• 한국경영과학회지
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• 제21권3호
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• pp.63-74
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• 1996

Ordering plays an important role in solving an LP problem with sparse matrix by the interior point method. Since ordering is NP-complete, we try to find an efficient method. The objective of this paper is to present an efficient heuristic ordering method for implementation of the minimum deficiency method. Both the ordering method and the data structure play important roles in implementation. First we define a new heuristic pseudo-deficiency ordering method and a data structure for the method-quotient graph and cliqued storage. Next we show an experimental result in terms of time and nonzero numbers by NETLIB problems.

• 한국경영과학회지
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• 제11권1호
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• pp.51-58
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• 1986

The propose of this study is to presnet a generalized linear/goal programming software, which has been developed to run on mickrocomputers with at least 512 K bytes of memory. The main characteristics of our algorithm for solving LP/GP problems are outlined as follows ; First, it uses the revised simplex algorithm, which is the most efficient computational procedure for computers. Second, it employs the sparse matrix technique to overcome the limited memory of microcomputers. Last, it uses the modified product form of invers (MPFI) to reduce round-off errors. The test runs with our code written in FORTRAN show that it can be used as an effective tool for solving linear/goal programming problems of considerable size.

• 대한전기학회논문지:전력기술부문A
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• 제48권10호
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• pp.1239-1246
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• 1999

This paper presents a new algorithm to construct the modular network model for SSR analysis by simply applying KCL to each node and KVL to all branches connected to the node sequentially. This method has advantages that the model can be derived directly from the system data for transient stability study and turbine/generator shaft model, the resulted model in the form of augmented state matrix is very sparse, and thus efficient SSR study of a large scale system becomes possible. The proposed algorithm is verified with the IEEE First and Second Benchmark models.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2008년도 학술대회
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• pp.71-78
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• 2008

For analyses of multi-phase flows in a water-cooled nuclear power plant, a three-dimensional SIMPLE-algorithm based hydrodynamic solver CUPID-S has been developed. As governing equations, it adopts a two-fluid three-field model for the two-phase flows. The three fields represent a continuous liquid, a dispersed droplets, and a vapour field. The governing equations are discretized by a finite volume method on an unstructured grid to handle the geometrical complexity of the nuclear reactors. The phasic momentum equations are coupled and solved with a sparse block Gauss-Seidel matrix solver to increase a numerical stability. The pressure correction equation derived by summing the phasic volume fraction equations is applied on the unstructured mesh in the context of a cell-centered co-located scheme. This paper presents the numerical method and the preliminary results of the calculations.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2008년 추계학술대회논문집
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• pp.71-78
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• 2008

For analyses of multi-phase flows in a water-cooled nuclear power plant, a three-dimensional SIMPLE-algorithm based hydrodynamic solver CUPID-S has been developed. As governing equations, it adopts a two-fluid three-field model for the two-phase flows. The three fields represent a continuous liquid, a dispersed droplets, and a vapour field. The governing equations are discretized by a finite volume method on an unstructured grid to handle the geometrical complexity of the nuclear reactors. The phasic momentum equations are coupled and solved with a sparse block Gauss-Seidel matrix solver to increase a numerical stability. The pressure correction equation derived by summing the phasic volume fraction equations is applied on the unstructured mesh in the context of a cell-centered co-located scheme. This paper presents the numerical method and the preliminary results of the calculations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권6호
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• pp.2497-2517
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• 2020

For compressed sensing (CS) applications, it is significant to construct deterministic measurement matrices with good practical features, including good sensing performance, low memory cost, low computational complexity and easy hardware implementation. In this paper, a deterministic construction method of bipolar measurement matrices is presented based on binary sequence family (BSF). This method is of interest to be applied for sparse signal restore and image block CS. Coherence is an important tool to describe and compare the performance of various sensing matrices. Lower coherence implies higher reconstruction accuracy. The coherence of proposed measurement matrices is analyzed and derived to be smaller than the corresponding Gaussian and Bernoulli random matrices. Simulation experiments show that the proposed matrices outperform the corresponding Gaussian, Bernoulli, binary and chaotic bipolar matrices in reconstruction accuracy. Meanwhile, the proposed matrices can reduce the reconstruction time compared with their Gaussian counterpart. Moreover, the proposed matrices are very efficient for sensing performance, memory, complexity and hardware realization, which is beneficial to practical CS.

• 한국지구물리탐사학회:학술대회논문집
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• 한국지구물리탐사학회 2003년도 Proceedings of the international symposium on the fusion technology
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• pp.402-409
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• 2003

Inversion of traveltime requires an efficient algorithm for computing the traveltime as well as its $Frech\hat{e}t$ derivative. We compute the traveltime of the head waves using the damped wave solution in the Laplace domain and then present a new algorithm for calculating the $Frech\hat{e}t$ derivative of the head wave traveltimes by exploiting the numerical structure of the finite element method, the modem sparse matrix technology, and SWEET algorithm developed recently. Then, we use a properly regularized steepest descent method to invert the traveltime of the Marmousi-2 model. Through our numerical tests, we will demonstrate that the refraction tomography with large aperture data can be used to construct the initial velocity model for the prestack depth migration.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 C
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• pp.1753-1755
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• 1996

This paper presents an analysis of the 3D microwave oven considering its forming. The results were compared with experimental data. Finite Element Method(FEM) using edge clement is employed for the analysis. For solving the large sparse system matrix equation was solved using the parallelized QMR method. Analysis of the 3d cavity has troublesome difficulties such as spurious solutions, too many memory and long computation time. We overcome this difficulties by using edge clement for spurious solutions and the parallelized QMR method by the aid of Paralle Virtual Machine(PVM) for the memory and computation time.

• Journal of Communications and Networks
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• 제9권1호
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• pp.75-83
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• 2007

Orthogonal frequency division multiplexing (OFDM) systems with multiple transmit antennas can exploit space-time block coding on each subchannel for reliable data transmission. Spacetime coded OFDM systems, however, are very sensitive to time variant channels because the channels need to be static over multiple OFDM symbol periods. In this paper, we propose to mitigate the channel variations in the frequency domain using a linear filter in the frequency domain that exploits the sparse structure of the system matrix in the frequency domain. Our approach has reduced complexity compared with alternative approaches based on time domain block-linear filters. Simulation results demonstrate that our proposed frequency domain block-linear filter reduces computational complexity by more than a factor of ten at the cost of small performance degradation, compared with a time domain block-linear filter.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1990년도 가을 학술발표회 논문집
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• pp.34-39
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• 1990

For the analysis of structures, specifically if it is large-scale, in which case it can not be solved within the core memory, the majority of computation time is consumed In the solution of simultaneous linear equation. In this study an efficient in- and out-of-core column solver for sparse symmetric matrix utilizing memory moving scheme is developed. Compare with existing blocking methods the algorithm is simple, therefore the coding and computational efficiencies are greatly enhanced. Upon available memory size, the solver automatically performs solution within the core or outside core. Analysis example shows that the proposed method efficiently solve the large structural problem on the small-memory microcomputer.