• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1195-1205
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• 2022

Recent developments on spectral diffusion algorithms, i.e., algorithms which exploit the projection of the solution on the eigenfunctions of the Laplacian operator, demonstrated their effective applicability in fast transient conditions. Nevertheless, the numerical error introduced by these algorithms, together with the uncertainties associated with model parameters, may impact the reliability of the predictions on short-lived volatile fission product release from nuclear fuel. In this work, we provide an upper bound on the numerical error introduced by the presented spectral diffusion algorithm, in both constant and time-varying conditions, depending on the number of modes and on the time discretization. The definition of this upper bound allows introducing a methodology to a priori bound the numerical error on short-lived volatile fission product retention.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.22 no.1
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• pp.15-28
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• 2018

Recently Machine Learning algorithms are widely used to process Big Data in various applications and a lot of these applications are executed in run time. Therefore the speed of Machine Learning algorithms is a critical issue in these applications. However the most of modern iteration Machine Learning algorithms use a successive iteration technique well-known in Numerical Linear Algebra. But this technique has a very low convergence, needs a lot of iterations to get solution of considering problems and therefore a lot of time for processing even on modern multi-core computers and clusters. Tchebychev iteration technique is well-known in Numerical Linear Algebra as an attractive candidate to decrease the number of iterations in Machine Learning iteration algorithms and also to decrease the running time of these algorithms those is very important especially in run time applications. In this paper we consider the usage of Tchebychev iterations for acceleration of well-known K-Means and SVM (Support Vector Machine) clustering algorithms in Machine Leaning. Some examples of usage of our approach on modern multi-core computers under Apache Spark framework will be considered and discussed.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.714-719
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• 2004

This paper presents two numerical algorithms for registration of cross-sectional medical images such as CT (Computerized Tomography) or MRI (Magnetic Resonance Imaging) by using geometrical information from helix or line fiducials. The registration algorithms are designed to be used for a surgical robot working inside cavities of human body. A cylindrical device with a combination of line and helix fiducials were also devised and is supposed to be attached to the end-effector of surgical robot. The algorithms and the fiducial pattern were tested in various computer-simulated situations, and the results indicate excellent overall registration accuracy.

• Structural Engineering and Mechanics
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• v.70 no.6
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• pp.649-659
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• 2019

Vibration-based structural damage detection through optimization algorithms and minimization of objective function has recently become an interesting research topic. Application of various objective functions as well as optimization algorithms may affect damage diagnosis quality. This paper proposes a new damage identification method using Moth-Flame Optimization (MFO). MFO is a nature-inspired algorithm based on moth's ability to navigate in dark. Objective function consists of a term with modal assurance criterion flexibility and natural frequency. To show the performance of the said method, two numerical examples including truss and shear frame have been studied. Furthermore, Los Alamos National Laboratory test structure was used for validation purposes. Finite element model for both experimental and numerical examples was created by MATLAB software to extract modal properties of the structure. Mode shapes and natural frequencies were contaminated with noise in above mentioned numerical examples. In the meantime, one of the classical optimization algorithms called particle swarm optimization was compared with MFO. In short, results obtained from numerical and experimental examples showed that the presented method is efficient in damage identification.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.26 no.4
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• pp.323-332
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• 2022

This paper presents a numerical study on multigrid algorithms of V-cycle type for problems posed in the Hilbert space H(curl) in three dimensions. The multigrid methods are designed for discrete problems originated from the discretization using the hexahedral Nédélec edge element of the lowest-order. Our suggested methods are associated with smoothers constructed by substructuring based on domain decomposition methods of nonoverlapping type. Numerical experiments to demonstrate the robustness and the effectiveness of the suggested algorithms are also provided.

• Nonlinear Functional Analysis and Applications
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• v.27 no.3
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• pp.553-568
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• 2022

In this paper, we introduce and study two different iterative hybrid projection algorithms for solving a fixed point problem of nonexpansive mappings. The first algorithm is generated by the combination of the inertial method and the hybrid projection method. On the other hand, the second algorithm is constructed by the convex combination of three updated vectors and the hybrid projection method. The strong convergence of the two proposed algorithms are proved under very mild assumptions on the scalar control. For illustrating the advantages of these two newly invented algorithms, we created some numerical results to compare various numerical performances of our algorithms with the algorithm proposed by Dong and Lu [11].

• Wind and Structures
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• v.32 no.1
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• pp.71-80
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• 2021

In steel cable bridges, the use of magnetorheological (MR) dampers between butt cables is constantly increasing to dampen vibrations caused by rain and wind. The biggest problem in the actual applications of those devices is to launch a kind of appropriate algorithm that can effectively and efficiently suppress the perturbation of the tie through basic calculations and optimal solutions. This article discusses the optimal evolutionary design based on a linear and quadratic regulator (hereafter LQR) to lessen the perturbation of the bridges with cables. The control numerical algorithms are expected to effectively and efficiently decrease the possible risks of the structural response in amplification owing to the feedback force in the direction of the MR attenuator. In addition, these numerical algorithms approximate those optimal linear quadratic regulator control forces through the corresponding damping and stiffness, which significantly lessens the work of calculating the significant and optimal control forces. Therefore, it has been shown that it plays an important and significant role in the practical application design of semiactive MR control power systems. In the present proposed novel evolutionary parallel distributed compensator scheme, the vibrational control problem with a simulated demonstration is used to evaluate the numerical algorithmic performance and effectiveness. The results show that these semiactive MR control numerical algorithms which are present proposed in the present paper has better performance than the optimal and the passive control, which is almost reaching the levels of linear quadratic regulator controls with minimal feedback requirements.

• Geomechanics and Engineering
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• v.23 no.3
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• pp.189-206
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• 2020

The accurate modeling of boundary conditions is important in simulations of the discrete element method (DEM) and can affect the numerical results significantly. In conventional triaxial compression (CTC) tests, the specimens are wrapped by flexible membranes allowing to deform freely. To accurately model the boundary conditions of CTC, new flexible boundary algorithms for 2D and 3D DEM simulations are proposed. The new algorithms are computationally efficient and easy to implement. Moreover, both horizontal and vertical component of confining pressure are considered in the 2D and 3D algorithms, which can ensure that the directions of confining pressure are always perpendicular to the specimen surfaces. Furthermore, the boundaries are continuous and closed in the new algorithms, which can prevent the escape of particles from the specimens. The effectiveness of the proposed algorithms is validated by biaxial and triaxial simulations of granular materials. The results show that the algorithms allow the boundaries to deform non-uniformly on the premise of maintaining high control accuracy of confining pressure. Meanwhile, the influences of different lateral boundary conditions on the numerical results are discussed. It is indicated that the flexible boundary is more appropriate for the models with large strain or significant localization than rigid boundary.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.14 no.1
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• pp.43-56
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• 2010

The representative numerical algorithms to solve the time dependent Navier-Stokes equations are projection type methods. Lots of projection schemes have been developed to find more accurate solutions. But most of projection methods [4, 11] suffer from inconsistency and requesting unknown datum. E and Liu in [5] constructed the gauge method which splits the velocity $u=a+{\nabla}{\phi}$ to make consistent and to replace requesting of the unknown values to known datum of non-physical variables a and ${\phi}$. The errors are evaluated in [9]. But gauge method is not still obvious to find out suitable combination of discrete finite element spaces and to compute boundary derivative of the gauge variable ${\phi}$. In this paper, we define 4 gauge algorithms via combining both 2 decomposition operators and 2 boundary conditions. And we derive variational derivative on boundary and analyze numerical results of 4 gauge algorithms in various discrete spaces combinations to search right discrete space relation.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.473-474
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• 2015

Halo merger trees are the essential backbone of semi-analytic models for galaxy formation and evolution. Srisawat et al. (2013) show that different tree building algorithms can build different halo merger histories from a numerical simulation for structure formation. In order to understand the differences induced by various tree building algorithms, we investigate the impact of halo merger trees on a semi-analytic model. We find that galaxy properties in our models show differences between trees when using a common parameter set. The models independently calibrated for each tree can reduce the discrepancies between global galaxy properties at z=0. Conversely, with regard to the evolutionary features of galaxies, the calibration slightly increases the differences between trees. Therefore, halo merger trees extracted from a common numerical simulation using different, but reliable, algorithms can result in different galaxy properties in the semi-analytic model. Considering the uncertainties in baryonic physics governing galaxy formation and evolution, however, these differences may not necessarily be significant.