The OpenLB team enjoyed a fantastic week at the CIRM in Marseille for the 8th and largest Spring School to date with 105 participants from 18 countries. Together with our friends from AMU, ProLB and the Falcon project we were happy to both introduce many new people to the theory and practice of LBM as well as to continue collaborating on many interesting research questions in the advanced section.
We also want to congratulate Sai Ravi Gupta Polasanapalli for winning this year’s poster award.
Already, we are busy organizing the next spring school which will take place in Liverpool, UK from March 23-27 2026. Stay tuned for more details soon!
The developer team is very happy to announce the release of the next major version of OpenLB. The updated open-source Lattice Boltzmann (LB) code is now available for download.
This release contains a plethora of new models, features and usability improvements, not to forget 40+ new example cases. The addition of a wall model for fixed and moving walls usable together with a new platform-transparent fluid structure interaction module, physically parameterized multi-phase models and examples and a completely revamped code generation pipeline deserve special mention. Last but not least, it also provides preliminary support for grid refinement operators.
The new release is also available in our public Git repository together with all previous releases. We encourage everyone to submit contributions as merge requests and report issues there.
Core development continues within the existing private repository which is available to consortium members.
Release notes
Highlights
Revised and new turbulence wall model for static and moving walls
Physically parameterize multi-phase models
New conservative Allen-Cahn model with access to high density and viscosity ratios as well as high surface tension and wetting
Improved well balanced Cahn-Hilliard model, now with no spurious currents and access to higher density and viscosity contrasts and wetting
Improved and consistent pseudo-potential model
Lots of new multi-phase examples, now in physical units
First release of general purpose fluid structure interaction module
Platform-transparent and performance optimized
Validation benchmark examples
Completely revamped automatic code generation for dynamics and non-local post processors
Automatic CSE optimization of any non-branching dynamics and post processor
Easily triggered without complex dependencies by introspection output
110+ dynamics optimized
Initial operators for efficient, GPU-enabled grid refinement
Initial examples using the scheme by Lagrava et al.
New backwards automatic differentiation approach for automatic generation of CSE-optimized adjoint dynamics
Initial immersed boundary model for resolved deformable blood cells New Uncertainty quantification (UQ) module
Non-intrusive UQ methods integrated with full support for Monte Carlo, Quasi Monte Carlo, Latin Hypercube Sampling, and stochastic collocation generalized polynomial chaos
A. Kummerländer, T. Bingert, F. Bukreev, L. Czelusniak, D. Dapelo, C. Gaul. N. Hafen, S. Ito, J. Jeßberger, D. Khazaeipoul, T. Krüger, H. Kusumaatmaja, J.E. Marquardt, A. Raeli, M. Rennick, F. Prinz, M. Schecher, A. Schneider, Y. Shimojima, S. Simonis, P. Sitter, P. Spelten, A. Tacques, D. Teutscher, M. Zhong, and M.J. Krause.
OpenLB Release 1.8: Open Source Lattice Boltzmann Code.
General metadata is also available as a CITATION.cff file following the standard Citation File Format (CFF).
Supported Systems
OpenLB is able to utilize vectorization (AVX2/AVX-512) on x86 CPUs [1] and NVIDIA GPUs for block-local processing. CPU targets may additionally utilize OpenMP for shared memory parallelization while any communication between individual processes is performed using MPI.
It has been successfully employed for simulations on computers ranging from low-end smartphones over multi-GPU workstations up to supercomputers and even runs in your browser.
The present release has been explicitly tested in the following environments:
Red Hat Enterprise Linux 8.x (HoreKa, BwUniCluster2)
NixOS 24.11 and unstable (Nix Flake provided)
Ubuntu 22.04 and newer
Windows 10, 11 via WSL
Mac OS Ventura 13.6.3
However, it generally will run without issue on any system offering one of the supported compilers. Don’t hesitate to contact us via the forum should you face any difficulties.
[1]: Other CPU targets are also supported, e.g. common Smartphone ARM CPUs and Apple M1/M2.
Registration is now open for the 8th Spring School 2025 on Lattice Boltzmann Methods with OpenLB and ProLB Software Lab that will be held in Marseille/France form 19.05.2025 – 23.05.2025.
The spring school introduces scientists and applicants from industry to the theory of LBM and trains them on practical problems. The first half of the week is dedicated to the theoretical fundamentals of LBM up to ongoing research on selected topics. Followed by mentored training on case studies using OpenLB or ProLB in the second half, where the participants gain deep insights into LBM and its applications. This educational concept is probably unique in the LBM community and offers a comprehensive and personal guided approach to LBM. Participants also benefit from the knowledge exchange during poster session, coffee breaks and the excursion. We look forward to your participation.
From October 6-11, 2024, the LBRG successfully organized the first OpenLB Hackathon in Feldberg, Germany. For one week, 14 group members focused on core development to further improve OpenLB in terms of boundary condition modeling, GPU support and user friendliness.
We have just released a new video on our OpenLB YouTube Channel:
Particle Swarm Settling Behavior Spheres and Cubes Using Lattice Boltzmann Methods and OpenLB
This video presents a detailed comparison of the swarm settling (or hindered settling) behavior of volume-equivalent spheres and cubes. The simulation is fully resolved and four-way coupled, showing the dynamic behavior of 1934 particles within a triple periodic domain measuring 15D x 15D x 15D, where D = 3 mm is the diameter of the spheres. The particle volume fraction is approximately 30% and the Archimedes number is set to 2000.
Observations from the video
Shape matters: Particle shape has a significant effect on the suspension dynamics.
Average settling velocity: Cubes settle on average approximately 24% slower than the volume-equivalent spheres.
Clustering: Spheres have a higher tendency to form clusters than cubes.
The simulations were performed with OpenLB using 152 cores (Intel Xeon Platinum 8368 CPU) and both simulations together took less than 13 hours to complete.
Further details and in-depth analysis can be found in the corresponding publications [1, 2].
[1]: J. E. Marquardt, N. Hafen, and M. J. Krause, “A novel model for direct numerical simulation of suspension dynamics with arbitrarily shaped convex particles,” Computer Physics Communications, vol. 304, p. 109321, 2024, doi: 10.1016/j.cpc.2024.109321.
[2]: J. E. Marquardt, N. Hafen, and M. J. Krause, “A novel particle decomposition scheme to improve parallel performance of fully resolved particulate flow simulations,” Journal of Computational Science, vol. 78, p. 102263, 2024, doi: https://doi.org/10.1016/j.jocs.2024.1….
We have just released a new video on our OpenLB YouTube Channel:
OpenLB Development Preview: Large Eddy Lattice Boltzmann Simulation of a Wind Park
This is a first experimental showcase of OpenLB’s upcoming general purpose fluid structure interaction (FSI) capabilities. Visualized are various viewpoints on the vorticity norm of a two-way coupled four-turbine wind park setup with Reynolds number 1.2 Million. The simulation consisting of 1.5 billion cells utilized a single accelerated compute node of 4x NVIDIA H100 GPGPUs.
Computed on HoreKa Teal at KIT, the world’s sixth most energy efficient supercomputer.
We are excited to announce the launch of a new section dedicated to showcasing OpenLB projects! This section features a variety of innovative and practical applications, demonstrating the powerful capabilities of OpenLB in computational fluid dynamics. Explore detailed project descriptions, and visual simulations that highlight the versatility and effectiveness of OpenLB in solving real-world problems. Visit the new Showcase section today and get inspired by the possibilities with OpenLB! Click here to explore.
The executive committee is happy to announce the closing of the 7th LBM Spring School with OpenLB Software Lab. We hosted 57 participants from 13 countries this year. Congratulations to Jakob Scheel from the US for winning our poster award. We are already busy with organizing the next spring schools. The 8th spring school is planned to take place in Marseille, France from May 19-23, 2025. We would like to thank all participants for attending the 7th spring school in Heidelberg and acknowledge the support from our funders.
On behalf of the spring school executive committee (Kerstin Dick, Shota Ito, Mathias J. Krause and Stephan Simonis)
The developer team is very happy to announce the release of the next version of OpenLB. The updated open-source Lattice Boltzmann (LB) code is now available for download.
Major changes include the adaptation of many existing models into the GPU-supporting operator style, a validated turbulent velocity inlet condition and a special focus on new multi phase and particle models. This is augmented by a collection of bugfixes and general usability improvements.
For the first time, the new release is also available in a new public Git repository together with all previous releases. We encourage everyone to submit contributions as merge requests and report issues there.
Core development continues within the existing private repository which is available to consortium members.
Release notes
New features and improvements
Many existing models converted to the operator-style (“GPU support”)
New multi phase models, interaction potentials and examples
New Unit Converter for multi phase simulations
New validated turbulent inlet condition Vortex Method
New particle decomposition scheme that improves parallel performance of fully resolved particulate flow simulations using HLBM
New boundary condition zero gradient
Tidy up, (performance) improvements of optimization code
Optional support for loading porosity data using OpenVDB voxel volumes
A. Kummerländer, T. Bingert, F. Bukreev, L. Czelusniak, D. Dapelo, N. Hafen, M. Heinzelmann, S. Ito, J. Jeßberger, H. Kusumaatmaja, J.E. Marquardt, M. Rennick, T. Pertzel, F. Prinz, M. Sadric, M. Schecher, S. Simonis, P. Sitter, D. Teutscher, M. Zhong, and M.J. Krause.
OpenLB Release 1.7: Open Source Lattice Boltzmann Code.
Version 1.7. Feb. 2024.
DOI: 10.5281/zenodo.10684609
General metadata is also available as a CITATION.cff file following the standard Citation File Format (CFF).
Supported Systems
OpenLB is able to utilize vectorization (AVX2/AVX-512) on x86 CPUs [1] and NVIDIA GPUs for block-local processing. CPU targets may additionally utilize OpenMP for shared memory parallelization while any communication between individual processes is performed using MPI.
It has been successfully employed for simulations on computers ranging from low-end smartphones over multi-GPU workstations up to supercomputers and even runs in your browser.
The present release has been explicitly tested in the following environments:
Red Hat Enterprise Linux 8.x (HoreKa, BwUniCluster2)
NixOS 22.11, 23.11 and unstable (Nix Flake provided)
Ubuntu 20.04 and newer
Windows 10, 11 via WSL
Mac OS Ventura 13.6.3
[1]: Other CPU targets are also supported, e.g. common Smartphone ARM CPUs and Apple M1/M2.
Introducing the app “paint2sim” – A Digital Twin for 2D Fluid Flow Simulations
Paint2sim is a mobile application using a Lattice Boltzmann Method realized by the open-source simulation framework OpenLB. This innovative app allows users to scan hand-drawn domains and visualize 2D fluid flow simulations just-in-time on their mobile devices. Whether you’re a student, researcher, or engineer, explore fluid dynamics with an intuitive interface with your fingertips. The app is freely available for download.
Dennis Teutscher and his team developed the app paint2sim as part of the “teaching4future” project, with funding from the Lattice Boltzmann Research Group at KIT and the Ministry of Science, Research, and Arts of Baden-Württemberg, Germany.
Use Case: Scanning a hand-drawn domain and simulating it on a mobile device
We use cookies to ensure that we give you the best experience on our website. If you continue to use this site we will assume that you are happy with it.Ok
