• Title, Summary, Keyword: Krylov Subspace

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Combination of Preconditioned Krylov Subspace Methods and Multi-grid Method for Convergence Acceleration of the incompressible Navier-Stokes Equations (비압축성 Navier-Stokes 방정식의 수렴 가속을 위한 예조건화 Krylov 부공간법과 다중 격자법의 결합)

  • Maeng Joo Sung;Choi IL Kon;Lim Youn Woo
    • 한국전산유체공학회:학술대회논문집
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    • pp.106-112
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    • 1999
  • In this article, combination of the FAS-FMG multi-grid method and the Krylov subspace method was presented in solving two dimensional driven-cavity flows. Three algorithms of the Krylov subspace method, CG, CGSTAB(Bi-CG Stabilized) and GMRES method were tested with MILU preconditioner. As a smoother of the pressure correction equation, the MILU-CG is recommended rather than MILU-GMRES(k) or MILU-CGSTAB, since the MILU-GMRES(k) preconditioner has too much computation on the coarse grid compared to the MILU-CG one. As for the momentum equation, relatively cheap smoother like SIP solver may be sufficient.

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Application of the Krylov Subspace Method to the Incompressible Navier-Stokes Equations (비압축성 Navier-Stokes 방정식에 대한 Krylov 부공간법의 적용)

  • Maeng, Joo-Sung;Choi, IL-Kon;Lim, Youn-Woo
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.24 no.7
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    • pp.907-915
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    • 2000
  • The preconditioned Krylov subspace methods were applied to the incompressible Navier-Stoke's equations for convergence acceleration. Three of the Krylov subspace methods combined with the five of the preconditioners were tested to solve the lid-driven cavity flow problem. The MILU preconditioned CG method showed very fast and stable convergency. The combination of GMRES/MILU-CG solver for momentum and pressure correction equations was found less dependency on the number of the grid points among them. A guide line for stopping inner iterations for each equation is offered.

Model Order Reduction Using Moment-Matching Method Based on Krylov Subspace and Its Application to FRF Calculation for Array-Type MEMS Resonators (Krylov 부공간에 근거한 모멘트일치법을 이용한 모델차수축소법 및 배열형 MEMS 공진기 주파수응답함수 계산에의 응용)

  • Han, Jeong-Sam;Ko, Jin-Hwan
    • Proceedings of the KSME Conference
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    • pp.436-441
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    • 2008
  • One of important factors in designing array-type MEMS resonators is obtaining a desired frequency response function (FRF) within a specific range. In this paper Krylov subspace-based model order reduction using moment-matching with non-zero expansion points is represented to calculate the FRF of array-type resonators. By matching moments at a frequency around a specific range of the array-type resonators, required FRFs can be efficiently calculated with significantly reduced systems regardless of their operating frequencies. In addition, because of the characteristics of moment-matching method, a minimal order of reduced system with a specified accuracy can be determined through an error indicator using successive reduced models, which is very useful to automate the order reduction process and FRF calculation for structural optimization iterations.

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AN ALGORITHM FOR SYMMETRIC INDEFINITE SYSTEMS OF LINEAR EQUATIONS

  • YI, SUCHEOL
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.3 no.2
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    • pp.29-36
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    • 1999
  • It is shown that a new Krylov subspace method for solving symmetric indefinite systems of linear equations can be obtained. We call the method as the projection method in this paper. The residual vector of the projection method is maintained at each iteration, which may be useful in some applications.

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PARALLEL PERFORMANCE OF MULTISPLITTING METHODS WITH PREWEIGHTING

  • Han, Yu-Du;Yun, Jae-Heon
    • Journal of the Korean Mathematical Society
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    • v.49 no.4
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    • pp.805-827
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    • 2012
  • In this paper, we first study convergence of a special type of multisplitting methods with preweighting, and then we provide some comparison results of those multisplitting methods. Next, we propose both parallel implementation of an SOR-like multisplitting method with preweighting and an application of the SOR-like multisplitting method with preweighting to a parallel preconditioner of Krylov subspace method. Lastly, we provide parallel performance results of both the SOR-like multisplitting method with preweighting and Krylov subspace method with the parallel preconditioner to evaluate parallel efficiency of the proposed methods.

A SPARSE APPROXIMATE INVERSE PRECONDITIONER FOR NONSYMMETRIC POSITIVE DEFINITE MATRICES

  • Salkuyeh, Davod Khojasteh
    • Journal of applied mathematics & informatics
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    • v.28 no.5_6
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    • pp.1131-1141
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    • 2010
  • We develop an algorithm for computing a sparse approximate inverse for a nonsymmetric positive definite matrix based upon the FFAPINV algorithm. The sparse approximate inverse is computed in the factored form and used to work with some Krylov subspace methods. The preconditioner is breakdown free and, when used in conjunction with Krylov-subspace-based iterative solvers such as the GMRES algorithm, results in reliable solvers. Some numerical experiments are given to show the efficiency of the preconditioner.

AN ITERATIVE METHOD FOR SYMMETRIC INDEFINITE LINEAR SYSTEMS

  • Walker, Homer-F.;Yi, Su-Cheol
    • Communications of the Korean Mathematical Society
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    • v.19 no.2
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    • pp.375-388
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    • 2004
  • For solving symmetric systems of linear equations, it is shown that a new Krylov subspace method can be obtained. The new approach is one of the projection methods, and we call it the projection method for convenience in this paper. The projection method maintains the residual vector like simpler GMRES, symmetric QMR, SYMMLQ, and MINRES. By studying the quasiminimal residual method, we show that an extended projection method and the scaled symmetric QMR method are equivalent.

Krylov subspace-based model order reduction for Campbell diagram analysis of large-scale rotordynamic systems

  • Han, Jeong Sam
    • Structural Engineering and Mechanics
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    • v.50 no.1
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    • pp.19-36
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    • 2014
  • This paper focuses on a model order reduction (MOR) for large-scale rotordynamic systems by using finite element discretization. Typical rotor-bearing systems consist of a rotor, built-on parts, and a support system. These systems require careful consideration in their dynamic analysis modeling because they include unsymmetrical stiffness, localized nonproportional damping, and frequency-dependent gyroscopic effects. Because of this complex geometry, the finite element model under consideration may have a very large number of degrees of freedom. Thus, the repeated dynamic analyses used to investigate the critical speeds, stability, and unbalanced response are computationally very expensive to complete within a practical design cycle. In this study, we demonstrate that a Krylov subspace-based MOR via moment matching significantly speeds up the rotordynamic analyses needed to check the whirling frequencies and critical speeds of large rotor systems. This approach is very efficient, because it is possible to repeat the dynamic simulation with the help of a reduced system by changing the operating rotational speed, which can be preserved as a parameter in the process of model reduction. Two examples of rotordynamic systems show that the suggested MOR provides a significant reduction in computational cost for a Campbell diagram analysis, while maintaining accuracy comparable to that of the original systems.

Multilevel acceleration of scattering-source iterations with application to electron transport

  • Drumm, Clif;Fan, Wesley
    • Nuclear Engineering and Technology
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    • v.49 no.6
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    • pp.1114-1124
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    • 2017
  • Acceleration/preconditioning strategies available in the SCEPTRE radiation transport code are described. A flexible transport synthetic acceleration (TSA) algorithm that uses a low-order discrete-ordinates ($S_N$) or spherical-harmonics ($P_N$) solve to accelerate convergence of a high-order $S_N$ source-iteration (SI) solve is described. Convergence of the low-order solves can be further accelerated by applying off-the-shelf incomplete-factorization or algebraic-multigrid methods. Also available is an algorithm that uses a generalized minimum residual (GMRES) iterative method rather than SI for convergence, using a parallel sweep-based solver to build up a Krylov subspace. TSA has been applied as a preconditioner to accelerate the convergence of the GMRES iterations. The methods are applied to several problems involving electron transport and problems with artificial cross sections with large scattering ratios. These methods were compared and evaluated by considering material discontinuities and scattering anisotropy. Observed accelerations obtained are highly problem dependent, but speedup factors around 10 have been observed in typical applications.

DATA MINING AND PREDICTION OF SAI TYPE MATRIX PRECONDITIONER

  • Kim, Sang-Bae;Xu, Shuting;Zhang, Jun
    • Journal of applied mathematics & informatics
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    • v.28 no.1_2
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    • pp.351-361
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    • 2010
  • The solution of large sparse linear systems is one of the most important problems in large scale scientific computing. Among the many methods developed, the preconditioned Krylov subspace methods are considered the preferred methods. Selecting a suitable preconditioner with appropriate parameters for a specific sparse linear system presents a challenging task for many application scientists and engineers who have little knowledge of preconditioned iterative methods. The prediction of ILU type preconditioners was considered in [27] where support vector machine(SVM), as a data mining technique, is used to classify large sparse linear systems and predict best preconditioners. In this paper, we apply the data mining approach to the sparse approximate inverse(SAI) type preconditioners to find some parameters with which the preconditioned Krylov subspace method on the linear systems shows best performance.