Release
PreonLab 4.2 Released

May 28, 2020

We are excited to announce the release of PreonLab 4.2 – the answer to life, the universe and everything! It also contains many new or improved features that will help you to find answers to your more specific CFD-related questions:

  • Mesh-based height sensor: The new sensor measures the height of fluid (or snow) above surfaces.
  • Improved user interface: With updates to the connection editor, the scene inspector and the on-screen display, PreonLab 4.2 looks and feels better than ever.
  • Optimized local refinement: Better performance and the introduction of user-defined domain shapes facilitate the acceleration of even more applications with local refinement.
  • Improved volume source: Improved volume source: The volume source now fills more accurately, minimizing artificial movements after the initialization.

Furthermore, PreonLab 4.2 also improves the snow solver, adds the Herschel-Bulkley viscosity model for non-Newtonian fluids, enhances the car suspension model, accelerates performance in scenes with large geometries, introduces new rendering capabilities, reduces memory consumption and improves the airflow import.

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Mesh-based height sensor

How much snow accumulated above the windshield? The new mesh-based height sensor was a much-requested feature by engineers who use PreonLab to predict the soiling and wetting of surfaces. The new sensor works for both snow and fluid and can be used for any solid surface in the scene.

Improved user interface

For PreonLab 4.2, we have focussed on two key components that typically become bottlenecks when managing complex scenes with many objects. The first is the connection editor, which in the past could become unusable if too many objects where displayed. The updated connection editor handles these scenarios much better and also promotes a more efficient workflow, which avoids displaying that many objects altogether. The second component is the scene inspector, which now offers more tools to locate and view objects of interest. Combined, these changes ensure a much smoother user experience when handling large scenes.

Improved local refinement and user-defined domain shapes

In previous PreonLab versions, the process of particle refinement introduced a high computational cost. This made it necessary to limit the number of refinement events that occur in a simulation. We achieved this by refining particles in a generous “buffer zone” around the refinement domain if a refinement became necessary. This ensured that the cost of refinement was amortized over time, but it also meant that more particles were refined than necessary, which reduced the possible speedup for many applications. With PreonLab 4.2, the cost of refinement events is reduced significantly, which means that less buffering is necessary.

We also added the option to use custom domain volumes. You can now define the domain volume using the same seedpoint-based approach that is also employed by the volume source and the volume sensor. In many cases, this allows you to limit the refinement more precisely to a region of interest. This functionality is also available for other domain types.

Improved volume source

Filling a volume with particles of a fixed size is not a trivial task. Depending on the shape of the volume and the size of the particles, it is very common that small void spaces emerge that can not be filled without creating overlapping particles. This often means that the fluid will sink down a bit after initialization, filling out the small void spaces. With the new “Quality” fill method in PreonLab 4.2, this problem is mostly solved. The video below showcases how “Quality” filling improves fluid initialization for a gearbox compared to the old method.

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Volume source

The new filling method reduced artificial movements after the initialization.

Other changes

Check out the changelog for a full list of changes. To learn more about the new features, have a look at the updated manual. We hope you will enjoy working with PreonLab 4.2 and as always, we would appreciate your feedback.

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