PreonLab 4.1 Released

January 17, 2020

2019 has been an extraordinary year for PreonLab. Probably the most exciting part was seeing the results that you achieved in your respective fields. Let’s push the boundaries of simulation further in 2020!

We’re kicking off the new year with the release of PreonLab 4.1, which expands and improves the features introduced in 4.0. The most notable changes include:

  • Improved local refinement: Local refinement is no longer an experimental feature and is now available for all users.
  • Preonpy sensor interface: It is now possible to access per-sample sensor data in preonpy, which allows for more powerful and customized post-processing.
  • Improved property editor: With physical units everywhere, better keyframing integration and many fixes, PreonLab 4.1 delivers a more reliable and productive user experience.
  • Improved snow solver: The snow solver is now more robust and efficient.

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Improved local refinement

Local refinement was added as an experimental feature in PreonLab 4.0. Since then, we have received lots of feedback ranging from minor bug reports to very ambitious feature requests. Overall, we are very excited by the feedback and worked on numerous fixes and improvements for 4.1. Most notably, this includes full support for MPI and most sensors. We also removed the experimental flag so that the feature is now available for all users.

The two images below show an example in which local refinement is used to speed up a gearbox simulation. The image to the left shows the simulation with a uniform particle size of 1mm after 0.2 seconds. The image to the right shows the same setup with local refinement. Only in the region where the two gears come into contact, a particle size of 1mm is used. In other regions, a particle size of 2mm may be used. The resulting fluid behavior matches the uniform simulation well, while the required simulation time is reduced by more than a factor of 2 and disk space consumption is reduced by a factor of 5. Both simulations were performed on a 32-core workstation and the stated timings include rendering.

Uniform: ~2.25 hours, 26 GB of data

Adaptive: 48 minutes, 5 GB of data

Local refinement is used in the region where the gears come into contact.

Preonpy sensor interface

Per-sample sensor data is now available in preonpy. The new interface provides efficient and easy-to-use access for most sensor data produced by PreonLab. Libraries like numpy can utilize it to run fast operations on the data, like filtering or statistical analysis. Compared to the existing CSV export options, this can reduce computation times from hours to minutes when implementing custom post-processing capabilities.

Improved property editor

The updated property editor now displays physical units for all appropriate properties, reducing the risk of mixing up units when entering values. We have addressed another common source of frustration by introducing colored states to indicate keyframed properties. It is now also much easier to see and if desired to reset properties that deviate from their default values. Finally, we invested a lot of effort to achieve a consistent look and feel of the entire UI including the property editor across all supported platforms.

Improved snow solver

PreonLab 4.1 improves the performance and stability of the snow solver. The updated implicit solver was optimized for more scenarios and made more robust. Check out our recent snow plow video below:

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This scene was simulated on a single machine in less than 12 hours.



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