A quadtree-based adaptive moment-of-fluid method for interface reconstruction with filaments

Abstract

Implementation of quadtree adaptive mesh refinement (AMR) to the moment-of-fluid (MOF) method is presented in the context of an interface capturing method. Filaments, thinner than a cell size, are resolved using a computationally efficient technique on an unconstrained quadtree structure. The centroid defect relative to its cell size is used as the refinement criterion, together with an enhanced refinement calculation and subsequently its volume conservation. In addition, different approaches are proposed to ensure mass conservation during the computation. This MOF-AMR framework is validated for a range of benchmark problems which are studied widely in the literature. There is no restriction on the choice of CFL number for the purely Lagrangian advection method considered here and this has advantages when combined with AMR. The current quadtree MOF-AMR method leads to much improved computational efficiency and accuracy relative to its grid size compared with a uniform grid. Higher levels of refinement can be costly, therefore the efficiency of mesh resolution is further discussed in relation to the choice of time step and number of AMR levels.