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voFoam - A geometrical Volume of Fluid algorithm on arbitrary unstructured meshes with local dynamic adaptive mesh refinement using OpenFOAM (1305.3417v1)

Published 15 May 2013 in physics.flu-dyn and math.NA

Abstract: A new parallelized unsplit geometrical Volume of Fluid (VoF) algorithm with support for arbitrary unstructured meshes and dynamic local Adaptive Mesh Refinement (AMR), as well as for two and three dimensional computation is developed. The geometrical VoF algorithm supports arbitrary unstructured meshes in order to enable computations involving flow domains of arbitrary geometrical complexity. The implementation of the method is done within the framework of the OpenFOAM library for Computational Continuum Mechanics (CCM) using the C++ programming language with modern policy based design for high program code modularity. The development of the geometrical VoF algorithm significantly extends the method base of the OpenFOAM library by geometrical volumetric flux computation for two-phase flow simulations. For the volume fraction advection, a novel unsplit geometrical algorithm is developed, which inherently sustains volume conservation utilizing unique Lagrangian discrete trajectories located in the mesh points. This practice completely eliminates the possibility of an overlap between the flux polyhedra and hence significantly increases volume conservation. A new efficient (quadratic convergent) and accurate iterative flux correction algorithm is developed, which avoids topological changes of the flux polyhedra. Our geometrical VoF algorithm is dimension agnostic, providing automatic support for both 2D and 3D computations, following the established practice in OpenFOAM. The geometrical algorithm used for the volume fraction transport has been extended to support dynamic local AMR available in OpenFOAM. Furthermore, the existing dynamic mesh capability of OpenFOAM has been modified to support the geometrical mapping algorithm executed as a part of the dynamic local AMR cycle. The method implementation is fully parallelized using the domain decomposition approach.

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