Innovation corner

Preoneers know that PreonLab is all about particles! This is driven by our vision of a unified mesh-free representation for fluids and solids to simulate a wide (and ever-increasing) range of applications. With each release we aim to continually add new functionalities and keep improving on existing capabilities, to make our goal of developing the ultimate simulation tool a reality. Accordingly, version 6.2 will bring many additions and updates to expand on the multiphysics capabilities of PreonLab.

We are excited to announce the release of PreonLab 6.2! It is packed with advanced features and performance improvements to push the boundaries of multi-physics simulations. With each new release we continuously refine PreonLab, adding powerful functionalities and enhancing existing capabilities to make it the ultimate simulation tool. Here’s what this version has in store for you. What’s New in PreonLab 6.2? Full Car Suspension Model: We are taking our existing car suspension model (CSM) to the next level! The new Full Car Suspension Model (FCSM) now computes deflection forces per wheel, considering not just fluid forces but also acceleration, deceleration, and weight shifts. This sophisticated upgrade enables more precise simulations for automotive applications, like fast water wading, enhancing the overall performance and accuracy. Improvements for thermodynamics, multiphase and snow model: PreonLab 6.2 builds on several important enhancements across key areas for multiphysics simulations. Thermodynamics, multiphase, and snow features have been refined to improve accuracy and stability. Notable improvements include a new thermal sensor, an updated convective boundary condition, lateral adhesion for snow, improved snow boundary handling, and more stable multiphase interfaces—each contributing to elevating these features to a new level. Linear Elastic Solver: For those looking to simulate fluid-structure interactions, we are introducing an experimental linear elastic deformable solver. This first step into the realm of solid deformations caused by fluid interactions, opens new possibilities for applications that require the consideration of deformations under the load of external forces. Other notable additions: The latest release includes the introduction of the Carreau-Yasuda model for simulating non-Newtonian fluids and GPU support for the rigid body solver. Enhanced post-processing capabilities are now available with the new Calculation Objects feature, improved options for the pathlines sensor, and the ability to visualize the Q-criterion for more detailed flow analysis. This is just a selection of new features and improvements. Check out the changelog to learn about all the changes.  Make sure to follow us on LinkedIn so that you don’t miss new videos, case studies and updates!

With every PreonLab update, we aim to continuously enhance your simulation experience by increasing efficiency and reducing the memory footprint. While simulation on CPU is still the bread and butter for CFD, it is undeniable that GPUs can provide a significant performance boost towards reducing computation time. Nevertheless, one advantage CPUs generally have over GPUs is a larger memory space. Due to the limited memory of single GPU cards, simulating very large scenes with a lot of particles can be quite challenging. In addition, importing large tensor fields like airflows can also occupy a lot of precious memory space on the graphic card. While PreonLab can cleverly resample such airflows to fit on single GPU hardware, there will always come a point when sacrificing accuracy will be inevitable. One logical solution is making use of state-of-the-art GPU hardware that can accommodate large simulation scenes. Professional GPU cards like Nvidia’s H100 GPUs can already offer memory space up to 80 GB. However, does this mean that GPU simulations are only possible through the acquisition of larger and larger professional GPU cards? And what about scenes which might require even more memory space than the latest hardware available?

In the field of Computational Fluid Dynamics, the pursuit of simulation efficiency and accuracy is the name of the game. These two seemingly contradictory goals often appear at opposite ends of the spectrum. But is this always the case? Is it possible to have both efficiency and accuracy without making sacrifices? We believe it is. And we’re not referring to hardware efficiency, a topic extensively covered in our previous articles (see here and here). What we mean is state-of-the-art software development which is in the DNA of the FIFTY2 team. What we want to talk about in detail is one of our most prominent features available only in PreonLab. We named it Continuous Particle Size, or in short, CPS.

We are delighted to announce our new release – PreonLab 6.1. It is loaded with new features and improvements, enabling new engineering possibilities and applications. Empowered by the new GPU capabilities, PreonLab 6.1 takes another leap forward in efficient computing, delivering results even quicker. Read on to find out more about: Enhanced GPU performance: PreonLab’s GPU implementation just got a significant boost. Not only does PreonLab 6.1 support multi-GPU computing now, but it also enables continuous particle size (CPS), dynamic sampling, and adaptive sampling on GPU, making your simulations even more efficient. Airflow and Car Suspension Model (CSM): PreonLab 6.1 also enables airflow import and CSM support for simulations on GPU. These are some of the key application enablers making it possible to simulate various use cases also on GPU. Snow Model on GPU: Snow modeling has been an important part of existing PreonLab capabilities. We are thrilled to announce that our snow model is now also available on the GPU platform. Enhanced Thermodynamics: Convective boundary condition has been added to the list of available boundary conditions.  Convective Boundary Conditions can represent a more physical heat transfer, that predominantly occurs due to convective heat transport at fluid-fluid or fluid-solid interfaces. It is designed to conveniently represent natural or forced convection of heated solid bodies or fluids, in applications like heat exchangers, heat sinks, and even e-motors. This is just a selection of new features and improvements. Check out the changelog to learn about all the changes.  Make sure to follow us on LinkedIn so that you don’t miss new videos, case studies and updates!

Preoneers rely on the fact that with every new release, PreonLab aims to enhance your simulation experience by increasing efficiency and reducing the memory footprint for simulations. We firmly hold this at the core of our vision towards developing the ultimate simulation tool. We are glad to announce that version 6.1 takes a great leap towards realizing this goal as it extends GPU support for many PreonLab features and introduces multi-GPU capabilities.

Organizing and searching through data takes a lot of time that could otherwise be used more productively. To address this challenge, we have developed PreonDock. Since we started using it at FIFTY2, it has changed the way we work. Not only has our productivity increased, but it has also made our daily work easier. Keep reading to discover how PreonDock has changed our daily work with PreonLab and how it can do the same for you.

As simulation engineers, we want to get our ideas and points across to stakeholders, managers, co-workers from other departments, and customers as efficiently as possible. Typically, we back up our arguments by generating plots for statistics, which we put together to analyze our simulation results. We know exactly what all those numbers and multiple graphs and diagrams on every PowerPoint slide mean, and what conclusions need to be drawn from them to improve the product’s design. However, this is not always the case for everyone else, who is looking at the presentation. It is possible that some viewers might even be viewing the results and concepts for the first time, without much in-depth technical knowledge. Furthermore, even the most experienced engineer or team member might interpret a simulation result inaccurately, if all they have time for is a quick glance at the data. So, when it comes to communicating these results effectively, the message needs to be conveyed clearly – ideally in an appealing and easy-to-understand manner. This can be quite challenging since there are many small details that matter, but we also do not want the viewer to lose focus from the big-picture point of the discussion. Showing graphs and numbers is important, but on its own this can be rather dry.

“No wind blows in favour of a ship without direction.” This wisdom resonates deeply with our journey at FIFTY2, as it emphasizes the importance of having a clear vision. From day one, our direction at FIFTY2 has been unmistakable – to develop the ULTIMATE simulation tool. This is the story of how it is done.

When we started looking into CUDA support for PreonLab I didn’t really have any experience programming for GPUs. Getting from the first experiments in 2021 to production code has been a long learning process. For CUDA, there is no shortage of useful articles, documentation and examples (in fact this was one of the reasons to pick CUDA as a platform). Nevertheless, I thought it might be interesting to go over the most important lessons from my perspective as a developer used to x86-based CPUs, so here we go!