• Advances in nano research
• /
• v.16 no.4
• /
• pp.413-426
• /
• 2024

This paper investigates the dynamic behavior of a simply supported viscoelastic plate made of functionally graded carbon nanotube reinforced composite under dynamic loading. Carbon nanotubes are distributed in 5 different shapes: U, V, A, O and X, depending on the shape they form through the thickness of the plate. The displacement fields are derived in the Laplace domain using a higher-order shear deformation theory. Equations of motion are obtained through the application of the energy method and Hamilton's principle. The resulting equations of motion are solved using Navier's method. Transforming the Laplace domain displacements into the time domain involves Durbin's modified inverse Laplace transform. To validate the accuracy of the developed algorithm, a free vibration analysis is conducted for simply supported plate made of functionally graded carbon nanotube reinforced composite and compared against existing literature. Subsequently, a parametric forced vibration analysis considers the influence of various parameters: volume fractions of carbon nanotubes, their distributions, and ratios of instantaneous value to retardation time in the relaxation function, using a linear standard viscoelastic model. In the forced vibration analysis, the dynamic distributed load applied to functionally graded carbon nanotube reinforced composite viscoelastic plate is obtained in terms of double trigonometric series. The study culminates in an examination of maximum displacement, exploring the effects of different carbon nanotube distributions, volume fractions, and ratios of instantaneous value to retardation times in the relaxation function on the amplitudes of maximum displacements.

• Journal of the Korean Data and Information Science Society
• /
• v.20 no.6
• /
• pp.1093-1101
• /
• 2009

Quantile regression has become a more widely used technique to describe the distribution of a response variable given a set of explanatory variables. This paper proposes a novel modelfor quantile regression using doubly penalized kernel machine with support vector machine iteratively reweighted least squares (SVM-IRWLS). To make inference about the shape of a population distribution, the widely popularregression, would be inadequate, if the distribution is not approximately Gaussian. We present a likelihood-based approach to the estimation of the regression quantiles that uses the asymmetric Laplace density.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.42 no.1
• /
• pp.19-28
• /
• 2017

Moments of stationary intervals and those of the counting process can be used for moment fittings of the point processes. As for the Markovian arrival processes, the moments of stationary intervals are given as a polynomial function of parameters whereas the moments of the counting process involve exponential terms. Therefore, moment fittings are more complicated with the counting process than with stationary intervals. However, in queueing network analysis, cross-correlation between point processes can be modeled more conveniently with counting processes than with stationary intervals. A Laplace-Stieltjies transform of the stationary intervals of MAP (3)s is recently proposed in minimal number of parameters. We extend the results and present the Laplace transform of the counting process of MAP (3)s. We also show how moments of the counting process such as index of dispersions for counts, IDC, and limiting IDC can be used for moment fittings. Examples of exact MAP (3) moment fittings are also presented on the basis of moments of stationary intervals and those of the counting process.

• Structural Engineering and Mechanics
• /
• v.63 no.1
• /
• pp.89-102
• /
• 2017

In this work, we present a theoretical framework to study the thermovisco-elastic responses of homogeneous, isotropic and perfectly conducting medium subjected to inclined load. Based on recently developed generalized thermoelasticity theory with fractional order strain, the two-dimensional governing equations are obtained in the context of generalized magnetothermo-viscoelasticity theory without energy dissipation. The Kelvin-Voigt model of linear viscoelasticity is employed to describe the viscoelastic nature of the material. The resulting formulation of the field equations is solved analytically in the Laplace and Fourier transform domain. On the application of inclined load at the surface of half-space, the analytical expressions for the normal displacement, strain, temperature, normal stress and tangential stress are derived in the joint-transformed domain. To restore the fields in physical domain, an appropriate numerical algorithm is used for the inversion of the Laplace and Fourier transforms. Finally, we have demonstrated the effect of magnetic field, viscosity, mechanical relaxation time, fractional order parameter and time on the physical fields in graphical form for copper material. Some special cases have also been deduced from the present investigation.

• Bulletin of the Korean Mathematical Society
• /
• v.51 no.1
• /
• pp.55-66
• /
• 2014

In this paper, the authors establish the conditions for the extinction of solutions, in finite time, of the fast diffusive p-Laplace equation $u_t=div({\mid}{\nabla}u{\mid}^{p-2}{\nabla}u)+a{\int}_{\Omega}u^q(y,t)dy$, 1 < p < 2, in a bounded domain ${\Omega}{\subset}R^N$ with $N{\geq}1$. More precisely, it is shown that if q > p-1, any solution vanishes in finite time when the initial datum or the coefficient a or the Lebesgue measure of the domain is small, and if 0 < q < p-1, there exists a solution which is positive in ${\Omega}$ for all t > 0. For the critical case q = p-1, whether the solutions vanish in finite time or not depends crucially on the value of $a{\mu}$, where ${\mu}{\int}_{\Omega}{\phi}^{p-1}(x)dx$ and ${\phi}$ is the unique positive solution of the elliptic problem -div(${\mid}{\nabla}{\phi}{\mid}^{p-2}{\nabla}{\phi}$) = 1, $x{\in}{\Omega}$; ${\phi}(x)$=0, $x{\in}{\partial}{\Omega}$. This is a main difference between equations with local and nonlocal sources.

• Computational Structural Engineering
• /
• v.8 no.4
• /
• pp.129-136
• /
• 1995

This paper presents a boundary element method for obtaining approximate solutions of 2-dimensional consolidation problems based on the Biot's linear theory. Laplace transform is applied to differential equation system in order to eliminate the time dependency. The boundary integral equations in transformed space are formulated and the fundamental solutions are shown in a closed form. In order to convert the transformed solutions to the ones in real space, the Hosono's numerical Laplace transform inversion method is applied. As a numerical example, a half-space consolidation problem subjected to a strip local load is selected and the applicability of the method is demonstrated through the comparison with the exact solutions.

• Proceedings of the Korean Geotechical Society Conference
• /
• 2010.03a
• /
• pp.1425-1432
• /
• 2010

In large construction site, although soil conversion factor is so significant to preliminary design, operation design and calculating the cost of construction that it is important to take reasonable estimation and application, the standard of soil conversion factor for weathered ground doesn't clearly suggested yet. So in this study, at first we obtain the image using DSLR - high resolution camera and Laser scanner in the Haeng-Bok city constructin site, then analysis the ratio of soil and rock using various image processing method(Sobel method, Laplace method, Highpass filter, Hue and Saturation analysis). Mutual comparation with the result of image processing analysis and manual segmentation of 5case image in the cad. As a result, best image processing method was different for each case. In case of high propotion of rock, Laplace was best and in case of high propotion of soil, Highpass was best, and mixed case Laplace was best.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.12
• /
• pp.12-19
• /
• 2014

In this paper, an advanced UWB (ultra wideband) Rake receiving technique based on the statistical distribution model is studied in the M-ary TH-PPM system with multiple access interference (MAI). In order to improve the performance of the Rake receiver, the stochastic model, which can flexibly express the behavior of MAI-plus-noise, is required and the Laplace distribution and the generalized normal Laplace (GNL) model applied by the curtosis matching method are considered. The performance of Rake receiver based on each probability distribution is evaluated in the IEEE multipath fading channel and compared to that of the conventional Rake receiver. The suggested approach shows a superior BER performance than that of conventional Rake receiver.

• Journal of the Korean Society for Railway
• /
• v.14 no.6
• /
• pp.495-500
• /
• 2011

In evaluating the ride comfort of railway vehicles, relationship between passenger's feeling and vibration characteristics is very important because human feeling is dependent on frequency spectrum of vibration. Therefore, the weighing curves in frequency domain are used to evaluate the ride comfort of railway vehicles. These curves have been defined in the Laplace transfer functions. It is necessary to convert the Laplace weighing function to the z weighing function in order to obtain the rms value in the time domain. In the present paper, we have applied Tustin's approximation to transform the Laplace weighing function to the z weighing and validated this method by reviewing the various cases.

• IEIE Transactions on Smart Processing and Computing
• /
• v.4 no.4
• /
• pp.202-208
• /
• 2015

In this study, we propose a new inference algorithm for a multiclass Gaussian process classification model using a variational EM framework and the Laplace approximation (LA) technique. This is performed in two steps, called expectation and maximization. First, in the expectation step (E-step), using Bayes' theorem and the LA technique, we derive the approximate posterior distribution of the latent function, indicating the possibility that each observation belongs to a certain class in the Gaussian process classification model. In the maximization step, we compute the maximum likelihood estimators for hyper-parameters of a covariance matrix necessary to define the prior distribution of the latent function by using the posterior distribution derived in the E-step. These steps iteratively repeat until a convergence condition is satisfied. Moreover, we conducted the experiments by using synthetic data and Iris data in order to verify the performance of the proposed algorithm. Experimental results reveal that the proposed algorithm shows good performance on these datasets.