We are proud to announce the release of PreonLab 2.0. Some of the most prominent new features are:
- PairwiseForce model for cohesion, adhesion and roughness
(calibrated and validated by the TU Dresden).
- PreonLab boundary handling: with the ‘no gap’ option, the offset between fluid and boundary is eliminated.
- Python library ‘preonpy’: the power of PreonLab at your hands right from your own python scripts.
- Velocity keyframing for even more intuitive and easily accessible rigid kinematics.
- Extended file format support: export your fluid data to the Ensight file format.
This is just a small excerpt from the extensive feature list of PreonLab 2.0. Be sure to check the changelog for a complete overview of the impressive changes.
Improved PREON® solver
New and improved cohesion, adhesion and roughness effects
During the past months our research and development team has been working hard on addressing the limitations that were inherent in the PreonCohesion model. With the new resolution invariant PairwiseForce model, we provide a unified approach to model effects like cohesion, adhesion and roughness. It asks for minimal user input and has been calibrated and validated by TU Dresden.
The default cohesion value is chosen automatically to resemble water. For adhesion, a value < 1 models a surface distracting the liquid phase while a value >= 1 models a wettable surface.
The PREON® solver now offers an option to eliminate the small gap between fluid and boundary geometries at moderate performance cost. This is crucial for simulations in which accurate flow rates and fluid volumes are necessary. In many cases, such simulations can now give good results even at coarse fluid resolutions.
We have improved the adaptive time-step estimation, resulting in more accurate and stable simulations.
Enhanced scripting and automation
PreonLab 2.0 introduced a new option for scripting. The PreonLabCLI executable with its integrated Python scripting is now accompanied by a stand-alone Python library, called preonpy. This Python library can be used like any other. You can simply import all the functionality of PREON® by typing `import preonpy` at the top of your Python script. The new method significantly simplifies the automatic execution of simulations with PREON® and better integrates into existing scripting environments, e.g. for optimization purposes.
The new ‘position control mode‘ provides more flexible and easier ways to specify the movement of objects. Instead of defining the position itself, you can choose to control the velocity or the acceleration of an object. In a similar way, the new ‘orientation control mode‘ allows to specify rotations and rotational velocities. This greatly simplifies the setup of scenes such as gear box simulations.
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Enhanced workflow – extended file format support
We extended the export functionality of PreonLab such that it fits better into your workflow. Starting with PreonLab 2.0 you can benefit from our technical partnership with Computational Engineering International, Inc. (CEI Inc.) and export particle data to the Ensight file format.
The new renderer dialog makes rendering images with Preon Renderer intuitive and simple. Rendering single images or image sequences for one or multiple cameras now requires only a few mouse clicks. Further, you can browse through previously rendered images, watch a live preview of the currently rendered image or abort the rendering process at any time. Creating impressive photorealistic renderings for presentations has never been this easy.
Improved water material
We added the photon mapping approach, allowing for beautiful caustics and improved the quality of reflections and refractions for the water material. It adds depth to the rendered images for a better understanding of the simulation results via visual cues.
With the new preferences dialog, you can choose presets for new scenes such as OSD background color, default working directories for simulations and global settings such as maximum number of threads.