FIFTY2

Innovation corner

There is always one more shot to solve the unsolved problem. Tinkering around, entering the unknown and starting over again is our approach to push the boundaries and create next level innovations. Stay tuned for PreonLab updates, new researches, groundbreaking innovation and upcoming events.

September 30, 2021
Fabian Meyer and Marian Majda
Snow creates deeply physical experiences that can remain vivid memories: Seeing snow for the first time, a snow crystal melting on your tongue, a snowball fight, the different activities summarized as winter sports. However, snow also affects human activity and can, quite literally, get in the way. Snowplows clear roads, highways, airfields and railroads. Snow drifts may destabilize structures due to uneven loading. Avalanches and blizzards are natural hazards that can endanger living beings. PreonLab solves many automotive problems. When it comes to snow, one is foremost interested to prevent soiling of critical components. The number of tasks is vast. Some that PreonLab has already solved are: Placing cameras for self-driving cars, snow entering the engine air intake which can cause a power drop or localizing corrosion hot-spots in the wheelhouse. Audi and Great Wall Motor are just some examples demonstrating the snow solver capabilities to simulate and capture phenomenas measured in real world test setups at different vehicle speeds. Out of the many sensors PreonLab provides, the addition of the height sensor has been key for the engineers to assess soiling. So how does PreonLab achieve this? Let’s take a step back and look what we are up against.
September 09, 2021
Aju Abraham and Shreyas Joshi
Each simulation tool/method has its strengths. Often in industrial workflows, multiple tools are combined over an interface to exploit the advantages each tool offers. PreonLab offers a wide range of possibilities to easily couple it with other tools. In this article, we talk over the several coupling interfaces that PreonLab offers, and more specifically a workflow developed for coupling PreonLab to TAITherm using a case of battery cooling simulation.
August 18, 2021
Saba Golshaahi Sumesaraayi and Markus Ihmsen
The lid-driven cavity problem is of high importance in fluid dynamics serving as a benchmark for the validation of CFD methods as well as for studying fundamental aspects of incompressible flows in confined volumes driven by the tangential motion of one or more bounding walls. In this article, capabilities of PreonLab in capturing 2-D flows inside a cavity are evaluated for different Reynolds numbers.
August 12, 2021
Saba Golshaahi Sumesaraayi, Max Flamm and Andreas Henne
With the release of version 5.0, PreonLab saw several additions to it, ranging from new features to under-the-hood developments. They play an important role for wading simulations, which can be broadly classified as follows: Performance & Accuracy: Adaptive simulations with up to 3 particle levels Faster Pressure Solver Usability: Object Grouping Improvements in the Plot Dialog Improvements in the Connection Editor Connect sensor right-click action
July 22, 2021
Loïc Wendling, Jennifer Weiche, Shreyas Joshi and Aju Abraham
Piston Cooling Jets (PCJs) are used in traditional Internal Combustion (IC) engines to remove the excess heat from the piston, allowing for higher thermal loads to be reached. PreonLab 5.0 allows for investigations of the dynamic and thermal interactions between the lubricating oil jet and the moving piston.
July 08, 2021
Jing Tai Tune
For coarsely-resolved simulations, especially those for applications that require numerous quick design iterations to asses the plausibility of a design, a simulation that both runs quickly and delivers results in the correct ballpark is needed. The coarse resolution allows for fast computation, but such simulations tend to suffer from gradient underprediction at the walls. This happens in particular for flow regimes which may be considered as turbulent, where the steep gradients at the wall mean that a very fine resolution is required to correctly reproduce them. With the effect of wall-bounded phenomena (e.g. wall shear stress, wall heat flux) being a key result for studies that such simulations are used for, it is clear that there is potential for improvement here.
June 23, 2021
Max Flamm and Saba Golshaahi Sumesaraayi
Being one of the flagship applications of PreonLab has made it important to offer various post-processing possibilities to address the needs of the users when it comes to water wading simulations. You can gain loads of insight by performing a full wetting analysis, measuring the flooding height, predicting under-body forces and understanding the flow paths for the regions of interest as well as measuring flow rates of water entering the engine compartment or any critical part of the vehicle.
May 05, 2021
It’s finally here! PreonLab 5.0 is a massive update and we couldn’t be more excited to share it with you. Are you ready for the next level? Here is why this major release is a leap forward in efficiency, usability and reliability: Adaptive Resolution: PreonLab 5.0 adds a third particle level and greatly improves the quality and efficiency of adaptive simulations. This enables unprecedented speedups for a broad range of applications. User Interface Update: Once you start PreonLab 5.0 for the first time, you will not want to go back. But this release does not only introduce a fresh and beautiful look, it also includes a number of changes that will accelerate your workflow. Thermodynamics: The new (experimental) conjugate heat transfer capability allows you to tackle even more applications with PreonLab. Furthermore, the new wall functions enable more accurate thermodynamics simulations. Snow Solver: PreonLab 5.0 improves complex snow dynamics with dramatic increases in accuracy and efficiency. Make sure to follow us on LinkedIn so that you don’t miss new videos, case studies and updates!
May 05, 2021
Jens Cornelis and Markus Ihmsen
Get ready for the »NEXT LEVEL«. Join us to celebrate the release of PreonLab 5.0 and be the first to learn about the new features.
March 16, 2021
Andreas Henne and Max Flamm
In the article, Adaptive Particle-based Simulation in PreonLab, we showed that a simulation with two particle levels can accurately reproduce the results of a simulation with higher uniform resolution. But delivering a good result is not enough – for the system to be useful it must also deliver this result faster than the uniform simulation. The adaptive simulation will always have fewer particles, but this does not necessarily mean that it will be more efficient overall. Splitting, merging and correction (see the last article) represent a significant effort and can outweigh the reduction in particles. Is the cost worth it?