Anisotropic Volume Mesh Generation Controlled by Adaptive Metric Space

Author(s):  
Barbara Głut ◽  
Tomasz Jurczyk ◽  
Jacek Kitowski
Author(s):  
Kumar Srinivasan ◽  
Z. J. Wang ◽  
Wei Yuan ◽  
Richard Sun

CFD simulation of vehicle under-hood and under-body poses several challenges. Specifically, the complexity of the geometry involved makes the use of traditional mesh generation approaches, based on the boundary-to-interior methodology, impractical and time consuming. The current work presents the use of an interior-to-boundary method wherein the need for creating a ‘water-tight’ surface mesh is not a pre-requisite for volume mesh generation. The application of the new method is demonstrated for an actual passenger vehicle under-hood model with nearly a hundred components. Coupled radiation/convection simulations are performed to obtain the complete airflow and thermal map of the engine compartment. Results are validated with test data. The new method results in significant gains in efficiency over traditional approaches allowing the simulation tool to be used effectively in the vehicle development process.


Author(s):  
Yasushi Ito ◽  
Mitsuhiro Murayama ◽  
Kazuomi Yamamoto ◽  
Alan Shih ◽  
Bharat Soni

2005 ◽  
Vol 5 (4) ◽  
pp. 283-290 ◽  
Author(s):  
James Qingyang Zhang ◽  
John M. Sullivan ◽  
Hamid Ghadyani ◽  
Donna M. Meyer

An accurate three-dimensional (3D) mesh of biological models is fundamental for analysis and treatment simulations. Generally noninvasive magnetic resonance image (MRI) data are taken as the input for the simulation. The topologic relationship of anatomy is extracted from MR images through segmentation processes. To accelerate the biological modeling phase, template surface and volume meshes are generated based on MR images and∕or anatomical atlases (e.g., brain atlas, etc.). The boundary surfaces are extracted from segmented regions on the image slices, which are used as the input for 3D volume mesh generation. An intuitive graphic user interface was developed for biomedical applications. It integrated MRI data manipulation with surface mesh and volume mesh generators. Image volume and mesh geometries are registered in the MRI working space. As the core component of the system, a robust 3D mesh generation approach is presented. It is capable of describing irregular geometries exhibiting concave and convex surfaces. It uses deltahedral building blocks for volume mesh generation and creates high-quality, regular-shaped tetrahedral mesh elements. The approach supports multiple levels of localized refinement without reducing the overall mesh quality. The validity of this new mesh generation strategy and implementation is demonstrated via the medical applications in brain vasculature modeling, multimodality imaging for breast cancer detection, and numerous anatomically accurate models presented. Multiple material boundaries are preserved in each mesh with fidelity.


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