• Title/Summary/Keyword: analytical Jacobian

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Form-finding analysis of suspension bridges using an explicit Iterative approach

  • Cao, Hongyou;Zhou, Yun-Lai;Chen, Zhijun;Wahab, Magd Abdel
    • Structural Engineering and Mechanics
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    • v.62 no.1
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    • pp.85-95
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    • 2017
  • This paper presents an explicit analytical iteration method for form-finding analysis of suspension bridges. By extending the conventional analytical form-finding method predicated on the elastic catenary theory, two nonlinear governing equations are derived for calculating the accurate unstrained lengths of the entire cable systems both the main cable and the hangers. And for the gradient-based iteration method, the derivation of explicit calculation for the Jacobian matrix while solving the nonlinear governing equation enhances the computational efficiency. The results from sensitivity analysis show well performance of the explicit Jacobian matrix compared with the traditional finite difference method. According to two numerical examples of long span suspension bridges studied, the proposed method is also compared with those reported approaches or the fundamental criterions in suspension bridge structural analysis, which eventually confirms the accuracy and efficiency of the proposed approach.

Inversion of spectral analysis of surface waves with analytic Jacobian (해석적 자코비안을 이용한 표면파 기법의 역산)

  • Ha, Hee-Sang
    • Journal of the Korean Geophysical Society
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    • v.5 no.3
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    • pp.233-245
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    • 2002
  • The spectral-analysis-of-surface-waves (SASW) method is a nondestructive testing method based upon generation and detection of elastic stress waves. SASW is widely used as one of the techniques to determine stiffness profile in engineering geophysics. The essential steps involved are construction of an experimental dispersion curve from data collected in situ, and inversion of the dispersion curve to determine the stiffness profile. The main object of this study is to derive an analytical Jacobian for the inversion. If we set the subsurface to N homogeneous layer, it could save 2N times Jacobian calculation compared to numerical jacobian calculation during inversion. To reconstruct a stiffness profile, constrained damped least square method was applied for the inversion. The algorithm was tested for the numerical data and for the real asphalt and tunnel data, which were able to verify the stiffness profile. The stiffness profile reconstructed by the algorithm showed the possibility to appraise the soundness of tunnel with applications SASW.

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Non-rigid Image Registration using Constrained Optimization (Constrained 최적화 기법을 이용한 Non-rigid 영상 등록)

  • Kim Jeong tae
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.10C
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    • pp.1402-1413
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    • 2004
  • In non-rigid image registration, the Jacobian determinant of the estimated deformation should be positive everywhere since physical deformations are always invertible. We propose a constrained optimization technique at ensures the positiveness of Jacobian determinant for cubic B-spline based deformation. We derived sufficient conditions for positive Jacobian determinant by bounding the differences of consecutive coefficients. The parameter set that satisfies the conditions is convex; it is the intersection of simple half spaces. We solve the optimization problem using a gradient projection method with Dykstra's cyclic projection algorithm. Analytical results, simulations and experimental results with inhale/exhale CT images with comparison to other methods are presented.

Image Restoration of Remote Sensing High Resolution Imagery Using Point-Jacobian Iterative MAP Estimation (Point-Jacobian 반복 MAP 추정을 이용한 고해상도 영상복원)

  • Lee, Sang-Hoon
    • Korean Journal of Remote Sensing
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    • v.30 no.6
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    • pp.817-827
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    • 2014
  • In the satellite remote sensing, the operational environment of the satellite sensor causes image degradation during the image acquisition. The degradation results in noise and blurring which badly affect identification and extraction of useful information in image data. This study proposes a maximum a posteriori (MAP) estimation using Point-Jacobian iteration to restore a degraded image. The proposed method assumes a Gaussian additive noise and Markov random field of spatial continuity. The proposed method employs a neighbor window of spoke type which is composed of 8 line windows at the 8 directions, and a boundary adjacency measure of Mahalanobis square distance between center and neighbor pixels. For the evaluation of the proposed method, a pixel-wise classification was used for simulation data using various patterns similar to the structure exhibited in high resolution imagery and an unsupervised segmentation for the remotely-sensed image data of 1 mspatial resolution observed over the north area of Anyang in Korean peninsula. The experimental results imply that it can improve analytical accuracy in the application of remote sensing high resolution imagery.

Despeckling and Classification of High Resolution SAR Imagery (고해상도 SAR 영상 Speckle 제거 및 분류)

  • Lee, Sang-Hoon
    • Korean Journal of Remote Sensing
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    • v.25 no.5
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    • pp.455-464
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    • 2009
  • Lee(2009) proposed the boundary-adaptive despeckling method using a Bayesian model which is based on the lognormal distribution for image intensity and a Markov random field(MRF) for image texture. This method employs the Point-Jacobian iteration to obtain a maximum a posteriori(MAP) estimate of despeckled imagery. The boundary-adaptive algorithm is designed to use less information from more distant neighbors as the pixel is closer to boundary. It can reduce the possibility to involve the pixel values of adjacent region with different characteristics. The boundary-adaptive scheme was comprehensively evaluated using simulation data and the effectiveness of boundary adaption was proved in Lee(2009). This study, as an extension of Lee(2009), has suggested a modified iteration algorithm of MAP estimation to enhance computational efficiency and to combine classification. The experiment of simulation data shows that the boundary-adaption results in yielding clear boundary as well as reducing error in classification. The boundary-adaptive scheme has also been applied to high resolution Terra-SAR data acquired from the west coast of Youngjong-do, and the results imply that it can improve analytical accuracy in SAR application.

A Study on the Shape Finding of Cable-Net Structures Introducing General Inverse Matrix (일반역행열(一般逆行列)을 이용(利用)한 케이블네트 구조물(構造物)의 형상결정에 관한 연구)

  • Sur, Sam-Uel;Lee, Jang-Bok
    • Journal of Korean Association for Spatial Structures
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    • v.2 no.1 s.3
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    • pp.75-84
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    • 2002
  • In this study, the 'force density method' for shape finding of cable net structures is presented. This concept is based on the force-length ratios or force densities which are defined for each branch of the net structures. This method renders a simple linear 'analytical form finding' possible. If the free choice of the force densities is restricted by further condition, the linear method is extended to a nonlinear one. The nonlinear one can be applied to the detailed computation of networks. In this paper, the general inverse matrix is introduced to solve the nonlinear equilibrium equation including Jacobian matrix which is rectangular matrix. Several examples for linear and nonlinear analysis applied additional constraints are presented. It is shown that the force density method is suitable for form finding of cable net and the general inverse matrix can be applied to solve the nonlinear equation without Lagrangian factors.

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Implementation of the modified compression field theory in a tangent stiffness-based finite element formulation

  • Aquino, Wilkins;Erdem, Ibrahim
    • Steel and Composite Structures
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    • v.7 no.4
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    • pp.263-278
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    • 2007
  • A finite element implementation of the modified compression field theory (MCFT) using a tangential formulation is presented in this work. Previous work reported on implementations of MCFT has concentrated mainly on secant formulations. This work describes details of the implementation of a modular algorithmic structure of a reinforced concrete constitutive model in nonlinear finite element schemes that use a Jacobian matrix in the solution of the nonlinear system of algebraic equations. The implementation was verified and validated using experimental and analytical data reported in the literature. The developed algorithm, which converges accurately and quickly, can be easily implemented in any finite element code.

Investigation of the Voltage Collapse Mechanism in Three-Phase PWM Rectifiers

  • Ren, Chunguang;Li, Huipeng;Yang, Yu;Han, Xiaoqing;Wang, Peng
    • Journal of Power Electronics
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    • v.17 no.5
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    • pp.1268-1277
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    • 2017
  • Three-phase pulse width modulation (PWM) rectifiers are usually designed under the assumption of ideal ac power supply and input inductance. However, non-ideal circuit parameters may lead to a voltage collapse of PWM rectifiers. This paper investigates the mechanism of voltage collapse in three-phase PWM rectifiers. An analytical stability boundary expression is derived by analyzing the equilibrium point of the averaging state space model, which can not only accurately locate the voltage collapse boundary in the circuit parameter domain, but also reveal the essential characteristic of the voltage collapse. Results are obtained and compared with those of the trial-error method and the Jacobian method. Based on the analysis results, the system parameters can be divided into two categories. One of these categories affects the critical point, and other affects only the instability process. Furthermore, an effective control strategy is proposed to prevent a vulnerable system from being driven into the instability region. The analysis results are verified by the experiments.

Multi-stage Image Restoration for High Resolution Panchromatic Imagery (고해상도 범색 영상을 위한 다중 단계 영상 복원)

  • Lee, Sanghoon
    • Korean Journal of Remote Sensing
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    • v.32 no.6
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    • pp.551-566
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    • 2016
  • In the satellite remote sensing, the operational environment of the satellite sensor causes image degradation during the image acquisition. The degradation results in noise and blurring which badly affect identification and extraction of useful information in image data. Especially, the degradation gives bad influence in the analysis of images collected over the scene with complicate surface structure such as urban area. This study proposes a multi-stage image restoration to improve the accuracy of detailed analysis for the images collected over the complicate scene. The proposed method assumes a Gaussian additive noise, Markov random field of spatial continuity, and blurring proportional to the distance between the pixels. Point-Jacobian Iteration Maximum A Posteriori (PJI-MAP) estimation is employed to restore a degraded image. The multi-stage process includes the image segmentation performing region merging after pixel-linking. A dissimilarity coefficient combining homogeneity and contrast is proposed for image segmentation. In this study, the proposed method was quantitatively evaluated using simulation data and was also applied to the two panchromatic images of super-high resolution: Dubaisat-2 data of 1m resolution from LA, USA and KOMPSAT3 data of 0.7 m resolution from Daejeon in the Korean peninsula. The experimental results imply that it can improve analytical accuracy in the application of remote sensing high resolution panchromatic imagery.