For the second time, more than twenty OpenLB developers retreated to the mountains for their annual Hackathon. There, they spent one week fully focused on improving the framework, exchanging knowledge and enjoying nature. This time, the focus was on refactoring all 133 example cases into a new consistent and user-friendly case style as well as general maintenance. The result is already visible in the public repository and will be incorporated into a new release this December. 

Preparations for next year’s iteration are already ongoing, any interested external contributors should feel free to contact us and join!

Registration is now open for the 9^th Spring School on Lattice Boltzmann Methods with OpenLB Software Lab that will be held in Liverpool, United Kingdom from March 23^rd to 27^th 2026.

The spring school introduces scientists and users 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 in the second half, where the participants gain deep insights into LBM and its applications. This educational concept is 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 an excursion. We look forward to your participation.

For more details and registration, visit https://www.openlb.net/spring-school-2026/.

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

New examples

• advectionDiffusionReaction/laminarReactiveTmixer
• electroChemistry/electroosmosis
• electroChemistry/poissonNernstPlanck
• forBeginners/cavity2d
• forBeginners/cylinder2d
• forBeginners/minimal3d
• forBeginners/pipeWithValve3d
• freeSurface/basicRisingBubble3d
• turbulence/airfoil2d
• fsi/deformableParticleInShearFlow3d
• fsi/rigidValve2d
• fsi/taylorCouette3d
• gridRefinement/cylinder2d
• gridRefinement/sphere3d
• laminar/nonNewtonianPoiseuille3d
• microfluidics/knudsenPump3d
• microfluidics/microChannel2d
• microfluidics/microChannel3d
• multiComponent/bubbleChannel2d
• multiComponent/dropletSplashing2d
• multiComponent/dropletSplashing3d
• multiComponent/flatInterfaceEOC2d
• multiComponent/isothermalEvaporation2d
• multiComponent/waterAirFlatInterface2d
• noise/gausspulse3d
• optimization/domainId3d
• optimization/pipeBendSolver2d
• optimization/testFlowOpti3d
• optimization/testFlowOpti3dSolver
• particles/bifurcation3d/eulerLagrange/nonSphericals
• pdeSolverEoc/cylinder2dEoc
• pdeSolverEoc/cylinder3dEoc
• pdeSolverEoc/poiseuille3dEoc
• pdeSolverEoc/poisson
• porousMedia/gasStorage2d
• radiativeTransport/sphere3d
• showCase/centrifugalPump3d
• showCase/urbanDigitalTwin3d
• uncertaintyQuantification/cavity2d
• uncertaintyQuantification/cavity3d
• uncertaintyQuantification/cylinder2d
• uncertaintyQuantification/cylinder3d
• uncertaintyQuantification/tgv2d
• web/cylinder2d

Citation

If you want to cite OpenLB 1.8 you can use:

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.

Version 1.8. Apr. 2024.

DOI: 10.5281/zenodo.15440776

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 8^th 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.

For more details and registration, visit https://www.openlb.net/spring-school-2025/.

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….

For further information please visit the associated show case: Particle Swarm Sedimentation

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.

Simulation & Visualization by Adrian Kummerländer

Visualization was generated in ParaView.

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.