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Kenji Shimada - One of the best experts on this subject based on the ideXlab platform.

  • fully automated hex dominant mesh generation with directionality control via packing rectangular solid cells
    International Journal for Numerical Methods in Engineering, 2003
    Co-Authors: Soji Yamakawa, Kenji Shimada
    Abstract:

    A new fully automatic hex-dominant mesh generation technique of an arbitrary 3D geometric domain is presented herein. The proposed Method generates a high-quality hex-dominant mesh by: (1) controlling the directionality of the output hex-dominant mesh; and (2) avoiding ill-shaped elements induced by nodes located too closely to each other. The proposed Method takes a 3D geometric domain as input and creates a hex-dominant mesh consisting mostly of hexahedral elements, with additional prism and tetrahedral elements. Rectangular solid cells are packed on the boundary of and inside the input domain to obtain ideal node locations for a hex-dominant mesh. Each cell has a potential energy field that mimics a body-centred cubic (BCC) structure (seen in natural substances such as NaCl) and the cells are moved to stable positions by a physically based simulation. The simulation mimics the formation of a crystal pattern so that the centres of the cells provide ideal node locations for a hex-dominant mesh. Via the Advancing Front Method, the centres of the packed cells are then connected to form a tetrahedral mesh, and this is converted to a hex-dominant mesh by merging some of the tetrahedrons. Copyright © 2003 John Wiley & Sons, Ltd.

  • hex dominant mesh generation with directionality control via packing rectangular solid cells
    Geometric Modeling and Processing, 2002
    Co-Authors: Soji Yamakawa, Kenji Shimada
    Abstract:

    A new computational Method that creates a hex-dominant mesh of an arbitrary 3D geometric domain is presented. The proposed Method generates a high-quality hex-dominant mesh by: (1) controlling the directionality of the output hex-dominant mesh; and (2) avoiding ill-shaped elements induced by nodes located too closely to each other. The proposed Method takes a 3D geometric domain as input and creates a hex-dominant mesh that consists of mostly hexahedral elements with additional prism elements and tetrahedral elements. The proposed Method packs rectangular solid cells on the boundary of and inside the input domain to obtain ideal node locations for a hex-dominant mesh. Each cell has a potential energy field that mimics a body centered cubic (BCC) structure, and the cells are moved to stable positions by a physically-based simulation. The simulation mimics the formation of a crystal pattern so that the centers of the cells give ideal node locations for a hex-dominant mesh. The domain is then meshed into a tetrahedral mesh by the Advancing Front Method, and finally the tetrahedral mesh is converted to a hex-dominant mesh by merging some tetrahedrons.

  • high quality anisotropic tetrahedral mesh generation via ellipsoidal bubble packing
    IMR, 2000
    Co-Authors: Soji Yamakawa, Kenji Shimada
    Abstract:

    This paper presents a new computational Method for anisotropic tetrahedral meshing that (1) can control shapes of the elements by an arbitrary anisotropy function, and (2) can avoid ill-shaped elements induced from poorly distributed node locations. Our Method creates a tetrahedral mesh in two steps. First our Method obtains node locations through a physically based particle simulation, which we call 'bubble packing.' Ellipsoidal bubbles are closely packed on the boundary and inside a geometric domain, and nodes are placed at the centers of the bubbles. Our Method then connects the nodes to create a tet mesh by the Advancing Front Method. Experimental results show that our Method can create a high quality anisotropic tetrahedral mesh that conforms well to the input anisotropy.

Barry Hilary Valentine Topping - One of the best experts on this subject based on the ideXlab platform.

  • a new element bisection algorithm for unstructured adaptive tetrahedral mesh generation
    Engineering Computations, 1998
    Co-Authors: J K Wilson, Barry Hilary Valentine Topping
    Abstract:

    A new h‐refinement adaptive tetrahedral mesh generation algorithm is presented. Three‐dimensional domains, to be analysed by the finite element Method, are initially modelled by a coarse background mesh of tetrahedral elements. This mesh forms the input for finite element analysis and error estimation by the Zienkiewicz‐Zhu simple error estimator. Adaptive mesh refinement proceeds by selecting an element for remeshing whose longest edge is shared by elements that also require refinement. This group of elements is refined by inserting a new node at the mid‐point of the shared edge thereby bisecting all elements within the group. Adaptive parameters are calculated for the new node and elements. Refinement then proceeds until no further group of elements can be found for refinement or no elements within the current mesh require further refinement. The shape quality of the current mesh is then enhanced by the iterative application of nodal relaxation plus three topological transformations. The entire refinement process is repeated iteratively until the required degree of mesh refinement is reached. Ten‐noded linear strain tetrahedral finite element meshes have been used for the finite element and error estimation analyses. Four examples of adaptive tetrahedral mesh generation for linear elastic stress/displacement analysis are presented which show that this algorithm is robust and efficient in terms of reduction of the domain error with a minimum number of degrees of freedom being generated, number of iterations, and therefore finite element analyses, required and computational time for refinement when compared to the Advancing Front Method and Delaunay triangulation.

  • Parallel adaptive tetrahedral mesh generation by the Advancing Front technique
    Computers & Structures, 1998
    Co-Authors: J. I. B. Wilson, Barry Hilary Valentine Topping
    Abstract:

    Abstract A parallel adaptive tetrahedral mesh generation program using the Advancing Front Method is described. The problem domain is initially defined by a course background mesh of tetrahedral elements which forms the input for finite element analysis and from which adaptive parameters are calculated. Parallel adaptive mesh generation is then carried out by dividing the background mesh into subdomains and refining each subdomain concurrently using the nodal parameters previously calculated and undertaken by the Advancing Front Method.

Soji Yamakawa - One of the best experts on this subject based on the ideXlab platform.

  • fully automated hex dominant mesh generation with directionality control via packing rectangular solid cells
    International Journal for Numerical Methods in Engineering, 2003
    Co-Authors: Soji Yamakawa, Kenji Shimada
    Abstract:

    A new fully automatic hex-dominant mesh generation technique of an arbitrary 3D geometric domain is presented herein. The proposed Method generates a high-quality hex-dominant mesh by: (1) controlling the directionality of the output hex-dominant mesh; and (2) avoiding ill-shaped elements induced by nodes located too closely to each other. The proposed Method takes a 3D geometric domain as input and creates a hex-dominant mesh consisting mostly of hexahedral elements, with additional prism and tetrahedral elements. Rectangular solid cells are packed on the boundary of and inside the input domain to obtain ideal node locations for a hex-dominant mesh. Each cell has a potential energy field that mimics a body-centred cubic (BCC) structure (seen in natural substances such as NaCl) and the cells are moved to stable positions by a physically based simulation. The simulation mimics the formation of a crystal pattern so that the centres of the cells provide ideal node locations for a hex-dominant mesh. Via the Advancing Front Method, the centres of the packed cells are then connected to form a tetrahedral mesh, and this is converted to a hex-dominant mesh by merging some of the tetrahedrons. Copyright © 2003 John Wiley & Sons, Ltd.

  • hex dominant mesh generation with directionality control via packing rectangular solid cells
    Geometric Modeling and Processing, 2002
    Co-Authors: Soji Yamakawa, Kenji Shimada
    Abstract:

    A new computational Method that creates a hex-dominant mesh of an arbitrary 3D geometric domain is presented. The proposed Method generates a high-quality hex-dominant mesh by: (1) controlling the directionality of the output hex-dominant mesh; and (2) avoiding ill-shaped elements induced by nodes located too closely to each other. The proposed Method takes a 3D geometric domain as input and creates a hex-dominant mesh that consists of mostly hexahedral elements with additional prism elements and tetrahedral elements. The proposed Method packs rectangular solid cells on the boundary of and inside the input domain to obtain ideal node locations for a hex-dominant mesh. Each cell has a potential energy field that mimics a body centered cubic (BCC) structure, and the cells are moved to stable positions by a physically-based simulation. The simulation mimics the formation of a crystal pattern so that the centers of the cells give ideal node locations for a hex-dominant mesh. The domain is then meshed into a tetrahedral mesh by the Advancing Front Method, and finally the tetrahedral mesh is converted to a hex-dominant mesh by merging some tetrahedrons.

  • high quality anisotropic tetrahedral mesh generation via ellipsoidal bubble packing
    IMR, 2000
    Co-Authors: Soji Yamakawa, Kenji Shimada
    Abstract:

    This paper presents a new computational Method for anisotropic tetrahedral meshing that (1) can control shapes of the elements by an arbitrary anisotropy function, and (2) can avoid ill-shaped elements induced from poorly distributed node locations. Our Method creates a tetrahedral mesh in two steps. First our Method obtains node locations through a physically based particle simulation, which we call 'bubble packing.' Ellipsoidal bubbles are closely packed on the boundary and inside a geometric domain, and nodes are placed at the centers of the bubbles. Our Method then connects the nodes to create a tet mesh by the Advancing Front Method. Experimental results show that our Method can create a high quality anisotropic tetrahedral mesh that conforms well to the input anisotropy.

Dai Xing - One of the best experts on this subject based on the ideXlab platform.

Yasushi Ito - One of the best experts on this subject based on the ideXlab platform.

  • References
    2015
    Co-Authors: Yasushi Ito, Alan M Shih, Bharat K Soni
    Abstract:

    An efficient and robust unstructured mesh generator, Mixed-Element Grid Generator in 3 Dimensions (MEG-G3D), has been developed [-]. MEGG3D has five key components: (1) a direct Advancing Front Method for sur-face triangulation based on discrete surface models [,]; (2) a decimation Method for triangular meshes with quality enhancement Methods [] (Figure 1a); (3) an ad-vancing Front Method for isotropic tetrahedral mesh gen-eration []; (4) a multiple marching direction Method for semi-structured near-field mesh generation []; (5) an octree-based unstructured hexahedral mesh generation Method with a new set of refinement templates [] (Fig-ure 1b). MEGG3D is previously known as EdgeEditor and has been demonstrated part of its capability for gen

  • parallel unstructured mesh generation by an Advancing Front Method
    Mathematics and Computers in Simulation, 2007
    Co-Authors: Yasushi Ito, Alan M Shih, Bharat K Soni, Andrey N Chernikov, Nikos Chrisochoides, Anil K Erukala, Kazuhiro Nakahashi
    Abstract:

    Mesh generation is a critical step in high fidelity computational simulations. High-quality and high-density meshes are required to accurately capture the complex physical phenomena. A robust approach for a parallel framework has been developed to generate large-scale meshes in a short period of time. A coarse tetrahedral mesh is generated first to provide the basis of block interfaces and then is partitioned into a number of sub-domains using METIS partitioning algorithms. A volume mesh is generated on each sub-domain in parallel using an Advancing Front Method. Dynamic load balancing is achieved by evenly distributing work among the processors. All the sub-domains are combined to create a single volume mesh. The combined volume mesh can be smoothed to remove the artifacts in the interfaces between sub-domains. A void region is defined inside each sub-domain to reduce the data points during the smoothing operation. The scalability of the parallel mesh generation is evaluated to quantify the improvement on shared- and distributed-memory computer systems.

  • unstructured mesh generation using megg3d mixed element grid generator in three dimensions
    2007
    Co-Authors: Yasushi Ito, Alan M Shih, Bharat K Soni
    Abstract:

    An efficient and robust unstructured mesh generator, Mixed-Element Grid Generator in 3 Dimensions (MEGG3D), has been developed [-]. MEGG3D has five key components: (1) a direct Advancing Front Method for surface triangulation based on discrete surface models [, ]; (2) a decimation Method for triangular meshes with quality enhancement Methods [] (Figure 1a); (3) an Advancing Front Method for isotropic tetrahedral mesh generation []; (4) a multiple marching direction Method for semi-structured near-field mesh generation []; (5) an octree-based unstructured hexahedral mesh generation Method with a new set of refinement templates [] (Figure 1b). MEGG3D is previously known as EdgeEditor and has been demonstrated part of its capability for generating meshes for complex geometries. In this paper, we will summarize the current capability of MEGG3D and show variety of meshes for complex geometries.

  • reliable isotropic tetrahedral mesh generation based on an Advancing Front Method
    IMR, 2004
    Co-Authors: Yasushi Ito, Alan M Shih, Bharat K Soni
    Abstract:

    In this paper, we propose a robust isotropic tetrahedral mesh generation Method. An Advancing Front Method is employed to control local mesh density and to easily preserve the original connectivity of boundary surfaces. Tetrahedra are created by each layer. Instead of preparing a background mesh for mesh spacing control, this information is estimated at the beginning of each layer at each node from the area of connecting triangles on the Front and a user-specified stretching factor. An alternating digital tree (ADT) is prepared to correct the mesh spacing information and to perform geometric search efficiently. At the end of the mesh generation process, angle-based smoothing and Delaunay refinement are employed to enhance the resulting mesh quality. Surface meshes are prepared beforehand using a direct Advancing Front Method for discrete surfaces extracted from computed tomography (CT) or magnetic resonance imaging (MRI) data. The algorithm is demonstrated with several biomedical models.

  • some challenges of realistic flow simulations by unstructured grid cfd
    International Journal for Numerical Methods in Fluids, 2003
    Co-Authors: Kazuhiro Nakahashi, Yasushi Ito, Fumiya Togashi
    Abstract:

    We discuss the unstructured grid Method to compute flows around geometrically complex bodies having relative motions. To enhance the capability to treat complex geometries, a surface triangulation Method using the Advancing Front Method coupled with geometric feature extraction technique is described. Stereolithography (STL) data are adopted as an interface between a CAD system and the surface grid generator. Moving bodies are treated by the overset unstructured grid Method. The capability of the Method is demonstrated for simulations of an airplane separation process from a rocket booster and a hornet in flight. In the hornet simulation, the detailed components such as antennas, legs and a sting are all included in the computational grid. The flapping wings are treated by the overset unstructured grid Method where a grid around the wing is overlapped on a stationary grid around the body of a hornet and moves with time to simulate the flapping motion