• Journal of the Korean Geotechnical Society
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• v.39 no.12
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• pp.7-22
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• 2023

In this study, the limit range of input acceleration was investigated based on time domain and response spectrum analyses by considering the relative density, groundwater depth, and soil type. Special attention was paid to the input acceleration and shear modulus of soil, which affect pile behavior. The surrounding soil was identified as an elastoplastic material and subjected to FLAC3D analysis using the Mohr-Coulomb and Finn models as well as FB-Multiplier analysis using a nonlinear p-y curve for soil spring. Based on the analyses, the limit range of acceleration on the pile is much higher for SP soil than for SM soil, and the groundwater level tends to reduce the limit range of input acceleration, irrespective of soil conditions. The limit range of acceleration was mainly affected by the shear modulus. The limit range of acceleration with nonlinear soil behavior is proportional to the relative density of the surrounding soil.

• Communications for Statistical Applications and Methods
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• v.16 no.2
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• pp.335-348
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• 2009

Fuzzy regression is used as a complement or an alternative to represent the relation between variables among the forecasting models especially when the data is insufficient to evaluate the relation. Such phenomenon often occurs in seasonal time series data which require large amount of data to describe the underlying pattern. Semiparametric model is useful tool in the case where domain knowledge exists about the function to be estimated or emphasis is put onto understandability of the model. In this paper we propose fuzzy semiparametric support vector regression so that it can provide good performance on forecasting of the seasonal time series by incorporating into fuzzy support vector regression the basis functions which indicate the seasonal variation of time series. In order to indicate the performance of this method, we present two examples of predicting the seasonal time series. Experimental results show that the proposed method is very attractive for the seasonal time series in fuzzy environments.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2005.11a
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• pp.302-305
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• 2005

Recently, many methods to analyze signal have been proposed and representative methods are the Fourier transform and wavelet transform. In these methods, the Fourier transform represents signal with combination cosine and sine at all locations in the frequency domain. However, it doesn't provide time information that particular frequency occurs in signal and denpends on only the global feature of the signal. So, to improve these points the wavelet transform which is capable of multiresolution analysis has been applied to many fields such as speech processing, image processing and computer vision. And the wavelet transform, which uses changing window according to scale parameter, presents time-frequency localization. In this paper, we proposed a new approach using a wavelet of cosine and sine type and analyzed features of signal in a limited point of frequency-time plane.

• Computational Structural Engineering
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• v.6 no.2
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• pp.103-114
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• 1993

An advanced time-domain finite element formulation is presented for the displacement and stress analysis of isotropic, linear viscoelastic problems of a hereditary-type constitutive law. The semidiscrete finite element method with linear time-stepping scheme and an elastic-viscoelastic correspondence principle are used in the theoretical development. An efficient treatment of hereditary integral is introduced to improve the numerical accuracy, to reduce the computation time, and to avoid the use of large memory storage. Two-dimensional numerical examples of plane strain and plane stress are solved under the assumption on the material property of being elastic in dilatation and like three-element Voigt model in distorsion, and compared with the analytical solutions and the past numerical results to show the versatility and efficiency of the proposed method.

• Economic and Environmental Geology
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• v.33 no.1
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• pp.41-50
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• 2000

Geo-radar survey which has the advantage of high-resolution and relatively fast survey has been widely used for engineering and environmental problems. Three-dimensional effects have to be considered in the interpretation of geo-radar for high-resolution. However, there exists a trouble on the analysis of the three dimensional effects. To solve this problem an efficient three dimension numerical modeling algorithm is needed. Numerical radar modeling in three dimensional case requires large memory and long calculating time. In this paper, a finite difference method time domain solution to Maxwell's equations for simulating electromagnetic wave propagation in three dimensional media was developed to make economic algorithm which requires smaller memory and shorter calculating time. And in using boundary condition Liao absorption boundary. The numerical result of cross-hole radar survey for tunnel is compared with real data. The two results are well matched. To prove application to three dimensional analysis, the results with variation of tunnel's incident angle to survey cross-section and the result when the tunnel is parallel to the cross-section were examined. This algorithm is useful in various geo-radar survey and can give basic data to develop dat processing and inversion program.

• Proceedings of the KIEE Conference
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• 2002.11b
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• pp.167-170
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• 2002

This paper presents a mode estimation for the analysis of small signal stability in power system. The low frequency oscillation mode estimation is based on Prony method that is able to accurately compute the modal parameters (frequency and damping) of oscillation mode from time series. The time series or time domain data is obtained in TSA process. The method applied to a large scale power systems and compared on the eigenanalysis results.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.694-698
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• 2008

In hydrology, it is a difficult task to deal with multivariate time series such as modeling streamflows of an entire complex river system. Normal distribution based model such as MARMA (Multivariate Autorgressive Moving average) has been a major approach for modeling the multivariate time series. There are some limitations for the normal based models. One of them might be the unfavorable data-transformation forcing that the data follow the normal distribution. Furthermore, the high dimension multivariate model requires the very large parameter matrix. As an alternative, one might be decomposing the multivariate data into independent components and modeling it individually. In 1985, Lins used Principal Component Analysis (PCA). The five scores, the decomposed data from the original data, were taken and were formulated individually. The one of the five scores were modeled with AR-2 while the others are modeled with AR-1 model. From the time series analysis using the scores of the five components, he noted "principal component time series might provide a relatively simple and meaningful alternative to conventional large MARMA models". This study is inspired from the researcher's quote to develop a multivariate simulation model. The multivariate simulation model is suggested here using Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Three modeling step is applied for simulation. (1) PCA is used to decompose the correlated multivariate data into the uncorrelated data while ICA decomposes the data into independent components. Here, the autocorrelation structure of the decomposed data is still dominant, which is inherited from the data of the original domain. (2) Each component is resampled by block bootstrapping or K-nearest neighbor. (3) The resampled components bring back to original domain. From using the suggested approach one might expect that a) the simulated data are different with the historical data, b) no data transformation is required (in case of ICA), c) a complex system can be decomposed into independent component and modeled individually. The model with PCA and ICA are compared with the various statistics such as the basic statistics (mean, standard deviation, skewness, autocorrelation), and reservoir-related statistics, kernel density estimate.

• Structural Engineering and Mechanics
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• v.46 no.2
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• pp.179-196
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• 2013

An experimentally measured single footfall trace (SFT) from a walking subject needs to be extended into a continuous force curve, which can then be used as load for floor vibration serviceability assessment, or on which further analysis like discrete Fourier transform can be conducted. This paper investigates the accuracy, applicability and parametrical sensitivity of four extension methods, Methods I to IV, which extends the SFT into a continuous time history by the walking step rate, stride time, double support proportion and the double support time, respectively. Performance of the four methods was assessed by comparing their results with the experimentally obtained reference footfall traces in the time and frequency domain, and by comparing the vibrational response of a concrete slab subjected to the extended traces to that of reference traces. The effect of the extension parameter on each method was also explored through parametrical analysis. This study finds that, in general, Method I and II perform better than Method III and IV, and all of the four methods are sensitive to their extension parameter. When reliable information of walking rate or gait period is available in the test, Methods I or II is a better choice. Otherwise, Method III, with the suggested extension parameter of double support time proportion, is recommended.

• Journal of the Society of Naval Architects of Korea
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• v.47 no.2
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• pp.242-247
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• 2010

To consider effects of essential parameters of water impact pressure on dynamic structural responses of bow bottom structures, a parametric study for a ship bottom panel is carried out. The idealized pressure time history models were assumed by triangular and rectangular shapes in time domain. The main loading parameters are duration time and peak pressure value maintaining the same impulse value. The structural models for local bottom stiffened panels of a container ship are analysed. The natural frequency analysis and transient dynamic response analysis are performed using MSC/NASTRAN. Added mass effects of contacting water are considered and the pressure distributions are assumed to be uniform in the whole water contacting surface. The effects of loading parameters on the structural responses, especially maximum displacements, are considered. Besides the peak pressure value, effects of duration time correlated with natural frequencies are thought to be the important parameters.

• Structural Engineering and Mechanics
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• v.45 no.1
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• pp.95-110
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• 2013

In the recent decade, practical of wavelet technique is being utilized in various domain of science. Particularly, engineers are interested to the wavelet solution method in the time series analysis. Fundamentally, seismic responses of structures against time history loading such as an earthquake, illustrates optimum capability of systems. In this paper, a procedure using particularly discrete Haar wavelet basis functions is introduced, to solve dynamic equation of motion. In the proposed approach, a straightforward formulation in a fluent manner is derived from the approximation of the displacements. For this purpose, Haar operational matrix is derived and applied in the dynamic analysis. It's free-scaled matrix converts differential equation of motion to the algebraic equations. It is shown that accuracy of dynamic responses relies on, access of load in the first step, before piecewise analysis added to the technique of equation solver in the last step for large scale of wavelet. To demonstrate the effectiveness of this scheme, improved formulations are extended to the linear and nonlinear structural dynamic analysis. The validity and effectiveness of the developed method is verified with three examples. The results were compared with those from the numerical methods such as Duhamel integration, Runge-Kutta and Wilson-${\theta}$ method.