• Title/Summary/Keyword: Newton Iteration

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Stall Prediction of Wing Using the Nonplanar Lifting Surface Theory and an Iterative Decambering Approach (비평면 양력면 이론과 반복적 캠버변형 기법을 이용한 날개의 실속 특성 예측)

  • 조정현;조진수;조연우
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.34 no.10
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    • pp.1-6
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    • 2006
  • This paper predicts the stall characteristics of three-dimensional wings. An iterative decambering approach is introduced into the nonplanar lifting surface method to take into consideration the stall characteristics of wings. An iterative decambering approach uses known airfoil lift curve and moment curve to predict the stall characteristics of wings. The multi-dimensional Newton iteration is used to take into consideration the coupling between the different sections of wings. Present results are compared with experiments and other numerical results. Computed results are in good agreement with other data. This scheme can be used for any wing with the twist or control surface and for wing-wing configurations such as wing-tail configuration or canard-wing configuration.

Efficient Alalysis of Resistive Networks With Canonical Piecewise-Linear Equations (정규 구간선형 방정식을 갖는 저항성 회로의 효율적인 해석)

  • 조준영;조진국;권용세;김영환
    • Journal of the Korean Institute of Telematics and Electronics A
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    • v.31A no.12
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    • pp.142-151
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    • 1994
  • This paper proposes new algorithms to solve canonical piecewise-linear equations with linear partitions and illustrates their efficiency through the analysis of resistive network. The basic idea of the proposed algorithm is to find the best next guess, closest to the actual solution, at each Newton-Raphson (N-R) iteration by comparing the images of nest guess candidates and that of the actual solution. The proposed algorithm can reduce the number of the N-R iterations rquired for convergence greatly, compared to the actual solution, at each Newton-Raphson (N-R) iteration by comparing the images of next guess candidates and that of the actual solution. The proposed algorithm can reduce the number of the N-R iterations required for convergence greatly, compared to the Katzenelson algorithm. When applied to analyzing test circuits, the proposed algorithm required 8 to 20 times fewer N-R iterations and 5 to 10 times less CPU time than the Katzenelson algorithm, depending on the size of the circuits. The experimental results also exhibit that the efficiency of the proposed algorithm over the Katzenelson algorithm increases as the number of the piecewise-linear regions for the representation of the circuit.

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Dynamic Formulation Using Finite Element and Its Analysis for Flexible Beam (유한요소를 이용한 유연보의 동역학적 정식화 및 해석)

  • Yun Seong-Ho;Eom Ki-Sang
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.18 no.4 s.70
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    • pp.385-393
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    • 2005
  • This paper established the dynamic model of a flexible Timoshenko beam capable of geometrical nonlinearities subject to large overall motions by using the finite element method. Equations of motion are derived by using Hamilton principle and are formulated in terms of finite elements in which the nonlinear constraint equations are adjoined to the system using Lagrange multipliers. The Newmark direct integration method and the Newton-Raphson iteration are employed here for the numerical study which is to demonstrate the efficiency of the proposed formulation.

A Study on the Iterative Solution Procedures for the Elasto-Plastic Large Deflection Analysis of Plates (판부재의 탄소성대변형 유한요소 해석문제에서의 수렴기법에 관한 고찰)

  • 백점기;김창렬;이정권
    • Computational Structural Engineering
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    • v.2 no.3
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    • pp.97-103
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    • 1989
  • In this study, a usefulness of the iterative solution procedures is reviewed for the elasto-plastic large deflection analysis of imperfect plates by finite element method. Three typical solution techniques such as simple incremental(SI) method, Newton-Raphson(NR) method and modified Newton-Raphson (mNR) method are compared. It is concluded that for thin plates which are given rise to the large deflection, iteration for the convergence of the unbalance force should be performed and in this case mNR method is more useful than NR method since the computing time of the former becomes to be a half of the latter, in which the accuracy of the result remains same. For thick plates or thin plates with large initial deflection, however, the use of SI method is quite better since the unbalance force may be negligible.

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A Study on a Load Flow calculation for Preserved Jacobian Matrix's elements except diagonal terms (Jacobian 행렬의 비 대각 요소를 보존시킬 수 있는 조류계산에 관한 연구)

  • Moon, Yong-Hyun;Lee, Jong-Gi;Choi, Byoung-Kon;Park, Jeong-Do;Ryu, Hun-Su
    • Proceedings of the KIEE Conference
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    • 1998.11a
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    • pp.311-315
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    • 1998
  • Load Flow calculation methods can usually be divided into Gauss-Seidel method, Newton-Raphson method and decoupled method. Load flow calculation is a basic on-line or off-line process for power system planning, operation, control and state analysis. These days Newton-Raphson method is mainly used since it shows remarkable convergence characteristics. It, however, needs considerable calculation time in construction and calculation of inverse Jacobian matrix. In addition to that, Newton-Raphson method tends to fail to converge when system loading is heavy and system has a large R/X ratio. In this paper, matrix equation is used to make algebraic expression and then to solve load flow equation and to modify above defects. And it preserve certain part of Jacobian matrix to shorten the time of calculation. Application of mentioned algorithm to 14 bus, 39 bus, 118 bus systems led to identical result and the number of iteration got by Newton-Raphson method. The effect of time reduction showed about 28%, 30%, at each case of 39 bus, 118 bus system.

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Application of Matrix Adaptive Regularization Method for Human Thorax Image Reconstruction (인체 흉부 영상 복원을 위한 행렬 적응 조정 방법의 적용)

  • Jeon, Min-Ho;Kim, Kyung-Youn
    • Journal of IKEEE
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    • v.19 no.1
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    • pp.33-40
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    • 2015
  • Inverse problem in electrical impedance tomography (EIT) is highly ill-posed therefore prior information is used to mitigate the ill-posedness. Regularization methods are often adopted in solving EIT inverse problem to have satisfactory reconstruction performance. In solving the EIT inverse problem, iterative Gauss-Newton method is generally used due to its accuracy and fast convergence. However, its performance is still suboptimal and mainly depends on the selection of regularization parameter. Although, there are few methods available to determine the regularization parameter such as L-curve method they are sometimes not applicable for all cases. Moreover, regularization parameter is a scalar and it is fixed during iteration process. Therefore, in this paper, a novel method is used to determine the regularization parameter to improve reconstruction performance. Conductivity norm is calculated at each iteration step and it used to obtain the regularization parameter which is a diagonal matrix in this case. The proposed method is applied to human thorax imaging and the reconstruction performance is compared with traditional methods. From numerical results, improved performance of proposed method is seen as compared to conventional methods.

Block-Coordinate Gauss-Newton Optimization for Image Registration (영상 정합을 위한 Block-Coordinate Gauss-Newton 최적화)

  • Kim, Dong-Sik
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.6
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    • pp.1-8
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    • 2007
  • In this paper, research on joint optimization of the image spatial registration and the exposure compensation is conducted. The exposure compensation is performed in a frame work of the intensity compensation based on the polynomial approximation of the relationship between images. This compensation is jointly combined with the registration problem employing the Gauss-Newton nonlinear optimization method. In this paper, to perform for a simple and stable optimization, the block-coordinate method is combined with the Gauss-Newton optimization and extensively compared with the traditional approaches. Furthermore, regression analysis is considered in the compensation part for a better stable performance. By combining the block-coordinate method with the Gauss-Newton optimization, we can obtain a compatible performance reducing the computational complexity and stabilizing the performance. In the numerical result for a particular image, we obtain a satisfactory result for 10 repeats of the iteration, which implies a 50% reduction of the computational complexity. The error is also further reduced by 1.5dB compared to the ordinary method.

Conductivity Image Reconstruction Using Modified Gauss-Newton Method in Electrical Impedance Tomography (전기 임피던스 단층촬영 기법에서 수정된 가우스-뉴턴 방법을 이용한 도전율 영상 복원)

  • Kim, Bong Seok;Park, Hyung Jun;Kim, Kyung Youn
    • Journal of IKEEE
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    • v.19 no.2
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    • pp.219-224
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    • 2015
  • Electrical impedance tomography is an imaging technique to reconstruct the internal conductivity distribution based on applied currents and measured voltages in a domain of interest. In this paper, a modified Gauss-Newton method is proposed for conductivity image reconstruction. In the proposed method, the dimension of the inverse term is reduced by replacing the number of elements with the number of measurement data in the conductivity updating equation of the conventional Gauss-Newton method. Therefore, the computation time is greatly reduced as compared to the conventional Gauss-Newton method. Moreover, the regularization parameter is selected by computing the minimum-maximum from the diagonal components of the Jacobian matrix at every iteration. The numerical experiments with several scenarios were carried out to evaluate the reconstruction performance of the proposed method.

Optimal Power Flow Study by The Newton's Method (뉴톤법에 의한 최적전력 조류계산)

  • Hwang, Kab-Ju
    • Proceedings of the KIEE Conference
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    • 1989.07a
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    • pp.173-178
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    • 1989
  • Optimal Power Flow (OPF) solution by the Newton's method provides a reliable and robust method to classical OPF problems. The major challenge in algorithm development is to identify the binding inequalities efficiently. This paper propose a simple strategy to identify the binding set. From the mechanism of penalty shifting with soft penalty in trial iteration, a active binding sit is identified automatically. This paper also suggests a technique to solve the linear system whore coefficients are presented by the matrix. This implementation is highly efficient for sparsity programming. Case study for 3,5,14,118,190 bus and practrical KEPCO 305 bus system are performed as well.

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A TWO-LEVEL FINITE ELEMENT METHOD FOR THE STEADY-STATE NAVIER-STOKES/DARCY MODEL

  • Fang, Jilin;Huang, Pengzhan;Qin, Yi
    • Journal of the Korean Mathematical Society
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    • v.57 no.4
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    • pp.915-933
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    • 2020
  • A two-level finite element method based on the Newton iterative method is proposed for solving the Navier-Stokes/Darcy model. The algorithm solves a nonlinear system on a coarse mesh H and two linearized problems of different loads on a fine mesh h = O(H4-𝜖). Compared with the common two-grid finite element methods for the considered problem, the presented two-level method allows for larger scaling between the coarse and fine meshes. Moreover, we prove the stability and convergence of the considered two-level method. Finally, we provide numerical experiment to exhibit the effectiveness of the presented method.