waLBerla - widely applicable lattice Boltzmann from Erlangen

Welcome to the waLBerla Framework, a widely applicable lattice Boltzmann simulation code from Erlangen. These are the documentation pages for the project's C++ code base.

Note

This is the documentation for waLBerla version 7.2. To find the documentation for the current development revision, please refer to our Git repository at https://walberla.pages.i10git.cs.fau.de/walberla/.

Setup Instructions

On the following pages, you can find instructions on downloading and setting up waLBerla both as a standalone project and as a library:

• Get and Build waLBerla
• Using waLBerla as a library in your CMake Project
• FAQ: Common Problems When Building waLBerla

Tutorials

Basics

The following tutorials show you how to get and build waLBerla and describe all the basic data strcutures and concepts of the framework.

• Tutorial - Basics 1: waLBerla Data Structures: Blocks and Fields
  The first tutorial explains the basic data structures of waLBerla and how to setup a simple domain.
• Tutorial - Basics 2: Algorithms on Blocks: Sweeps
  The second tutorial shows how to write algorithms that operate on block data.
• Tutorial - Basics 3: Writing a Simple Cellular Automaton in waLBerla
  The third tutorial deals with communication, iterating field/grid/lattice data, and geometry setup.

Modular and Extensible Software Architecture for Particle Dynamics

• Tutorial - Confined Gas: Setting up a simple MESA-PD simulation
  

Solving Partial Differential Equations

• Tutorial - PDE 1: Solving PDEs with the Jacobi Method
  Implementation of an iterative solver for the solution of a partial differential equation.
• Tutorial - PDE 2: Solving the Heat Equation
  Extending the previous tutorial to be able to solve the heat equation.

Simulations with the Lattice Boltzmann Method

• Tutorial - LBM 1: Basic LBM Simulation
  A full LBM simulation is built.
• Tutorial - LBM 4: Complex Geometry
  A LBM simulation with complex geometries is built.
• Tutorial - LBM 5: Backward-facing step
  A LBM simulation with a backward-facing step is set up.
• Tutorial - LBM 6: Boundary Conditions
  This tutorial deals with the usage of different LBM boundary conditions.

Advanced Topics

GPU

• Tutorial - GPU 1: Game of Life on GPU
  A simple tutorial for Game of Life on GPU

Code Generation

• Tutorial - Code Generation 1: Explicit Solver for the Heat Equation
  This tutorial shows how to use pystencils to generate waLBerla sweeps from symbolic descriptions.
• Tutorial - Code Generation 2: Lattice Model Generation with lbmpy
  This tutorial demonstrates how to use lbmpy to generate an efficient lattice model for a waLBerla sweep.
• Tutorial - Code Generation 3: Advanced LBM Code Generation
  This tutorial describes how to use lbmpy to generate a full LBM sweep for waLBerla.

Further information

Not all features of the framework are covered in the tutorials. To get further information have a look at the modules pages.

Also, the test cases provided in the tests directory are a good starting point for your own developments. Additionally, there is a folder for full-fledged application codes to be found under apps/benchmarks where also codes of walBerla publications are found.

Contact Us

To get in touch with the waLBerla team, you can:

• For bug reports and code-related issues: Create an issue at https://i10git.cs.fau.de/walberla/walberla and describe the bug as accurately as possible.
• For feature requests, collaboration inquiries, etc.: write to our developer's mailing list (cs10-.nosp@m.walb.nosp@m.erla@.nosp@m.fau..nosp@m.de).

Please cite us

If you use waLBerla in the preparation of a publication, please cite [godenschwager2013framework] and [bauer2021walberla]. There are separate publications for some modules, which you should cite in addition if you use them.

• Grid refinement: [schornbaum2016massively]
• PE coupling: [rettinger2017comparative]
• Python interface: [bauer2016python]
• pystencils code generation: [bauer2019code]
• lbmpy LB model generation: [bauer2021lbmpy]