the complicated grasping operation based on electroencephalography (simply named as EEG) is very helpful on realtime control of the robotic hand. In the paper, a new spectral feature analysis method based on Band Pass Filter (simply named as BPF) and Power Spectral Analysis (simply named as PSA) is presented for discriminating the complicated grasping operations. By analyzing the spectral features of grasping operations with the use of the two-channel EEG measurement system and the pattern recognition of the BP neural network, the degree of recognition by the traditional spectral feature method based on FFT and the new spectral features method based on BPF and PSA could be compared. The results show that the proposed method provides highly improved performance than the traditional one because the new method has two obvious advantages such as high recognition capability and the fast learning speed.

• Structural Engineering and Mechanics
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• v.39 no.5
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• pp.669-682
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• 2011

A Chebyshev spectral method (CSM) for the dynamic analysis of non-uniform Timoshenko beams under various boundary conditions and concentrated masses at their ends is proposed. The matrix-based Chebyshev spectral approach was used to construct the spectral differentiation matrix of the governing differential operator and its boundary conditions. A matrix condensation approach is crucially presented to impose boundary conditions involving the homogeneous Cauchy conditions and boundary conditions containing eigenvalues. By taking advantage of the standard powerful algorithms for solving matrix eigenvalue and generalized eigenvalue problems that are embodied in the MATLAB commands, chebfun and eigs, the modal parameters of non-uniform Timoshenko beams under various boundary conditions can be obtained from the eigensolutions of the corresponding linear differential operators. Some numerical examples are presented to compare the results herein with those obtained elsewhere, and to illustrate the accuracy and effectiveness of this method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.409-414
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• 2005

In the literatures, the FFT-based SAM has been well applied to the computation of the steady-state responses of discrete dynamic systems. In this paper, a fast fourier transforms (FFT)-based spectral analysis method (SAM) is proposed fur the dynamic analysis of spectral element models subjected to the non-zero initial conditions. However, the FFT-based SAM has not yet been developed for the continuous systems represented by the spectral element model.

• Aerospace Engineering and Technology
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• v.6 no.2
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• pp.104-110
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• 2007

Analyzed is the spectral response profile specification used for the infrared (IR) channels of the meteorological imagers of GOES series geostationary satellites. The variation characteristics of effective wavelength and effective input radiance due to the change of the spectral response function profile within the imager performance specification are analyzed in order to propose how to understand the spectral response specification. As an analysis approach, at first a center symmetrical spectral response function and 4 worst case spectral response functions are selected within the spectral response specification, and then effective wavelength and effective input radiance are calculated for each spectral response function. As a result, the maximum allowable ranges of effective wavelength and effective input radiance are provided per the spectral response specification.

• ETRI Journal
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• v.38 no.3
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• pp.540-550
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• 2016

Spectral clustering is a powerful tool for exploratory data analysis. Many existing spectral clustering algorithms typically measure the similarity by using a Gaussian kernel function or an undirected k-nearest neighbor (kNN) graph, which cannot reveal the real clusters when the data are not well separated. In this paper, to improve the spectral clustering, we consider a robust similarity measure based on the shared nearest neighbors in a directed kNN graph. We propose two novel algorithms for spectral clustering: one based on the number of shared nearest neighbors, and one based on their closeness. The proposed algorithms are able to explore the underlying similarity relationships between data points, and are robust to datasets that are not well separated. Moreover, the proposed algorithms have only one parameter, k. We evaluated the proposed algorithms using synthetic and real-world datasets. The experimental results demonstrate that the proposed algorithms not only achieve a good level of performance, they also outperform the traditional spectral clustering algorithms.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11b
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• pp.85-89
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• 2005

For the analysis of a vibrating two dimensional structure such as the simply supported rectangular plate, Spectral Finite Element Method (SFEM) has been studied. Under the condition that two parallel edges are simply supported at least and the other two edges can be arbitrary, Spectral Finite Element has been developed. Using this element SFEM is applied to the vibrating rectangular plate which all edges are simply supported, and obtain the frequency response function in frequency domain and the dynamic response in time domain. To evaluate these results normal mode method and finite element method (FEM) are also accomplished and compared. It is seen that SFEM is more powerful analysis tool than FEM in high frequency range.