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Semi-automatic construction of Lattice Boltzmann models

A crucial step in constructing a Lattice Boltzmann model is the definition of a suitable set of lattice velocities, and the correct assignment of the associated weights. For high-order models, the solution of this problem requires a non-trivial effort. The paper outlines the functioning of a publicly available Python script which has been written to assist researchers in that task. The speed of sound $c_s$ is considered as a parameter, which can, within limits, be chosen at will. Under this premise, the Maxwell-Boltzmann constraint equations are a system of linear equations to determine the weights, and hence amenable to numerical solution by standard linear algebra library routines. By suitable contractions, the tensor equations are mapped to a set of equivalent scalar equations, which simplifies the treatment significantly. For a user-supplied set of velocity shells, the software first checks if a solution for the weights exists, and returns it if it also happens to be unique. In such a case, the software also calculates the range of $c_s$ values that yield positive weights. Standard models like D3Q19 with a well-defined special $c_s$ value then result as limiting cases where one of the weights vanishes. In case of an infinite set of solutions, the user may find one particular solution by supplying a $c_s$ value, and then minimizing one or several weights within the framework of standard linear programming. Some examples illustrate the feasibility and usefulness of the approach. A number of models that have been discussed in the literature are nicely reproduced, while the software has also been able to find some new models of even higher order.

preprint2020arXivOpen access
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