No De-featuring or Simplification of CAD Geometries

Engineers spend a lot of time preparing CAD models for CFD. Weeks can be spent transferring a CAD file, simplifying the geometry, meshing the design and creating the fluid domain.

The Sub-Grid Geometry Resolution (SGGR) technology allows FlowVision to import the CAD file to the computational domain without any feature loss, thus both saving man hour and letting the engineer focus on the physics of the problem to be solved. SGGR technology allows preserving the curvilinear boundaries of the imported CAD geometry, even if the smallest cell size used in the calculation is not capable of resolving the curvature.

Combined with the locally adapted grid generation, importing a geometry and generating a high quality computational grid (mesh) in FlowVision takes a few minutes.

sggr_vv

 

Car_Tire_AquaHigh-Fidelity Tire Aquaplaning Studies.

Human Heart FSI FlowVision-Abaqus Cosimulation

Effect of SGGR on Other Capabilities

The unique SGGR technology enhances the fluid-body interface resolution capacity. Thanks to this; a smooth, lossless data transfer between Finite Element Analysis (FEA) tools and FlowVision can be established, paving the way to the ultimate accuracy for Fluid Structure Interaction (FSI). Through these sub-micron level resolution and strictly conservative data exchange capabilities, the state of art FSI calculations such as simulation of a beating human heart can be fulfilled.

Likewise, for Volume of Fluid (VOF) calculations SGGR helps to resolve and reconstruct the free surface topology even at a sub-grid level.

SGGR does not only allow seamless working of locally adapted Cartesian grid; together with unique FlowVision Gap Model and features such as user defined auto-offsetting, it also provides highly accurate solutions for calculations where hundreds of different parts are closely situated (e.g. micron level gaps in a cell phone cooling simulation).

Moreover, the CAD geometries can be replaced during the course of calculation without any manual grid regeneration efforts. Upon a geometry replacement, FlowVision strictly maintains the originally obtained mesh quality. This novel capability of offers a time-effective approach for optimization studies. Additionally, for multi-domain nonlinear automatized optimization, FlowVision can be coupled with 3rd party optimization tools such as IOSO.