• The Pure and Applied Mathematics
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• v.13 no.1 s.31
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• pp.19-38
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• 2006

We analyze the spectral collocation approximation for a parabolic partial integrodifferential equations(PIDE) with a weakly singular kernel. The space discretization is based on the spectral collocation method and the time discretization is based on Crank-Nicolson scheme with a graded mesh. We obtain the stability and second order convergence result for fully discrete scheme.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.19 no.1 s.71
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• pp.39-46
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• 2006

This paper analyzes the continuous Galerkin method for the space-time discretization of wave equation. The method of space-time finite elements enables the simple solution than the usual finite element analysis with discretization in space only. We present a discretization technique in which finite element approximations are used in time and space simultaneously for a relatively large time period called a time slab. The weighted residual process is used to formulate a finite element method for a space-time domain. Instability is caused by a too large time step in successive time steps. A stability problem is described and some investigations for chosen types of rectangular space-time finite elements are carried out. Some numerical examples prove the efficiency of the described method under determined limitations.

• Structural Engineering and Mechanics
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• v.3 no.4
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• pp.391-410
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• 1995

The application of adaptive finite element method to dynamic problems is investigated. Both the kinetic and strain energy errors induced by space and time discretization were estimated in a consistent manner and controlled by the simultaneous use of the adaptive mesh generation and the automatic time stepping. Also an optimal ratio of spatial discretization error to temporal discretization error was discussed. In this study it was found that the best performance can be obtained when the specified spatial and temporal discretization errors have the same value. Numerical examples are carried out to verify the performance of the procedure.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.2
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• pp.122-132
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• 2013

In this research the development of unstructured grid discretization solution techniques is presented. The purpose is to describe such a conservative discretization scheme applied for experimental validation work. The objective of this paper is to better establish the effects of mesh generation techniques on velocity fields and particle deposition patterns to determine the optimal aerodynamic characteristics. In order to achieve the objective, the mesh surface discretization approaches used the VLA prototype manufacturing tolerance zone of the outer surface. There were 3 schemes for this discretization study implementation. They are solver validation, grid convergence study and surface tolerance study. A solver validation work was implemented for the simple 2D and 3D model to get the optimum solver for the VLA model. A grid convergence study was also conducted with a different growth factor and cell spacing, the amount of mesh can be controlled. With several amount of mesh we can get the converged amount of mesh compared to experimental data. The density around surface model can be calculated by controlling the number of element in every important and sensitive surface area of the model. The solver validation work result provided the optimum solver to employ in the VLA model analysis calculation. The convergence study approach result indicated that the aerodynamic trend characteristic was captured smooth enough compared with the experimental data. During the surface tolerance scheme, it could catch the aerodynamics data of the experiment data. The discretization studies made the validation work more efficient way to achieve the purpose of this paper.

• The Pure and Applied Mathematics
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• v.14 no.4
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• pp.283-287
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• 2007

An extension of the contraction mapping theorem is provided in a Banach space setting to approximate fixed points of operator equations. Our approach is justified by numerical examples where our results apply whereas the classical contraction mapping principle cannot.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.9
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• pp.56-65
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• 2005

A dynamic analysis method that freezes a time domain by discretization and solves the spatial propagation equation has a unique feature that provides a degree of freedom on spatial domain compared with the space discretization or space-time discretization finite element method. Using this feature, the time finite element analysis can be effectively applied to optimize the spatial characteristics of distributed type actuators. In this research, the time domain finite element method was used to discretize the model. A state variable vector was used in the discretization to include arbitrary initial conditions. A performance index was proposed on spatial domain to consider both potential and vibrational energy, so that the resulting shape of the distributed actuator was optimized for dynamic control of the structure. It is assumed that the structure satisfies the final rest condition using the realizable control scheme although the initial disturbance can affect the system response. Both equations on states and costates were derived based on the selected performance index and structural model. Ricatti matrix differential equations on state and costate variables were derived by the reconfiguration of the sub-matrices and application of time/space boundary conditions, and finally optimal actuator distribution was obtained. Numerical simulation results validated the proposed actuator shape optimization scheme.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.4
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• pp.816-826
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• 2017

In this paper, a generalized discretization scheme is proposed that can derive general-order finite difference equations representing the joint probability density function of dynamic response of stochastic systems. The various order of finite difference equations are applied to solutions of the Fokker-Planck-Kolmogorov (FPK) equation. The finite difference equations derived by the proposed method can greatly increase accuracy even at the tail parts of the probability density function, giving accurate reliability estimations. Compared with exact solutions and finite element solutions, the generalized finite difference method showed increasing accuracy as the order increases. With the proposed method, it is allowed to use different orders and types (i.e. forward, central or backward) of discretization in the finite difference method to solve FPK and other partial differential equations in various engineering fields having requirements of accuracy or specific boundary conditions.

• Journal of the Korean Society of Safety
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• v.21 no.2 s.74
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• pp.143-149
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• 2006

This paper deals with the space-time finite element analysis of two-dimensional vibration problem with a single variable. The method of space-time finite elements enables the simpler solution than the usual finite element analysis with discretization in space only. We present a discretization technique in which finite element approximations are used in time and space simultaneously for a relatively large time period. The weighted residual process is used to formulate a finite element method for a space-time domain. A stability problem is described and some investigations for chosen type of rectangular space-time finite elements are carried out. Instability is caused by a too large time step of successive time steps in the traditional time-dependent problems. It has been shown that the numerical stability of time-stepping on the larger time steps is quite good. The unstructured space-time finite element not only overcomes the shortcomings of the stability in the traditional numerical methods, but it is also endowed with the features of an effective computational technique. Some numerical examples have been presented to illustrate the efficiency of the described method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3180-3199
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• 2013

While non-predefined object segmentation (NDOS) distinguishes an arbitrary self-assumed object from its background, predefined object segmentation (DOS) pre-specifies the target object. In this paper, a new and novel method to segment predefined objects is presented, by globally optimizing an orientation-based objective function that measures the fitness of the object boundary, in a discretized parameter space. A specific object is explicitly described by normalized discrete sets of boundary points and corresponding normal vectors with respect to its plane shape. The orientation factor provides robust distinctness for target objects. By considering the order of transformation elements, and their dependency on the derived over-segmentation outcome, the domain of translations and scales is efficiently discretized. A branch and bound algorithm is used to determine the transformation parameters of a shape model corresponding to a target object in an image. The results tested on the PASCAL dataset show a considerable achievement in solving complex backgrounds and unclear boundary images.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.4
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• pp.391-396
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• 2003

This paper proposes a new approach that converts continuous-valued attributes to categorical-valued ones considering the distribution of target attributes(classes). In this approach, It can be possible to get optimal interval boundaries by considering the distribution of data itself without any requirements of parameters. For each attributes, the distribution of target attributes is projected to one-dimensional space. And this space is clustered according to the criteria like as the density value of each target attributes and the amount of overlapped areas among each density values of target attributes. Clusters which are made in this ways are based on the probabilities that can predict a target attribute of instances. Therefore it has an interval boundaries that minimize a loss of information of original data. An improved performance of proposed discretization method can be validated using C4.5 algorithm and UCI Machine Learning Data Repository data sets.