In this paper, we introduce and discuss an algorithm for the numerical solution of two- dimensional fractional dispersion equation. The algorithm for the numerical solution of this equation is based on explicit finite difference approximation. Consistency, conditional stability, and convergence of this numerical method are described. Finally, numerical example is presented to show the dispersion behavior according to the order of the fractional derivative and we demonstrate that our explicit finite difference approximation is a computationally efficient method for solving two-dimensional fractional dispersion equation
Buried pipeline systems are commonly used to transport water, sewage, natural oil/gas and other materials. The beneficial of using geogrid reinforcement is to increase the bearing capacity of the soil and decrease the load transfer to the underground structures.
This paper deals with simulation of the buried pipe problem numerically by finite elements method using the newest version of PLAXIS-3D software. Rajkumar and Ilamaruthi's study, 2008 has been selected to be reanalyzed as 3D problem because it is containing all the properties needed by the program such as the modulus of elasticity, Poisson's ratio, angle of internal friction. It was found that the results
... Show MoreIn the lifetime process in some systems, most data cannot belong to one single population. In fact, it can represent several subpopulations. In such a case, the known distribution cannot be used to model data. Instead, a mixture of distribution is used to modulate the data and classify them into several subgroups. The mixture of Rayleigh distribution is best to be used with the lifetime process. This paper aims to infer model parameters by the expectation-maximization (EM) algorithm through the maximum likelihood function. The technique is applied to simulated data by following several scenarios. The accuracy of estimation has been examined by the average mean square error (AMSE) and the average classification success rate (ACSR). T
... Show MoreThe purpose of the paper is to tind the degree of the approximation of a functions f be bounded , measurable and defined
in interval [a,h]by Bernstein polynomial in LP space 1 $ p < oo by
using Ditzian-Totik modulus of smootlmess and k 1n average modvlus of smoothness.
Our aim of this research is to find the results of numerical solution of Volterra linear integral equation of the second kind using numerical methods such that Trapezoidal and Simpson's rule. That is to derive some statistical properties expected value, the variance and the correlation coefficient between the numerical and exact solutionâ–¡
In this paper, Min-Max composition fuzzy relation equation are studied. This study is a generalization of the works of Ohsato and Sekigushi. The conditions for the existence of solutions are studied, then the resolution of equations is discussed.
A computer theoretical s1udy has been carried out in field of opto - clcctroniccs, to design an electron gun using the space charge effect.
The distribution of axial potential upon the two -electrode
immersion lens of (L=l4mm) has been carried out using Poisons equation and the tinite clement method; knowing the first 11nd second derivation of the axial potential and the solution of paraxial ray equation, the optical prop
... Show MoreIn this paper, a new technique is offered for solving three types of linear integral equations of the 2nd kind including Volterra-Fredholm integral equations (LVFIE) (as a general case), Volterra integral equations (LVIE) and Fredholm integral equations (LFIE) (as special cases). The new technique depends on approximating the solution to a polynomial of degree and therefore reducing the problem to a linear programming problem(LPP), which will be solved to find the approximate solution of LVFIE. Moreover, quadrature methods including trapezoidal rule (TR), Simpson 1/3 rule (SR), Boole rule (BR), and Romberg integration formula (RI) are used to approximate the integrals that exist in LVFIE. Also, a comparison between those methods i
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