The latest release of Caedium (v3.0) can now create and perform Computational Fluid Dynamics (CFD) simulations using hybrid models that mix faceted geometry (e.g., Google SketchUp models) with analytic geometry (e.g., CAD models). Also Caedium now has the option to use the Microsoft Windows Azure cloud service to perform CFD simulations.
The latest Caedium release also has other exciting new features:
- Import COLLADA (.dae) faceted geometry from Google SketchUp.
- Test experimental GPU acceleration using CUDA on NVIDIA hardware.
- Realize shorter startup times and improved overall performance with OpenFOAM® 2.0.x, especially on Windows with new MinGW-w64 compiler improvements.
- Use new selection filters to easily select geometry based on a wide range of constraints.
- Automate operations, such as export, during simulation updates using new telemetrics.
- Create detailed geometry, mesh, and physics reports using the new Info tool.
Powerful new topology-based operations in Caedium now provide a means to combine faceted geometry and analytic geometry into hybrid models for CFD simulations. Also the same topology toolset now allows non-manifold model creation so you can:
- Create a set of interconnected volumes each with 6 faces such that Caedium’s structured meshing algorithm can then generate high quality hexahedral elements, which is also known as multi-block meshing. Often hexahedral meshes provide improved accuracy over tetrahedral meshes.
- Assign different initial conditions to different volumes within a flow domain to speed up the convergence rate of a simulation.
- Create zero-thickness (or double sided) walls to avoid having to resolve extremely thin faces and wasting mesh elements.
Caedium provides two cloud-based options:
- Cloud Service – a direct Windows Azure service
- Cloud Burst Service – the ‘Burst to Azure’ service provided by Windows HPC Server 2008 R2 SP2
These innovative new services provide Caedium users with options to better optimize their designs by performing more CFD simulations unbounded by on-premises hardware limitations thanks to the elastic resource scaling of the cloud-based Azure service.
[submitted by Richard Smith, Symscape]