• Interaction and multiscale mechanics
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• v.2 no.3
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• pp.277-293
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• 2009

The Enriched Free Mesh Method (EFMM) is a patch-wise procedure in which both a displacement field on an element and a stress/strain field on a cluster of elements connected to a node can be defined. On the other hand, the Superconvergent Patch Recovery (SPR) is known to be an efficient post-processing procedure of the finite element method to estimate the error norm at a node. In this paper, we discuss the relationship between solutions of the EFMM and those of the SPR through several convergence studies. In addition, in order to solve the demerit of the smoothing effect on the fracture mechanics fields, we implement a singular stress field to a local patch in the EFMM, and its effectiveness is investigated.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1998.03a
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• pp.246-249
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• 1998

In the present study, domain decomposition using the substructuring method is developed for the computational efficiency of the finite element analysis of metal forming processes. In order to avoid calculation of an inverse matrix during the substructuring procedure, the modified Cholesky decomposition method is implemented. As obtaining the data independence by the substructuring method, the program is easily parallelized using the Parallel Virtual Machine(PVM) library on a workstation cluster connected on networks. A numerical example for a simple upsetting is calculated and the speed-up ratio with respect to various domain decompositions and number of processors. Comparing the results, it is concluded that the improvement of performance is obtained through the proposed method.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.497-508
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• 2005

This paper aims at studying on K-means Clustering focusing on initialization which affect the clustering results in K-means cluster analysis. The four different methods(the MA method, the KA method, the Max-Min method and the Space Partition method) were compared and the clustering result shows that there were some differences among these methods, especially that the MA method sometimes leads to incorrect clustering due to the inappropriate initialization depending on the types of data and the Max-Min method is shown to be more effective than other methods especially when the data size is large.

• Journal of Information Processing Systems
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• v.17 no.1
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• pp.163-177
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• 2021

Many methods of discovering social networking communities or clustering of features are based on the network structure or the content network. This paper proposes a community discovery method based on topic models using a time factor and an unsupervised clustering method. Online community discovery enables organizations and businesses to thoroughly understand the trend in users' interests in their products and services. In addition, an insight into customer experience on social networks is a tremendous competitive advantage in this era of ecommerce and Internet development. The objective of this work is to find clusters (communities) such that each cluster's nodes contain topics and individuals having similarities in the attribute space. In terms of social media analytics, the method seeks communities whose members have similar features. The method is experimented with and evaluated using a Vietnamese corpus of comments and messages collected on social networks and ecommerce sites in various sectors from 2016 to 2019. The experimental results demonstrate the effectiveness of the proposed method over other methods.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.1
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• pp.72-78
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• 1993

While the rules for an expert system are obtained through the interviewing with domain experts or by designer's own experience, these are not adequate for fuzzy controllers dealing quantitative control values. In this paper, by considering a state of the controlled system as a pattern, we propose a method to obtain the control rules by a statistical method. Namely, we propose a method to obtain the control rules by a statistical method. Namely, we propose an rule acquisition method that is objective, mechanical, and inductive inference using a cluster-seeking algorithm, or K-means clustering algorithm. To validate this study, we show an example of an IRIS control in a CAMCODER and analyse the rules acquired from 98 sample patterns consisting of 45 features.

• Transactions of Materials Processing
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• v.7 no.5
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• pp.474-480
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• 1998

In the present study a domain decomposition scheme using the substructuring method is developed for the computational efficiency of the finite element analysis of metal forming processes. in order to avoid calculation of an inverse matrix during the substructuring procedure, the modified Cholesky decomposition method is implemented. As obtaining the data independence by the substructuring method the program is easily paralleized using the Parallel Virtual machine(PVM) library on a work-station cluster connected on networks. A numerical example for a simple upsetting is calculated and the speed-up ratio with respect to various number of subdomains and number of processors. The efficiency of the parallel computation is discussed by comparing the results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.7 s.262
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• pp.739-746
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• 2007

Recently, models in STL files are widely used in reverse engineering processes, CAD systems and analysis systems. However the models have poor geometric quality and include only triangles, so the models are not suitable for the finite element analysis. This paper presents a general method that generates finite element mesh from STL file models. Given triangular meshes, the method estimates triangles and makes clusters which consist of triangles. The clusters are merged by some geometric indices. After merging clusters, the method applies plane meshing algorithm, based on domain decomposition method, to each cluster and then the result plane mesh is projected into the original triangular set. Because the algorithm uses general methods to generate plane mesh, we can obtain both tri and quad meshes unlike previous researches. Some mechanical part models are used to show the validity of the proposed method.

• Journal of computational fluids engineering
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• v.12 no.3
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• pp.20-28
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• 2007

A fast and robust method of grid generation to multiple functions has been developed for flow analysis in three dimensional space. It is based on the Non-Uniform Rational B-Spline(NURBS) of an approximation method. Many of NURBS intrinsic properties are introduced and much more easily understood. The grid generation method, details of numerical implementation. examples of application, and potential extensions of the current method are illustrated in this paper. The object of this study is to develop the surface grid generation and the grid cluster techniques capable of resolving complex flows with shock waves, expansion waves, shear layers. The knot insert method of Non-Uniform Rational B-Spline seems well worked. In addition, NURBS has been widely utilized to generate grids in the computational fluid dynamics community. Computational examples associated with practical configurations have shown the utilization of the algorithm.

• Journal of information and communication convergence engineering
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• v.15 no.1
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• pp.49-52
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• 2017

Ganglion cysts are benign soft tissues usually encountered in the wrist. In this paper, we propose a method to extract a ganglion cyst region from ultrasonography images by using image segmentation. The proposed method using the possibilistic c-means (PCM) clustering method is applicable to ganglion cyst extraction. The methods considered in this thesis are fuzzy stretching, median filter, PCM clustering, and connected component labeling. Fuzzy stretching performs well on ultrasonography images and improves the original image. Median filter reduces the speckle noise without decreasing the image sharpness. PCM clustering is used for categorizing pixels into the given cluster centers. Connected component labeling is used for labeling the objects in an image and extracting the cyst region. Further, PCM clustering is more robust in the case of noisy data, and the proposed method can extract a ganglion cyst area with an accuracy of 80% (16 out of 20 images).

• Nuclear Engineering and Technology
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• v.52 no.3
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• pp.477-484
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• 2020

The control rod drive mechanism needs to be debugged after reactor fresh fuel loading. It is of great importance to monitor the subcriticality of this process accurately. A modified method was applied to the subcriticality monitoring process, in which only a single control rod cluster was fully withdrawn from the core. In order to correct the error in the results obtained by Neutron Source Multiplication Method, which is based on one point reactor model, Monte Carlo neutron transport code was employed to calculate the fission neutron distribution, the iterated fission probability and the neutron flux in the neutron detector. This article analyzed the effect of a coarse mesh and a fine mesh to tally fission neutron distributions, the iterated fission probability distributions and to calculate correction factors. The subcriticality before and after modification is compared with the subcriticality calculated by MCNP code. The modified results turn out to be closer to calculation. It's feasible to implement the modified NSM method in large local reactivity addition process using Monte Carlo code based on 3D model.