• 한국전산유체공학회:학술대회논문집
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• 1998.11a
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• pp.147-152
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• 1998

2-D flow fields are studied by using a shared memory parallel computer with a parallel flow analysis program which uses domain decomposition method and MPI library for data exchange at overlapped interface. Especially, effects of directional domain decomposition on parallel efficiency are studied for 2-D Lid-Driven cavity flow and flow through square cavity. It is known from the present study that domain decomposition along the main flow direction gives better parallel efficiency in 1-D partitioning than along the other direction. 2-D partitioning, however, is less sensitive to flow directions and gives good parallel efficiency for most of the cases considered.

• Journal of computational fluids engineering
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• v.21 no.1
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• pp.36-42
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• 2016

One of the obstacles on the grid generation for complex geometries with multi-block structured grids is the domain decomposition. In this paper, the domain decomposition for two-dimensional flow is studied using the flow characteristics. The potential flow equation with the source distribution on the panel surface is solved to extract the information of the flow. The current approach is applied to a two-dimensional cylinder and Bi-NACA0012 problems. The generated grids are applied to generic flow solvers and reasonable results are obtained. It can be concluded that the current methods is useful in the domain decomposition for the multi-block structured grid.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.18 no.1
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• pp.17-26
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• 2014

This paper presents development of an improved domain decomposition method for large scale structural problem that aims to provide high computational efficiency. In the previous researches, we developed the domain decomposition algorithm based on augmented Lagrangian formulation and proved numerical efficiency under both serial and parallel computing environment. In this paper, new computational analysis by the proposed domain decomposition method is performed. For this purpose, reduction in computational time achieved by the proposed algorithm is compared with that obtained by the dual-primal FETI method under serial computing condition. It is found that the proposed methods significantly accelerate the computational speed for a linear structural problem.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1998.03a
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• pp.246-249
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• 1998

In the present study, domain decomposition using the substructuring method is developed for the computational efficiency of the finite element analysis of metal forming processes. In order to avoid calculation of an inverse matrix during the substructuring procedure, the modified Cholesky decomposition method is implemented. As obtaining the data independence by the substructuring method, the program is easily parallelized using the Parallel Virtual Machine(PVM) library on a workstation cluster connected on networks. A numerical example for a simple upsetting is calculated and the speed-up ratio with respect to various domain decompositions and number of processors. Comparing the results, it is concluded that the improvement of performance is obtained through the proposed method.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.1
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• pp.115-123
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• 1997

In this paper we present a polynomial matrix decomposition algorithm that determines a polynomial matix M(z) which satisfies the relation V(z)=M(z) for a given polynomial matrix V(z) which is paraconjugate hermitian matrix with normal rank r and is positive semidenfinite on the unit circle of z-plane. All the decomposition procedures in this proposed method are performed in the digitral domain. We also discuss how to apply the polynomial matirx decomposition in realizing MIMO LBR two-pairs.

• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.37-53
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• 2009

In this paper the problem of calculating the probability that the responses of a wind-excited structure exceed specified thresholds within a given time interval is considered. The failure domain of the problem can be expressed as a union of elementary failure domains whose boundaries are of quadratic form. The Domain Decomposition Method (DDM) is employed, after being appropriately extended, to solve this problem. The probability estimate of the overall failure domain is given by the sum of the probabilities of the elementary failure domains multiplied by a reduction factor accounting for the overlapping degree of the different elementary failure domains. The DDM is extended with the help of Line Sampling (LS), from its original presentation where the boundary of the elementary failure domains are of linear form, to the current case involving quadratic elementary failure domains. An example involving an along-wind excited steel building shows the accuracy and efficiency of the proposed methodology as compared with that obtained using standard Monte Carlo simulations (MCS).

• International Journal of Aeronautical and Space Sciences
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• v.16 no.2
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• pp.177-189
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• 2015

This paper presents an all-direct domain decomposition approach for large-scale structural analysis. The proposed approach achieves computational robustness and efficiency by enforcing the compatibility of the displacement field across the sub-domain boundaries via local Lagrange multipliers and augmented Lagrangian formulation (ALF). The proposed domain decomposition approach was compared to the existing FETI approach in terms of the computational time and memory usage. The parallel implementation of the proposed algorithm was described in detail. Finally, a preliminary validation was attempted for the proposed approach, and the numerical results of two- and three-dimensional problems were compared to those obtained through a dual-primal FETI approach. The results indicate an improvement in the performance as a result of the implementing the proposed approach.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.11 s.188
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• pp.93-102
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• 2006

In this study an advanced domain decomposition method is suggested in order to construct surface models from very large amount of points. In this method the spatial domain of interest that is occupied by the input set of points is divided in repetitive manner. First, the space is divided into smaller domains where the problem can be solved independently. Then each subdomain is again divided into much smaller domains where the problem can be solved locally. These local solutions of subdivided domains are blended together to obtain a solution of each subdomain using partition of unity function. Then the solutions of subdomains are merged together in order to construct whole surface model. The suggested methods are conceptually very simple and easy to implement. Since RDDM(Repetitive Domain Decomposition Method) is effective in the computation time and memory consumption, the present study is capable of providing a fast and accurate reconstructions of complex shapes from large amount of point data containing millions of points. The effectiveness and validity of the suggested methods are demonstrated by performing numerical experiments for the various types of point data.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.18 no.4
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• pp.305-316
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• 2014

The Hodge-Helmholtz decomposition splits a vector field into the unique sum of a divergence-free vector field (solenoidal part) and a gradient field (irrotational part). In a bounded domain, a boundary condition needs to be supplied to the decomposition. The decomposition with the non-penetration boundary condition is equivalent to solving the Poisson equation with the Neumann boundary condition. The Gibou-Min method is an application of the Poisson solver by Purvis and Burkhalter to the decomposition. Using the $L^2$-orthogonality between the error vector and the consistency, the convergence for approximating the divergence-free vector field was recently proved to be $O(h^{1.5})$ with step size h. In this work, we analyze the convergence of the irrotattional in the decomposition. To the end, we introduce a discrete version of the Poincare inequality, which leads to a proof of the O(h) convergence for the scalar variable of the gradient field in a domain with general intersection property.

• Transactions of Materials Processing
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• v.7 no.5
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• pp.474-480
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• 1998

In the present study a domain decomposition scheme using the substructuring method is developed for the computational efficiency of the finite element analysis of metal forming processes. in order to avoid calculation of an inverse matrix during the substructuring procedure, the modified Cholesky decomposition method is implemented. As obtaining the data independence by the substructuring method the program is easily paralleized using the Parallel Virtual machine(PVM) library on a work-station cluster connected on networks. A numerical example for a simple upsetting is calculated and the speed-up ratio with respect to various number of subdomains and number of processors. The efficiency of the parallel computation is discussed by comparing the results.