• Journal of the military operations research society of Korea
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• v.28 no.2
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• pp.56-69
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• 2002

A technique of finding both probability density and distribution function for interkilling times is considered and demonstrated. An important result is that any arbitrary interfiring time random variables fit to this study, The interfiring renewal density function given a certain interfiring probability density function can be applied to obtain the corresponding interkilling renewal density function which helps us to estimate the expected number of killing events in a time period. The numerical inversion of Laplace transformation makes these possible and the results appear to be excellent. In case of ammunition supply is limited, an alternative way of getting the probability density function of time to the killing is investigated. The convolution technique may give us a means of settling for this new problem.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.607-610
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• 2005

A remeshing algorithm using tetrahedral elements has been developed, which is adapted to the mesh density map constructed by a posteriori error estimation. In the finite element analyses of metal forging processes, numerical error increases as deformation proceeds due to severe distortion of elements. In order to reduce the numerical error, the desired mesh sizes in each region of the workpiece are calculated by a posteriori error estimation and the density map is constructed. Piecewise density functions are then constructed with the radial basis function in order to interpolate the discrete data of the density map. The sample mesh is constructed based on the point insertion technique which is adapted to the density function and the mesh size is controlled by moving and deleting nodes to obtain optimal distribution according to the mesh density function and the quality optimization function as well. After finishing the redistribution process of nodes, a tetrahedral mesh is constructed with the redistributed nodes, which is adapted to the density map and resulting in good mesh quality. A goodness and adaptability of the constructed mesh is verified with a testing measure. The proposed remeshing technique is applied to the finite element analyses of forging processes.

• Structural Engineering and Mechanics
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• v.86 no.3
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• pp.349-359
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• 2023

This paper presents a technique for determining the optimal number of elements in stochastic finite element analysis based on reliability analysis. Using the change-of-variable perturbation stochastic finite element approach, the probability density function of the dynamic responses of stochastic structures is explicitly determined. This method combines the perturbation stochastic finite element method with the change-of-variable technique into a united model. To further examine the relationships between the random fields, discretization of the random field parameters, such as the variance function and the scale of fluctuation, is also performed. Accordingly, the reliability index is calculated based on the explicit probability density function of responses with Gaussian or non-Gaussian random fields in any number of elements corresponding to the random field discretization. The numerical examples illustrate the effectiveness of the proposed method for a one-dimensional cantilever reinforced concrete column and a two-dimensional steel plate shear wall. The benefit of this method is that the probability density function of responses can be obtained explicitly without the use simulation techniques. Any type of random variable with any statistical distribution can be incorporated into the calculations, regardless of the restrictions imposed by the type of statistical distribution of random variables. Consequently, this method can be utilized as a suitable guideline for the efficient implementation of stochastic finite element analysis of structures, regardless of the statistical distribution of random variables.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.56-58
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• 1996

The Preisach model needs a density function to simulate the hysteresis phenomena. To obtain this function, many experimental data obtained from the first order transition curves are required to get accurate density function. However, it is difficult to perform this procedure, especially for the hard magnetic materials. In this paper, we compare the density function obtained from the experimental data with that computed from the mathematical function like the Gaussian function, and propose a simple technique to get mathematical equation of the density function or Everett function which is obtained from the initial curve, major and minor loop.

• Journal of Ocean Engineering and Technology
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• v.10 no.3
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• pp.62-73
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• 1996

Numerical simulation is made of the three-dimensional wave breaking motion about a part of a floating offshore structure containing a circular cylinder mounted vertically onto a lower hull in regular periodic gravity wave generated by a numerical wave maker. TUMMAC-VIII finite-difference method is newly developed for such a problem. By use of density-function technique the three-dimensional wave breaking motion is approximately implenented in the framework of rectangular grid system. A porosity technique is devised for the implementation of the no-slip bydy boundary conditions. The generation of breaking waves by the interaction of incident waves with the structure is well simulated and interesting features of breaking waves are revealed with containing degree of quantitative and qualitative accuracy.

• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.1
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• pp.136-145
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• 1997

To analyzed ride quality and to predict durability in vehicle dynamics, it is essential to describe a road surface profile precisely. This paper presents a technique to generate road surface profiles in a spatial domain by using a power spectral density function. A single track power spectral density function is proposed to describe a road surface profile, which is also applicable for multi-track vehicle response analysis, The derived road surfaces are compared to ISO(International Organization for Standardization) standards and classifications, proposed by the MIRA(Motor Industry Research Association). The methodology in this paper is also proposed to generate road roughness description with a limited external data. A small amount of external curve data is combined with an internal PSD function to generate road surface roughness in a spatial domain.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.5 no.1
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• pp.65-72
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• 1993

An experiment has been carried out to identify flow patterns in a horizontal condensing flow with R-113. Characteristics of flow patterns were determined based upon a statistical analysis of differential pressure fluctuations at an orifice. The probability density function and power spectral density function of instantaneous pressure drop curves for various flow conditions were obtained. In comparison to the results of air-water flows, the flow patterns in a condensing flow such as annular, wavy, slug and plug could be identified. The experimental data determined by this technique were compared with the flow pattern maps suggested by other investigators. The result indicates that the statistical characteristics of differential pressure fluctuations at an orifice may be a useful tool for identifying flow patterns both in condensing flows and in adiabatic two-phase flows.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.503-512
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• 2006

In this paper, the Inverse Weibull distribution parameters have been estimated using a new estimation technique based on the non-parametric kernel density function that introduced as an alternative and reliable technique for estimation in life testing models. This technique will require bootstrapping from a set of sample observations for constructing the density functions of pivotal quantities and thus the confidence intervals for the distribution parameters. The performances of this technique have been studied comparing to the conditional inference on the basis of the mean lengths and the covering percentage of the confidence intervals, via Monte Carlo simulations. The simulation results indicated the robustness of the proposed method that yield reasonably accurate inferences even with fewer bootstrap replications and it is easy to be used than the conditional approach. Finally, a numerical example is given to illustrate the densities and the inferential methods developed in this paper.

• Journal of Magnetics
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• v.2 no.3
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• pp.105-109
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• 1997

The Preisach model neds a density function or Everett function for the hysterisis operator to simulate the hysteresis phenomena. To obtain the function, many experimental data for the first order transition curves are required. However, it needs so much efforts to measure the curves, especially for the hard magnetic materials. By the way, it is well known that the density function has the Gaussian distribution for the interaction axis on the Preisach plane. In this paper, we propose a simple technique to determine the distribution function or Everett function analytically. The initial magnetization curve is used for the distribution of the Everett function for the coercivity axis. A major, minor loop and the initial curve are used to get the Everett function for the interaction axis using the Gaussian distribution function and acceptable results were obtained.

• Communications for Statistical Applications and Methods
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• v.31 no.3
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• pp.337-347
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• 2024

Kernel density estimation is a prevalent technique employed for nonparametric density estimation, enabling direct estimation from the data itself. This estimation involves two crucial elements: selection of the kernel function and the determination of the appropriate bandwidth. The selection of the bandwidth plays an important role in kernel density estimation, which has been developed over the past decade. A range of methods is available for selecting the bandwidth, including the plug-in bandwidth. In this article, the proposed plug-in bandwidth is introduced, which leverages shifted Chebyshev series-based approximation to determine the optimal bandwidth. Through a simulation study, the performance of the suggested bandwidth is analyzed to reveal its favorable performance across a wide range of distributions and sample sizes compared to alternative bandwidths. The proposed bandwidth is also applied for kernel density estimation on real dataset. The outcomes obtained from the proposed bandwidth indicate a favorable selection. Hence, this article serves as motivation to explore additional plug-in bandwidths that rely on function approximations utilizing alternative series expansions.