2007
DOI: 10.1002/fld.1577
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Extension of efficient, swept‐integration‐based conservative remapping method for meshes with changing connectivity

Abstract: SUMMARYRemapping is one of the essential parts of most arbitrary Lagrangian-Eulerian methods. Here, we extend the idea of swept integration introduced in (J. Comput. Phys. 2003; 184(1):266-298) to meshes with connectivity changing in Voronoi-like manner. To demonstrate properties of the developed method, we present several numerical examples.

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Cited by 19 publications
(20 citation statements)
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“…Thus, it is utilized for ALE computation wherein the multi-material modeling is performed using concentration equations. We note that an extension of this method to polygonal grids with connectivity changing in a Voronoi-like manner has been recently developed 3 [31]. The second approach is the cell-intersection-based method.…”
Section: Introductionmentioning
confidence: 99%
“…Thus, it is utilized for ALE computation wherein the multi-material modeling is performed using concentration equations. We note that an extension of this method to polygonal grids with connectivity changing in a Voronoi-like manner has been recently developed 3 [31]. The second approach is the cell-intersection-based method.…”
Section: Introductionmentioning
confidence: 99%
“…Their common face has been removed on the new mesh, and a new face has appeared between falsec̃2 and falsec̃4. This type of reconnection, where one edge is removed and another one appears, is called Voronoi‐like reconnection . We want to notice that the method we define here for Voronoi‐like reconnection is different from the method proposed in , which consists of a swept‐integration‐based method where we shrink faces into a single node.…”
Section: The Reale Strategymentioning
confidence: 99%
“…One challenge of those single phase simulations are changes in topology of the volume occupied by water. This is difficult to handle, as neighbors have to be searched as soon as two water volumes unify [3].…”
Section: Introductionmentioning
confidence: 99%