• Title/Summary/Keyword: Conjugate Gradient 법

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Application of the Preconditioned Conjugate Gradient Method to the Generalized Finite Element Method with Global-Local Enrichment Functions (전처리된 켤레구배법의 전체-국부 확장함수를 지닌 일반유한요소해석에의 응용)

  • Choi, Won-Jeong;Kim, Min-Sook;Kim, Dae-Jin;Lee, Young-Hak;Kim, Hee-Cheul
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.24 no.4
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    • pp.405-412
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    • 2011
  • This paper introduces the generalized finite element method with global-local enrichment functions using the preconditioned conjugate gradient method. The proposed methodology is able to generate enrichment functions for problems where limited a-priori knowledge on the solution is available and to utilize a preconditioner and initial guess of good quality with only small addition of computational cost. Thus, it is very effective to analyze problems where a complex behavior is locally exhibited. Several numerical experiments are performed to confirm its effectiveness and show that it is computationally more efficient than the analysis utilizing direct solvers such as Gauss elimination method.

Inverse Problem of Determining Unknown Inlet Temperature Profile in Two Phase Laminar Flow in a Parallel Plate Duct by Using Regularization Method (조정법을 이용한 덕트 내의 이상 층류 유동에 대한 입구 온도분포 역해석)

  • Hong, Yun-Ky;Baek, Seung-Wook
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.28 no.9
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    • pp.1124-1132
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    • 2004
  • The inverse problem of determining unknown inlet temperature in thermally developing, hydrodynamically developed two phase laminar flow in a parallel plate duct is considered. The inlet temperature profile is determined by measuring temperature in the flow field. No prior information is needed for the functional form of the inlet temperature profile. The inverse convection problem is solved by minimizing the objective function with regularization method. The conjugate gradient method as iterative method and the Tikhonov regularization method are employed. The effects of the functional form of inlet temperature, the number of measurement points and the measurement errors are investigated. The accuracy and efficiency of these two methods are compared and discussed.

The Estimation of an Origin-Destination Matrix from Traffic Counts using Conjugate Gradient Method in Nationwide Networks (관측교통량 기반 기종점 OD행렬 추정모형의 대규모 가로망에 적용(CG모형 적용을 중심으로))

  • Lee, Heon-Ju;Lee, Seung-Jae
    • Journal of Korean Society of Transportation
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    • v.23 no.3 s.81
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    • pp.61-71
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    • 2005
  • We evaluated the availability of Origin-Destination Matrix from traffic counts Using conjugate gradient method to large scale networks by applying it to the networks in 246 zones. As a result of the analysis of the consistency of the model on Nationwide Networks, the upper and lower levels in model had the systematic relationship internally. From the analysis of the estimable power or the model according to the number of traffic counting links, the error in traffic volume had the estimable power in the range of permissible error. In addition, the estimable power of estimation of an Origin-Destination Matrix was more satisfactory than that of existing methods. We conclude that conjugate gradient method cab be applied to nationwide networks if we can make sure that the algorithm of the developed model is reliable by doing various kinds of experiment.

A Parallel Algorithm for Large DOF Structural Analysis Problems (대규모 자유도 문제의 구조해석을 위한 병렬 알고리즘)

  • Kim, Min-Seok;Lee, Jee-Ho
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.23 no.5
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    • pp.475-482
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    • 2010
  • In this paper, an efficient two-level parallel domain decomposition algorithm is suggested to solve large-DOF structural problems. Each subdomain is composed of the coarse problem and local problem. In the coarse problem, displacements at coarse nodes are computed by the iterative method that does not need to assemble a stiffness matrix for the whole coarse problem. Then displacements at local nodes are computed by Multi-Frontal Sparse Solver. A parallel version of PCG(Preconditioned Conjugate Gradient Method) is developed to solve the coarse problem iteratively, which minimizes the data communication amount between processors to increase the possible problem DOF size while maintaining the computational efficiency. The test results show that the suggested algorithm provides scalability on computing performance and an efficient approach to solve large-DOF structural problems.

Optimization Inverse Design Technique for Fluid Machinery Impellers (유체기계 임펠러의 최적 역설계 기법)

  • Kim J. S.;Park W. G.
    • Journal of computational fluids engineering
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    • v.3 no.1
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    • pp.37-45
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    • 1998
  • A new and efficient inverse design method based on the numerical optimization technique has been developed. The 2-D incompressible Navier-Stokes equations are solved for obtaining the objective functions and coupled with the optimization procedure to perform the inverse design. The steepest descent and the conjugate gradient method have been applied to find the searching direction. The golden section method was applied to compute the design variable intervals. It has been found that the airfoil and the pump impellers are well converged to their targeting shapes.

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Comparison of Regularization Techniques for an Inverse Radiation Boundary Analysis (역복사경계해석을 위한 다양한 조정법 비교)

  • Kim, Ki-Wan;Shin, Byeong-Seon;Kil, Jeong-Ki;Yeo, Gwon-Koo;Baek, Seung-Wook
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.29 no.8 s.239
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    • pp.903-910
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    • 2005
  • Inverse radiation problems are solved for estimating the boundary conditions such as temperature distribution and wall emissivity in axisymmetric absorbing, emitting and scattering medium, given the measured incident radiative heat fluxes. Various regularization methods, such as hybrid genetic algorithm, conjugate-gradient method and finite-difference Newton method, were adopted to solve the inverse problem, while discussing their features in terms of estimation accuracy and computational efficiency. Additionally, we propose a new combined approach that adopts the hybrid genetic algorithm as an initial value selector and uses the finite-difference Newton method as an optimization procedure.

Numerical Analysis of Shallow Water Equation with Fully Implicit Method (음해법을 이용한 천수방정식의 수치해석)

  • Kang, Ju Whan;Park, Sang Hyun;Lee, Kil Seong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.13 no.3
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    • pp.119-127
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    • 1993
  • Recently, ADI scheme has been a most common tool for solving shallow water equation numerically. But ADI models of tidal flow is likely to cause so called ADI effect in such a region of the Yellow Sea which shows complex topography and has submarine canyons especially. To overcome this, a finite difference algorithm is developed which adopts fully implicit method and preconditioned conjugate gradient squared method. Applying the algorithm including simulation of intertidal zone to Sae-Man-Keum. velocity fields and flooding/drying phenomena are simulated well in spite of complex topography.

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A Multiresolution Wavelet Scattering Analysis of Microstrip Patch antennas (마이크로스트립 패치 안테나의 다중 분해능 웨이블릿 산란해석법)

  • 강병용;주세훈;빈영부;김형훈;김형동
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.9 no.5
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    • pp.640-647
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    • 1998
  • Microstrip patch antennas are analyzed by a multiresolution wavelet method. The spectral Green's dyad of the structure is obtained and its joint spatial-spectral domain representations are presented. Based on the joint spatial-spectral domain representation, we show that the spectral-domain wavelets are useful in the analysis of this problem. We obtain the matrix equations of the integral equations of this Green's dyad by using the method of moment(MoM), and efficiently solve the problem using the spectral domain wavelet transform concepts in conjuction with the conjugate gradient method. The results for a single-layered square patch are compared with those of conventional MoM and CG-FFT.

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A Study on GPU Computing of Bi-conjugate Gradient Method for Finite Element Analysis of the Incompressible Navier-Stokes Equations (유한요소 비압축성 유동장 해석을 위한 이중공액구배법의 GPU 기반 연산에 대한 연구)

  • Yoon, Jong Seon;Jeon, Byoung Jin;Jung, Hye Dong;Choi, Hyoung Gwon
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.40 no.9
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    • pp.597-604
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    • 2016
  • A parallel algorithm of bi-conjugate gradient method was developed based on CUDA for parallel computation of the incompressible Navier-Stokes equations. The governing equations were discretized using splitting P2P1 finite element method. Asymmetric stenotic flow problem was solved to validate the proposed algorithm, and then the parallel performance of the GPU was examined by measuring the elapsed times. Further, the GPU performance for sparse matrix-vector multiplication was also investigated with a matrix of fluid-structure interaction problem. A kernel was generated to simultaneously compute the inner product of each row of sparse matrix and a vector. In addition, the kernel was optimized to improve the performance by using both parallel reduction and memory coalescing. In the kernel construction, the effect of warp on the parallel performance of the present CUDA was also examined. The present GPU computation was more than 7 times faster than the single CPU by double precision.

Battery State-of-Charge Estimation Using ANN and ANFIS for Photovoltaic System

  • Cho, Tae-Hyun;Hwang, Hye-Rin;Lee, Jong-Hyun;Lee, In-Soo
    • The Journal of Korean Institute of Information Technology
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    • v.18 no.5
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    • pp.55-64
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    • 2020
  • Estimating the state of charge (SOC) of a battery is essential for increasing the stability and reliability of a photovoltaic system. In this study, battery SOC estimation methods were proposed using artificial neural networks (ANNs) with gradient descent (GD), Levenberg-Marquardt (LM), and scaled conjugate gradient (SCG), and an adaptive neuro-fuzzy inference system (ANFIS). The charge start voltage and the integrated charge current were used as input data and the SOC was used as output data. Four models (ANN-GD, ANN-LM, ANN-SCG, and ANFIS) were implemented for battery SOC estimation and compared using MATLAB. The experimental results revealed that battery SOC estimation using the ANFIS model had both the highest accuracy and highest convergence speed.