• Structural Engineering and Mechanics
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• v.33 no.4
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• pp.447-484
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• 2009

The spatially coupled buckling, in-plane, and lateral bucking analyses of thin-walled Timoshenko curved beam with non-symmetric, double-, and mono-symmetric cross-sections resting on elastic foundation are performed based on series solutions. The stiffness matrices are derived rigorously using the homogeneous form of the simultaneous ordinary differential equations. The present beam formulation includes the mechanical characteristics such as the non-symmetric cross-section, the thickness-curvature effect, the shear effects due to bending and restrained warping, the second-order terms of semitangential rotation, the Wagner effect, and the foundation effects. The equilibrium equations and force-deformation relationships are derived from the energy principle and expressions for displacement parameters are derived based on power series expansions of displacement components. Finally the element stiffness matrix is determined using force-deformation relationships. In order to verify the accuracy and validity of this study, the numerical solutions by the proposed method are presented and compared with the finite element solutions using the classical isoparametric curved beam elements and other researchers' analytical solutions.

• Journal of applied mathematics & informatics
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• v.25 no.1_2
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• pp.435-443
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• 2007

Computing the interior spectrum of large sparse generalized eigenvalue problems $Ax\;=\;{\lambda}Bx$, where A and b are large sparse and SPD(Symmetric Positive Definite), is often required in areas such as structural mechanics and quantum chemistry, to name a few. Recently, CG-type methods have been found useful and hence, very amenable to parallel computation for very large problems. Also, as in the case of linear systems proper choice of preconditioning is known to accelerate the rate of convergence. After the smallest eigenpair is found we use the orthogonal deflation technique to find the next m-1 eigenvalues, which is also suitable for parallelization. This offers advantages over Jacobi-Davidson methods with partial shifts, which requires re-computation of preconditioner matrx with new shifts. We consider as preconditioners Incomplete LU(ILU)(0) in two variants, ever-relaxation(SOR), and Point-symmetric SOR(SSOR). We set m to be 5. We conducted our experiments on matrices from discretizations of partial differential equations by finite difference method. The generated matrices has dimensions up to 4 million and total number of processors are 32. MPI(Message Passing Interface) library was used for interprocessor communications. Our results show that in general the Multi-Color ILU(0) gives the best performance.

• Kyungpook Mathematical Journal
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• v.62 no.1
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• pp.1-28
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• 2022

In this paper, we define the G-Brauer algebras $D^G_f(x)$, where G is a cyclic group, called cyclic G-Brauer algebras, as the linear span of r-signed 1-factors and the generalized m, k signed partial 1-factors is to analyse the multiplication of basis elements in the quotient $^{\rightarrow}_{I_f}^G(x,2k)$. Also, we define certain symmetric matrices $^{\rightarrow}_T_{m,k}^{[\lambda]}(x)$ whose entries are indexed by generalized m, k signed partial 1-factor. We analyse the irreducible representations of $D^G_f(x)$ by determining the quotient $^{\rightarrow}_{I_f}^G(x,2k)$ of $D^G_f(x)$ by its radical. We also find the eigenvalues and eigenspaces of $^{\rightarrow}_T_{m,k}^{[\lambda]}(x)$ for some values of m and k using the representation theory of the generalised symmetric group. The matrices $T_{m,k}^{[\lambda]}(x)$ whose entries are indexed by generalised m, k signed partial 1-factors, which helps in determining the non semisimplicity of these cyclic G-Brauer algebras $D^G_f(x)$, where G = ℤ_r.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.4
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• pp.26-30
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• 2003

The Lanczos algorithm is the most commonly used in approximating a small number of extreme eigenvalues for symmetric large sparse matrices. Global communications in MP(Message Passing) parallel computer decrease the computation speed. In this paper, we introduce the s-step Lanczos method, and s-step method generates reduction matrices which are similar to reduction matrices generated by the standard Lanczos method. One iteration of the s-step Lanczos algorithm corresponds to s iterations of the standard Lanczos algorithm. The s-step method has the minimized global communication and has the superior parallel properties to the standard method. These algorithms are implemented on Cray T3E and performance results are presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.4
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• pp.769-774
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• 2006

This paper proposed a theoretic numerical modelling in control system design to analyze active suspension equipment by adopting minimum phase system theory. Recent in the field of suspension system design it is general to adopt active control scheme for stiffness and damping, and connection with other vehicle stability control equipment is also intricate, it is required for control system scheme to design more robust, higher response and precision control equipment. Transfer matrices of system with collocated sensors and actuators are symmetric. The symmetry is independent of the entities of mass, damping, or stiffness matrices, and is a non parametric nature. From this point of view, symmetric robust control system is analyzed and designed in this paper. Numerical example is shown for validity of robust control system design.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5C
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• pp.461-467
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• 2003

We propose an efficient method for separable symmetric linear filtering in the DCT domain. First, separable 2-D linear filtering is decomposed into the cascade of 1-D filtering in the DCT domain. We investigate special characteristics of DCT domain filtering matrices when the filter coefficients are symmetric. Then we present the DCT domain 2-D filtering method using these characteristics. The proposed method requires smaller number of multiplications including typical sparseness of DCT coefficients compared to previous DCT domain linear filtering methods. Also, the proposed method is composed of simple and regular operations, which would be appropriate for efficient VLSI implementation.

• Earthquakes and Structures
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• v.10 no.1
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• pp.25-51
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• 2016

In this study, graph product rules are applied to the dynamic analysis of regular skeletal structures. Graph product rules have recently been utilized in structural mechanics as a powerful tool for eigensolution of symmetric and regular skeletal structures. A structure is called regular if its model is a graph product. In the first part of this paper, the formulation of time history dynamic analysis of regular structures under seismic excitation is derived using graph product rules. This formulation can generally be utilized for efficient linear elastic dynamic analysis using vibration modes. The second part comprises of random vibration analysis of regular skeletal structures via canonical forms and closed-form eigensolution of matrices containing special patterns for symmetric structures. In this part, the formulations are developed for dynamic analysis of structures subjected to random seismic excitation in frequency domain. In all the proposed methods, eigensolution of the problems is achieved with less computational effort due to incorporating graph product rules and canonical forms for symmetric and cyclically symmetric structures.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.1
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• pp.1-12
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• 1993

Tangent stiffness matrices are derived for the torsional and lateral stability analysis of the space beams and framed structures with the symmetric thin-walled section by using the principle of virtual displacement. In the cases of restrained torsion and unrestrained torsion, the elastic and geometric stiffness matrices are evaluated by using the Hermitian polynomials which represent the displacement field of the beam element in simple flexure. Numerical examples illustrate the accuracy and convergence characteristics of the derived formulations.

• Korean Management Science Review
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• v.11 no.3
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• pp.1-11
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• 1994

Recent advances in linear programming solution methodology have focused on interior point methods. This powerful new class of methods achieves significant reductions in computer time for large linear programs and solves problems significantly larger than previously possible. These methods can be examined from points of Fiacco and McCormick's barrier method, Lagrangian duality, Newton's method, and others. This study presents a primal-dual log barrier algorithm of interior point methods for linear programming. The primal-dual log barrier method is currently the most efficient and successful variant of interior point methods. This paper also addresses a Cholesky factorization method of symmetric positive definite matrices arising in interior point methods. A special structure of the matrices, called supernode, is exploited to use computational techniques such as direct addressing and loop-unrolling. Two dense matrix handling techniques are also presented to handle dense columns of the original matrix A. The two techniques may minimize storage requirement for factor matrix L and a smaller number of arithmetic operations in the matrix L computation.

• Journal of applied mathematics & informatics
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• v.28 no.1_2
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• pp.515-521
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• 2010

In multivariate analysis, the inversion formula of the Stieltjes transform is used to find the density of a spectral distribution of random matrices of sample covariance type. Let $B_n\;=\;\frac{1}{N}Y_nY_n^TT_n$ where $Y_n\;=\;[Y_{ij}]_{n\;{\times}\;N}$ is with independent, identically distributed entries and $T_n$ is an $n\;{\times}\;n$ symmetric non-negative definite random matrix independent of the $Y_{ij}$'s. In the present paper, using the inversion formula of the Stieltjes transform, we will find that the limiting distribution of $B_n$ has a continuous density function away from zero.