Hexahedral Mesh Generation for the Simulation of the Human Mandible (original) (raw)
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A Case Study in Hexahedral Mesh Generation: Simulation of the Human Mandible
Engineering With Computers, 2001
We provide a case study for the generation of pure hexahedral meshes for the numerical simulation of physiological stress scenarios of the human mandible. Due to its complex and very detailed free-form geometry, the mandible model is very demanding. This test case is used as a running example to demonstrate the applicability of a combinatorial approach for the generation of hexahedral meshes by means of successive dual cycle eliminations, which has been proposed by the second author in previous work. We report on the progress and recent advances of the cycle elimination scheme. The given input data, a surface triangulation obtained from computed tomography data, requires a substantial mesh reduction and a suitable conversion into a quadrilateral surface mesh as a first step, for which we use mesh clustering and b-matching techniques. Several strategies for improved cycle elimination orders are proposed. They lead to a significant reduction in the mesh size and a better structural quality. Based on the resulting combinatorial meshes, gradient-based optimized smoothing with the condition number of the Jacobian matrix as objective together with mesh untangling techniques yielded embeddings of a satisfactory quality. To test our hexahedral meshes for the mandible model within an FEM simulation we used the scenario of a bite on a 'hard nut.' Our simulation results are in good agreement with observations from biomechanical experiments.
Development of Octree-Based High-Quality Mesh Generation Method for Biomedical Simulation
Lecture Notes in Computer Science, 2018
This paper proposes a robust high-quality finite element mesh generation method which is capable of modeling problems with complex geometries and multiple materials and suitable for the use in biomedical simulation. The previous octree-based method can generate a high-quality mesh with complex geometries and multiple materials robustly allowing geometric approximation. In this study, a robust mesh optimization method is developed combining smoothing and topology optimization in order to correct geometries guaranteeing element quality. Through performance measurement using sphere mesh and application to HTO tibia mesh, the validity of the developed mesh optimization method is checked.
Improved Hexahedral Meshing on Biological Models
2004
Certain applications of the finite element method require hexahedral meshes for the underlying discretization. A procedure, known as THexing, which is guaranteed to produce an all-hex mesh is to begin with a tetrahedral mesh and then subdivide each element into four hexahedra. This research presents a method for improving the THex approach, known as Diced THexing, or DTHexing. The DTHex approach is based on general coarsening tools. An initial triangle surface mesh is coarsened and smoothed iteratively until a coarse mesh of reasonable quality is obtained. The volume is then easily meshed using a tetrahedral scheme, then refined using 'h' type modifications. The goal of this method is to 1) improve the quality of elements in the finite element mesh and 2) decrease the number of overall nodes. The DTHex approach has been successful at improving models on biological meshes without increasing node count. This research was conducted using the CUBIT software.
High-Quality Multi-tissue Mesh Generation for Finite Element Analysis
Springer eBooks, 2013
Mesh generation on 3D segmented images is a fundamental step for the construction of realistic biomechanical models. Mesh elements with low or large dihedral angles are undesirable, since they are known to underpin the speed and accuracy of the subsequent finite element analysis. In this paper, we present an algorithm for meshing 3D multi-label images. A notable feature of our method is its ability to produce tetrahedra with very good dihedral angles respecting, at the same time, the interfaces created by two or more adjoining tissues. Our method employs a Delaunay refinement scheme orchestrated by special point rejection strategies which remove poorly shaped elements without deteriorating the representation of the objects' anatomical boundaries. Experimental evaluation on CT and MRI atlases have shown that our algorithm produces watertight meshes consisting of elements of very good quality (all the dihedral angles were between 19 and 150 degrees) which makes our method suitable for finite element simulations.
Unstructured mesh generation from the Virtual Family models for whole body biomedical simulations
Procedia Computer Science, 2010
Physiological systems are inherently complex, involving multi-physics phenomena at a multitude of spatial and temporal scales. To realistically simulate their functions, detailed high quality multi-resolution often patient specific human models are required. Mesh generation has remained a central topic in finite element analysis (FEA) for a few decades now. Recent developments in high performance computing (HPC) driven by the need for multi-physics multiscale simulations of physiological systems define new challenges in this area. Even though many algorithms have been developed over years and are offered as commercial packages, they are often limited to mechanical engineering applications only. Mesh generation for human anatomical domains requires more effective and flexible techniques to tackle their greater geometrical and topological complexities. We present, evaluate and discuss several methods to generate unstructured body fitted multi-domain adaptive meshes with geometrically and topologically compatible interfaces from the segmented cross-sections of the Virtual Family models for the purpose of large scale whole body simulations. We found that an automated solution is difficult to achieve with real-image qualities, but if optimal methods are selected, good results can be achieved with minimal user-interactions. Therefore we believe that our observations can serve as guidance when choosing an optimal method for a specific application.
Hexahedral mesh generation for biomedical models in SCIRun
Engineering with Computers, 2008
Biomedical simulations are often dependent on numerical approximation methods, including finite element, finite difference, and finite volume methods, to model the varied phenomena of interest. An important requirement of the numerical approximation methods above is the need to create a discrete decomposition of the model geometry into a mesh. Historically, the generation of these meshes has been a critical bottleneck in efforts to efficiently generate biomedical simulations which can be utilized in understanding, planning, and diagnosing biomedical conditions. In this paper we discuss a methodology for generating hexahedral meshes for biomedical models using an algorithm implemented in the SCIRun Problem Solving Environment. The method is flexible and can be utilized to build up conformal hexahedral meshes ranging from models defined by single isosurfaces to more complex geometries with multi-surface boundaries.
Exacta, 2008
In this work, a software package based on the Delaunay’s algorithm is described. The main feature of this package is the capability in applying discretization in geometric domains of teeth taking into account their complex inner structures and the materials with different hardness. Usually, the mesh generators reported in literature treat molars and other teeth by using simplified geometric models, or even considering the teeth as homogeneous structures.
Shelling Hexahedral Complexes for Mesh Generation
Journal of Graph Algorithms and Applications, 2001
We present a new approach for the generation of hexahedral finite element meshes for solid bodies in computer-aided design. The key idea is to use a purely combinatorial method, namely a shelling process, to decompose a topological ball with a prescribed surface mesh into combinatorial cubes, so-called hexahedra. The shelling corresponds to a series of graph transformations on the surface mesh which is guided by the cycle structure of the combinatorial dual. Our method transforms the graph of the surface mesh iteratively by changing the dual cycle structure until we get the surface mesh of a single hexahedron. Starting with a single hexahedron and reversing the order of the graph transformations, each transformation step can be interpreted as adding one or more hexahedra to the so far created hex complex. Given an arbitrary solid body, we first decompose it into simpler subdomains equivalent to topological balls by adding virtual 2-manifolds. Second, we determine a compatible quadrilateral surface mesh for all created subdomains. Then, in the main part we can use the shelling of topological balls to build up a hex complex for each subdomain independently. Finally, the combinatorial mesh(es) are embedded into the given solids and smoothed to improve quality.