• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.414-422
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• 2021

The aim of this work considers a second order point reactor kinetics model based on the P1 approximation of transport theory, called in this work as P1 point reactor model. The P1 point reactor model implicitly considers the time derivative of the neutron source which has not been thus considered previously. The inverse method to calculate the reactivity in nuclear reactors -chosen because its high accuracy- Matrix Formulation. The numerical results shown that the Matrix Formulation for the reactivity estimation constitutes a method with insignificant calculation errors.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.386-391
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• 2001

This paper presents a new two-point approximation method based on the exponential intervening variable. To avoid the lack of definition of the conventional exponential intervening variables due to zero- or negative-valued design variables the shifting level into each exponential intervening variable is introduced. Then a new quadratic approximation, whose Hessian matrix has only diagonal elements of different values, is proposed in terms of these intervening variables. These diagonal elements are computed in a closed form, which correct the typical error in the approximate gradient of the TANA series due to the lack of definition of exponential type intervening variables and their incomplete second-order terms. Also, a correction coefficient is multiplied to the pre-determined quadratic term to match the value of approximate function with that of the original function at the previous point. Finally, the authors developed a sequential approximate optimizer, solved several typical design problems used in the literature and compared these optimization results with those of TANA-3. These comparisons show that the proposed method gives more efficient and reliable results than TANA-3.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.12
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• pp.3804-3821
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• 1996

The configuration optimization is a structural optimization method which includes the coordinates of a structure as well as the sectional properties in the design variable set. Effective reduction of the weight of discrete structures can be obrained by changing the geometry while satisfying stress, Ei;er bickling, displacement, and frequency constraints, etc. However, the nonlinearity due to the configuration variables may cause the difficulties of the convergence and expensive computational cost. An efficient approximation method for the configuration optimization has been developed to overcome the difficulties. The method approximates the constraint functions based onthe second-order Taylor series expansion with reciprocal design variables. The Hessian matrix is approzimated from the information on previous design points. The developed algotithms are coded and the examples are solved.

• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.125-131
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• 2021

In recent years, Convolutional Neural Networks (CNNs) have achieved outstanding performance in the fields of computer vision such as image classification, object detection, visual quality enhancement, etc. However, as huge amount of computation and memory are required in CNN models, there is a limitation in the application of CNN to low-power environments such as mobile or IoT devices. Therefore, the need for neural network compression to reduce the model size while keeping the task performance as much as possible has been emerging. In this paper, we propose a method to compress CNN models by combining matrix decomposition methods of LR (Low-Rank) approximation and CP (Canonical Polyadic) decomposition. Unlike conventional methods that apply one matrix decomposition method to CNN models, we selectively apply two decomposition methods depending on the layer types of CNN to enhance the compression performance. To evaluate the performance of the proposed method, we use the models for image classification such as VGG-16, RestNet50 and MobileNetV2 models. The experimental results show that the proposed method gives improved classification performance at the same range of 1.5 to 12.1 times compression ratio than the existing method that applies only the LR approximation.

• Structural Engineering and Mechanics
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• v.16 no.1
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• pp.17-34
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• 2003

This paper presents a damage assessment procedure applied to periodic spring mass systems using an eigenvalue sensitivity-based method. The damage is directly related to the stiffness reduction of the damage element. The natural frequencies of periodic structures with one single disorder are found by adopting the transfer matrix approach, consequently, the first order approximation of the natural frequencies with respect to the disordered stiffness in different elements is used to form the sensitivity matrix. The analysis shows that the sensitivity of natural frequencies to damage in different locations depends only on the mode number and the location of damage. The stiffness changes due to damage can be identified by solving a set of underdetermined equations based on the sensitivity matrix. The issues associated with many possible damage locations in large structural systems are addressed, and a means of improving the computational efficiency of damage detection while maintaining the accuracy for large periodic structures with limited available measured natural frequencies, is also introduced in this paper. The incomplete measurements and the effect of random error in terms of measurement noise in the natural frequencies are considered. Numerical results of a periodic spring-mass system of 20 degrees of freedom illustrate that the proposed method is simple and robust in locating single or multiple damages in a large periodic structure with a high computational efficiency.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.27 no.1
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• pp.51-56
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• 2017

This paper presents an approach of predicting the radiated noise due to the structural vibration by internal harmonic forces using the doubly asymptotic approximation (DAA). Acoustic transfer vector is derived from the Helmholtz integral equation and the fluid-structure interaction relation of DAA. Numerical results and analytical results of radiated noise for a cylindrical shell were compared and showed that they were consistent in most of frequencies and radiation directions, but showed errors in some radiated directions in the mid-frequency region. Despite these errors, the prediction method will be suitable for practical radiated noise prediction.

• The Journal of the Acoustical Society of Korea
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• v.25 no.1E
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• pp.1-7
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• 2006

This study examines the reflection characteristic of a thin transition layer of the ocean bottom showing variability with respect to depth. In order to model the surficial sediment simply, we reduce the Biot model to the depth dependent wave equation for the pseudo fluid using the fluid approximation (weak frame approximation). From the reduced equation, the difference between the inherent frequency dependency of the reflection and the frequency dependency resulting from a thin transition layer is investigated. Using Tang's depth porosity profile model of the surficial sediment [D. Tang et al., IEEE J. Oceanic Eng., vol.27(3), 546-560(2002)], we numerically simulated the reflection loss and investigated the contribution from both frequency dependencies. In addition, the effects of different sediment type and varying depth structure of the sediment are discussed.

• Journal of applied mathematics & informatics
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• v.8 no.3
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• pp.935-942
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• 2001

A finite element approximation of a fourth-order nonlinear boundary value problem is given. In the direct implementation, a nonlinear system will be obtained and also a full size matrix will be introduced when Newton’s method is adopted to solve the system. To avoid this difficulty we introduce an iterative scheme which can be shown to converge the positive solution of the system lying between 0 and $sin{\pi}x$.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.2 no.3
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• pp.134-142
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• 1990

A wide-angle approximation in the parabolic equation method is presented to calculate wave transformation in the shallow water. The parabolic approximation to the mild-slope equation is obtain-ed by the use of a splitting matrix, which leads to a generalized equation in form. A numerical model based on a finite difference scheme is presented and computational results are provided to test the model against the laboratory measurements of circular and elliptical shoals. The numerical results are in good agreement with most of experimental data. Therefore it can be concluded that the model shows greater capability to reproduce the characteristics of waves in the refractive focus.

• Korean Journal of Optics and Photonics
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• v.31 no.2
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• pp.59-70
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• 2020

We discuss a modified numerical model based on the Monte Carlo radiative transfer (MCRT) method, i.e., the MCRT matrix method, for the analysis of atmospheric scattering effects in three-dimensional flash LIDAR systems. Based on the MCRT method, the radiative transfer function for a LIDAR signal is constructed in a form of a matrix, which corresponds to the characteristic response. Exploiting the superposition and convolution of the characteristic response matrices under the paraxial approximation, an extended computer simulation model of an overall flash LIDAR system is developed. The MCRT matrix method substantially reduces the number of tracking signals, which may grow excessively in the case of conventional Monte Carlo methods. Consequently, it can readily yield fast acquisition of the signal response under various scattering conditions and LIDAR-system configurations. Using the computational model based on the MCRT matrix method, we carry out numerical simulations of a three-dimensional flash LIDAR system operating under different atmospheric conditions, varying the scattering coefficient in terms of visible distance. We numerically analyze various phenomena caused by scattering effects in this system, such as degradation of the signal-to-noise ratio, glitches, and spatiotemporal spread and time delay of the LIDAR signals. The MCRT matrix method is expected to be very effective in analyzing a variety of LIDAR systems, including flash LIDAR systems for autonomous driving.