What's New in 2022.2
Watch our What’s New video:
Features & Functionalities:
Automatic preparation of FE-Verification with MSC Apex
Transfer of the Design Candidate’s boundary conditions and material information
The Transfer Design Candidate to Pre Processing button is now including even more functionality than the simple transfer of the geometry to the Pre Processing. There are two feasible workflows:
Nurbs Geometry: The Smooth Geometry is transferred to the Pre Processing and the Facet to Nurbs Tool is automatically executed with the chosen Density of the Nurbs Patches. When the transformation is completed, the Nurbs Geometry is intersected with the Design Space to receive the Nominal Geometry. Next, the new functionality is executed and the Loads & Boundary Conditions as well as the Material information are mapped to the Nominal Nurbs Geometry.
Facet Geometry: The Smooth Geometry is transferred to the Pre Processing and is intersected with the Design Space to receive the Nominal Geometry. Next, the new functionality is executed and the Loads & Boundary Conditions as well as the Material information are mapped to the Nominal Faceted Geometry.
The database is saved and closed in MSC Apex Generative Design.
Open Generative Design project in Apex to verify results
The MSC Apex Generative Design database can be directly opened in MSC Apex. A copy of the database for Apex is created and can be worked in. To run a linear static analysis the only workflow step necessary is to mesh the geometry and create the desired Scenario.
If other Loads and Boundary Conditions are intended for the verification, these can be added to the model and the corresponding analysis can be run.
Backend:
Development of SuperVoxel Phase 1
The algorithm is changed to include SuperVoxel. This change will happen in different phases and will be introduced over the next few releases. In phase 1, a performance enhancement of up to 30% is realised as well as a file size reduction during the optimisation. This enables users to calculate with higher complexity values even on GPUs with limited memory.
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