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Quality improvement methods for hexahedral element meshes adaptively generated using grid-based algorithm

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING 2012年第6期89卷 726-761页

作者： Sun, Lu Zhao, Guoqun Ma, Xinwu Shandong Univ Engn Res Ctr Mould & Die Technol Jinan 250061 Shandong Peoples R China Shandong Univ Minist Educ Key Lab Liquid Solid Struct Evolut & Proc Mat Jinan 250061 Shandong Peoples R China

The quality of finite element meshes is one of the key factors that affects the accuracy and reliability of numerical simulation results of many science and engineering problems. In order to solve the problem wherein the surface elements of the mesh generated by the grid-based method have poor quality, this paper studied mesh quality improvement methods, including node position smoothing and topological optimization. A curvature-based Laplacian scheme was used for smoothing of nodes on the C-edges, which combined the normal component with the tangential component of the Laplacian operator at the curved boundary. A projection-based Laplacian algorithm for smoothing the remaining boundary nodes was established. The deviation of the newly smoothed node from the practical surface of the solid model was solved. A node- and area-weighted combination method was proposed for smoothing of interior nodes. Five element-inserting modes, three element-collapsing modes and three mixed modes for topological optimization were newly established. The rules for harmonious application and conformity problem of each mode, especially the mixed mode, were provided. Finally, several examples were given to demonstrate the practicability and validity of the mesh quality improvement methods presented in this paper. Copyright (C) 2011 John Wiley & Sons, Ltd.

关键词： hexahedral element mesh refinement templates grid-based algorithm Laplacian smoothing topological optimization scaled Jacobian metric

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Energy efficient grid based k-means clustering algorithm for large scale wireless sensor networks

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INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS 2022年第14期35卷 e5255-e5255页

作者： Ben Gouissem, Bechir Gantassi, Rahma Hasnaoui, Salem Univ Tunis El Manar Natl Engn Sch Tunis Commun Syst Lab SysCom BP 37 Tunis 1002 Tunisia

Hierarchical based routing is a kind of group-based routing that consists in creating of a virtual hierarchy among network sensor nodes. This class of routing technique is generally designed for large-scale networks. It aims to efficiently increase network lifetime by cutting the whole network into clusters. However, traditional clustering techniques show some limitations and do not take into consideration the self-organized with dynamic topology inherent in wireless sensor networks (WSNs). These limitations can lead to an unbalanced cluster head distribution that affects the whole network energy consumption. In this paper, we propose a grid-based k-means clustering protocol (named GBK), which combines grid-based routing with k-means algorithm in order to overcome the above mentioned weaknesses. From the supervised zone area size parameter, the base station determines the optimal grid size based on our optimization study. Afterwards, the k-means algorithm is executed in every grid cell generating a cluster head per cell grid where the nearest node to the grid cell centroid is elected. An enhancement of this proposed GBK algorithm named GBK-R is also proposed to extend network stability of the GBK algorithm by node scoring calculation that take as parameters the node remaining energy in addition to the distance to centroid. Our proposed GBK and GBK-R algorithms allow for an enhanced network stability and increase the network lifetime as demonstrated by our performance evaluation study. In addition, this GBK clustering algorithm provides a better network topology control and a better control of the random nature of node distribution by generating cluster heads with bounded localization.

关键词： clustering algorithm energy efficient algorithm grid-based algorithm k-means algorithm large scale WSN machine learning

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An unsupervised grid-based approach for clustering analysis

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Science China(Information Sciences) 2010年第7期53卷 1345-1357页

作者： YUE ShiHong1, WANG JeenShing2, TAO Gao1 & WANG HuaXiang1 1School of Electrical Engineering and Automation, Tianjin Key Laboratory of Process Measurement and Control, Tianjin University, Tianjin 300072, China 2Department of Electrical Engineering, National Cheng Kung University, Tainan 701, China 1. School of Electrical Engineering and Automation Tianjin Key Laboratory of Process Measurement and Control Tianjin University Tianjin 300072 China2. Department of Electrical Engineering National Cheng Kung University Tainan 701 China

In recent years, the growing volume of data in numerous clustering tasks has greatly boosted the existing clustering algorithms in dealing with very large datasets. The K-means has been one of the most popular clustering algorithms because of its simplicity and easiness in application, but its effciency and effectiveness for large datasets are often unacceptable. In contrast to the K-means algorithm, most existing grid-clustering algorithms have linear time and space complexities and thus can perform well for large datasets. In this paper, we propose a grid-based partitional algorithm to overcome the drawbacks of the K-means clustering algorithm. This new algorithm is based on two major concepts: 1) maximizing the average density of a group of grids instead of minimizing the minimal square error which is applied in the K-means algorithm, and 2) using grid- clustering algorithms to thoroughly reformulate the object-driven assigning in the K-means algorithm into a new grid-driven assigning. Consequently, our proposed algorithm obtains an average speed-up about 10-100 times faster and produces better partitions than those by the K-means algorithm. Also, compared with the K-means algorithm, our proposed algorithm has ability to partition any dataset when the number of clusters is unknown. The effectiveness of our proposed algorithm has been demonstrated through successfully clustering datasets with different features in comparison with the other three typical clustering algorithms besides the K-means algorithm.

关键词： clustering grid-based algorithm K-means algorithm

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Evaluation of a sort-based matching algorithm for DDM 16

Evaluation of a sort-based matching algorithm for DDM

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16th Workshop on Parallel and Distributed Simulation

作者： Jun, Y Raczy, C Tan, G Natl Univ Singapore Sch Comp Singapore 119260 Singapore

ISBN: (纸本)0769516084

The High Level Architecture (HLA) provides several Data Distribution Management (DDM) services to reduce the transmission and reception of irrelevant data. These services rely on the computation of the intersection between "update" and "subscription" regions. As the brute force approach does not scale well, the current implementations of DDM usually use a grid partitioning of the routing space to efficiently compute the intersection. Since this approach still has some shortcomings, we have focused our recent research on the design and the evaluation of different intersection algorithms for the DDV. In this paper, we introduce a new intersection algorithm in which regions are sorted before computing the intersections. The strong points of this algorithm are (1) the sort suppresses many useless checks, (2) the algorithm allows many optimizations at the implementation level. An experimental comparison of this algorithm with brute force and grid-based approach provides additional information about the good points and weak points of each of the three approaches.

关键词： high level architecture runtime infrastructure data distribution management brute force algorithm grid-based algorithm sort-based algorithm

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Vertex Climax: Converting Geometry into a Non-nanifold Midsurface 16

Vertex Climax: Converting Geometry into a Non-nanifold Midsu...

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16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP) / 16th International Conference on Computer Graphics Theory and Applications (GRAPP)

作者： Schinko, Christoph Ullrich, Torsten Fraunhofer Austria Res GmbH Graz Austria Graz Univ Technol Graz Austria

ISBN: (纸本)9789897584886

The physical simulation of CAD models is usually performed using the finite elements method (FEM). If the input CAD model has one dimension that is significantly smaller than its other dimensions, it is possible to perform the physical simulation using thin shells only. While thin shells offer an enormous speed-up in any simulation, the conversion of an arbitrary CAD model into a thin shell representation is extremely difficult due to its non-uniqueness and its dependence on the simulation method used afterwards. The current state-of-the-art algorithms in conversion voxelize the input geometry and remove voxels based on matched, predefined local neighborhood configurations until only one layer of voxels remains. In this article we discuss a new approach that can extract a midsurface of a thin solid using a kernel-based approach: In contrast to other voxel-based thinning approaches, our algorithm applies a kernel onto a binary grid. In the resulting density field, opposing surface-voxels are iteratively moved towards each other until a thin representation is obtained.

关键词： Midsurface grid-based algorithm Volume Graphics Design Automation

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Layer Partition-based Matching algorithm of DDM

Layer Partition-based Matching Algorithm of DDM

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3rd International Conference on Computational Techniques and Artificial Intelligence(ICCTAI’2014)

作者： Nwe Nwe Myint Thein Nay Min Tun Thein University of Technology(Yatanarpon Cyber City) Computer University(Kyaing Tong)

High Level Architecture（HLA） is architecture for reuse and interoperation of *** HLA paradigm,the Runtime Infrastructure（RTI） provides a set of *** Distribution Management（DDM） service reduces message traffic over the *** aims to control and limit the data exchanged between federates during *** federate may inform the RTI about its intention to publish some data or it may subscribe to receive a subset of the published *** services are used to reduce the transmission and receiving of irrelevant data and aimed at reducing the communication over the *** services rely on the computation of the intersection between "update" and "subscription" *** calculating the intersection between update regions and subscription regions,the higher computation overhead can ***,there are several main DDM filtering *** paper proposes the layer partition-based matching algorithm for DDM in the HLA-based large-scale distributed *** new algorithm chooses the dynamic pivot based on regions distribution in the routing *** binary partition-based algorithm is fundamentally based on a divide and conquers *** algorithm always chooses the midpoint as the pivot point of routing *** approach promises low computational overhead,since it does not require unnecessary comparisons within regions in different *** proposed algorithm firstly calculates the regions ***,the partitioning among regions performs based on the result of choosing pivot based on region detection and defines the matching area that entirely covers all regions which need to match with regions at pivot *** proposed algorithm provides the more definite matching area between update region and subscription region during matching *** algorithm guarantees low computational overheads for matching process based on the overlapping degree between the regions and reduce the irrelevant m

关键词： HLA DDM Region-based algorithm grid-based algorithm Sort-based algorithm Binary Partition-based algorithm Layer Partition-based algorithm

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Evaluation of a sort-based matching algorithm for DDM 02

Evaluation of a sort-based matching algorithm for DDM

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Proceedings of the sixteenth workshop on Parallel and distributed simulation

作者： Yu Jun Come Raczy Gary Tan National University of Singapore Singapore

ISBN: (纸本)9780769516080

The High Level Architecture (HLA) provides several Data Distribution Management (DDM) services to reduce the transmission and reception of irrelevant data. These services rely on the computation of the intersection between "update" and "subscription" regions. As the brute force approach does not scale well, the current implementations of DDM usually use a grid partitioning of the routing space to efficiently compute the intersection. Since this approach still has some shortcomings, we have focused our recent research on the design and the evaluation of different intersection algorithms for the *** this paper, we introduce a new intersection algorithm in which regions are sorted before computing the intersections. The strong points of this algorithm are (1) the sort suppresses many useless checks, (2) the algorithm allows many optimizations at the implementation level. An experimental comparison of this algorithm with brute force and grid-based approach provides additional information about the good points and weak points of each of the three approaches.

关键词： runtime infrastructure data distribution management grid-based algorithm sort-based algorithm brute force algorithm high level architecture

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