Automatically generate high-quality unstructured meshes
Boundary Layer Meshing
Create boundary layers for CFD analysis
Refine meshes based on solution feedback
Create multi-billion node meshes using parallel processing
3D Image Data Processing
Convert voxelized image data into geometric models for meshing
The Simulation Modeling Suite is a set of C++ libraries that can be embedded into your application to provide robust, high quality, automatic mesh generation and other simulation modeling functionality.
The mesh generation capabilities work on general non-manifold geometries and include: surface and volume meshing, boundary layer meshing, extrusion meshing, higher order (curved) meshes and many other features. Adapting existing meshes is also fully supported, including moving and deforming bodies. All meshing functionality is fully automatic and also works in parallel.
Mesh generation maintains a direct interface to a wide variety of modeling kernels and CAD systems and also support discrete (mesh-based) geometry. This direct access ensures complete conformity of the mesh to the geometry.
Date: Thursday, October 15, 2020
Time: 1:30 PM EDT
Learn how SimModeler Crack can be used to perform accurate, automated 3D component-level fatigue crack growth predictions.
Come learn about how SimModeler Voxel can be used to transform microstructure representations created with Dream.3D into geometry and meshes suitable for simulations.
SimModeler is a full featured preprocessor built on top of the Simulation Modeling Suite. It streamlines the generation of analysis input decks for a variety of analysis packages starting from geometric data.
Starting with your CAD data, SimModeler allows you to prepare your model for simulation by removing unnecessary features, creating non-manifold geometry from assemblies, and augmenting with additional geometry. Discrete data can also be imported and prepared for simulation.
The built-in meshing functionality then allows you to easily create high quality meshes for your simulation.
SimModeler can be easily customized and extended to produce run-ready input for additional solvers.
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Mesh Generation Image: Model Courtesy Infolytica Corporation