polyhedral meshes
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2021 ◽  
Author(s):  
Paula C Sanematsu

The development of physics-based 3D models that investigate the behavior of biological tissues requires effective and efficient visualization tools. The open-source software ParaView has such capabilities, but often impose a steep learning curve due to the use of the Visualization Toolkit (VTK) data structures. To overcome this, I show how to setup the components of 3D vertex-like models, i.e., vertices, faces, and polyhedra, into the VTK data format and then output as ParaView unstructured grid files. I present a few relevant tools to visualize and analyze the files in ParaView. All sample codes are available in the Github repository vis3Dvertex.


2021 ◽  
Vol 40 (5) ◽  
pp. 217-230
Author(s):  
A. Bunge ◽  
M. Botsch ◽  
M. Alexa
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2021 ◽  
pp. 1420326X2110276
Author(s):  
Haofu Chen ◽  
Xiaoqing Zhou ◽  
Zhuangbo Feng ◽  
Shi-Jie Cao

Computational fluid dynamics (CFD) has been proven to be a versatile tool for indoor environment simulations. The discretization of computational domain (mesh generation) determines the reliability of CFD simulation and computational cost. For cases with complex/irregular geometries, the widely utilized tetrahedral meshes have critical limitations, including low accuracy, considerate grid number and computing cost. To overcome these disadvantages, the current research developed a polyhedral meshes based meshing strategy for indoor environment simulations. This study applied tetrahedral, hexahedral and polyhedral meshes for evaluating indoor environment cases developed from previous studies. Simulation accuracy, computing time and physical storage of different mesh types were compared. The results show that the polyhedral meshes could save almost 95% of computing time without sacrificing model accuracy, compared with the other two mesh types with the approximately same grid numbers. Due to its large mesh information, the polyhedral meshes occupied the most physical memory. Overall, the polyhedral meshes based meshing strategy produced a superior performance (model accuracy and computing time) for indoor environment simulations and shows a great potential in engineering applications.


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