• Journal of IKEEE
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• v.28 no.2
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• pp.158-167
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• 2024

In this study, U-net model based on electrical capacitance is applied to monitor the condition inside the pipeline of semiconductor rear end process implemented in the numerical simulation. Capacitance values measured from electrodes attached to the pipeline is used as input data for the U-net network model and estimated permittivity distribution by the U-net model is used to reconstructed cross-sectional image at the pipeline. In the numerical simulation, images reconstructed by U-net model, Fully-connected neural network (FCNN) model and Newton-Raphson method are compared for evaluation. U-net model shows good results as compared to other models.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.73-78
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• 2004

In this research, the photoelastic experimental hybrid method with Hook-Jeeves numerical method has been developed: This method is more precise and stable than the photoelastic experimental hybrid method with Newton-Rapson numerical method with Gaussian elimination method. Using the photoelastic experimental hybrid method with Hook-Jeeves numerical method, we can separate stress components from isochromatics only and stress intensity factors and stress concentration factors can be determined. The photoelastic experimental hybrid method with Hook-Jeeves had better be used in the full field experiment than the photoelastic experimental hybrid method with Newton-Rapson with Gaussian elimination method.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.3
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• pp.481-490
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• 2002

The purpose of this paper is to evaluate the efficiency of various solution techniques and propose new efficient solution techniques for space trusses. Solution techniques used in this study are three load control methods (Newton-Raphson Method, modified Newton-Raphson Method, Secant-Newton Method), two load-displacement control methods(Arc-length Method, Work Increment Control Method) and three combined load-displacement control methods(Combined Arc-length Method I , Combined Arc-length MethodⅡ, Combined Work Increment Control Method). To evaluate the efficiency of these solution techniques, we must examine accuracy of their solutions, convergences and computing times of numerical examples. The combined load-displacement control methods are the most efficient in the geometric nonlinear solution techniques and in tracing post-buckling behavior of space truss. The combined work increment control method is the most efficient in tracing the buckling load of spate trusses with high degrees of freedom.

• Computational Structural Engineering
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• v.10 no.4
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• pp.217-228
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• 1997

The high precision analysis by the p-version of the finite element method are fairly well established as highly efficient method for linear elastic problems, especially in the presence of stress singularity. It has been noted that the merits of the p-version are accuracy, modeling simplicity, robustness, and savings in user's and CPU time. However, little has been done to exploit their benefits in elasto-plastic analysis. In this paper, the p-version finite element model is proposed for the materially nonlinear analysis that is based on the incremental theory of plasticity using the constitutive equation for work-hardening materials, and the associated flow rule. To obtain the solution of nonlinear equation, the Newton-Raphson method and initial stiffness method, etc are used. Several numerical examples are tested with the help of the square plates with cutout, the thick-walled cylinder under internal pressure, and the circular plate with uniformly distributed load. Those results are compared with the theoretical solutions and the numerical solutions of ADINA

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.1
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• pp.15-26
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• 2003

Ultrasonic inspection methods are widely used for detecting flaws in materials. The signal analysis step plays a crucial part in the data interpretation process. A number of signal processing methods have been proposed to classify ultrasonic flaw signals. One of the more popular methods involves the extraction of an appropriate set of features followed by the use of a neural network for the classification of the signals in the feature space. This paper describes an alternative approach which uses the least mean square (LMS) method and expectation maximization (EM) algorithm with the model based deconvolution which is employed for classifying nondestructive evaluation (NDE) signals from steam generator tubes in a nuclear power plant. The signals due to cracks and deposits are not significantly different. These signals must be discriminated to prevent from happening a huge disaster such as contamination of water or explosion. A model based deconvolution has been described to facilitate comparison of classification results. The method uses the space alternating generalized expectation maximization (SAGE) algorithm In conjunction with the Newton-Raphson method which uses the Hessian parameter resulting in fast convergence to estimate the time of flight and the distance between the tube wall and the ultrasonic sensor Results using these schemes for the classification of ultrasonic signals from cracks and deposits within steam generator tubes are presented and showed a reasonable performances.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.1
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• pp.27-35
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• 2005

Ultrasonic inspection methods are widely used for detecting flaws in materials. The signal analysis step plays a crucial part in the data interpretation process. A number of signal processing methods have been proposed to classify ultrasonic flaw signals. One of the more popular methods involves the extraction of an appropriate set of features followed by the use of a neural network for the classification of the signals in the feature spare. This paper describes an alternative approach which uses the least mean square (LMS) method and exportation maximization (EM) algorithm with the model based deconvolution which is employed for classifying nondestructive evaluation (NDE) signals from steam generator tubes in a nuclear power plant. The signals due to cracks and deposits are not significantly different. These signals must be discriminated to prevent from happening a huge disaster such as contamination of water or explosion. A model based deconvolution has been described to facilitate comparison of classification results. The method uses the space alternating generalized expectation maximiBation (SAGE) algorithm ill conjunction with the Newton-Raphson method which uses the Hessian parameter resulting in fast convergence to estimate the time of flight and the distance between the tube wall and the ultrasonic sensor. Results using these schemes for the classification of ultrasonic signals from cracks and deposits within steam generator tubes are presented and showed a reasonable performances.

• Journal of IKEEE
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• v.18 no.2
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• pp.272-281
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• 2014

In electrical impedance tomography (EIT), modified Newton Raphson (mNR) method is widely used inverse algorithm for static image reconstruction due to its convergence speed and estimation accuracy. The unknown conductivity distribution is estimated iteratively by minimizing a cost functional such that the residual error namely the difference in measured and calculated voltages is reduced. Although, mNR method has good estimation performance, EIT inverse problem still suffers from ill-conditioned and ill-posedness nature. To mitigate the ill-posedness, generally, regularization methods are adopted. The inverse solution is highly dependent on the choice of regularization parameter. In most cases, the regularization parameter has a constant value and is chosen based on experience or trail and error approach. In situations, when the internal distribution changes or with high measurement noise, the solution does not get converged with the use of constant regularization parameter. Therefore, in this paper, in order to improve the image reconstruction performance, we propose a new scheme to determine the regularization parameter. The regularization parameter is computed based on residual error and updated every iteration. The proposed scheme is tested with numerical simulations and laboratory phantom experiments. The results show an improved reconstruction performance when using the proposed regularization scheme as compared to constant regularization scheme.

• Proceedings of the Korean Statistical Society Conference
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• 2004.11a
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• pp.1-8
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• 2004

We address the problem of parameter estimation in multivariate distributions under ignorable non-monotone missing data. The factoring likelihood method for monotone missing data, termed by Robin (1974), is extended to a more general case of non-monotone missing data. The proposed method is algebraically equivalent to the Newton-Raphson method for the observed likelihood, but avoids the burden of computing the first and the second partial derivatives of the observed likelihood Instead, the maximum likelihood estimates and their information matrices for each partition of the data set are computed separately and combined naturally using the generalized least squares method. A numerical example is also presented to illustrate the method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.144-150
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• 2000

In this paper, we introduce a modified six-degrees-of-freedom parallel-link manipulator, which will be applied to the human vibration experiments. We analyze the inverse kinematics and workspace of this manipulator and comprehend the characteristics of kinematics analyzed. Additionally, solutions of forward kinematics are obtained through the iterative Newton-Raphson method known as one of the most used numerical analysis. Finally, dynamic equation of the manipulator is derived in closed form through the Newton-Euler approach, which will be used for the development of control software.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.03a
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• pp.481-490
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• 2003

This paper presents an efficient eigensolution method for non-proportionally damped systems. The proposed method is obtained by applying the accelerated Newton-Raphson technique and the orthonormal condition of the eigenvectors to the linearized form of the quadratic eigenproblem. A step length and a selective scheme are introduced to increase the convergence of the solution. The step length can be evaluated by minimizing the norm of the residual vector using the least square method. While the singularity may occur during factorizing process in other iteration methods such as the inverse iteration method and the subspace iteration method if the shift value is close to an exact eigenvalue, the proposed method guarantees the nonsingularity by introducing the orthonormal condition of the eigenvectors, which can be proved analytically. A numerical example is presented to demonstrate the effectiveness of the proposed method.