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

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

基于四叉树的自适应流体矩方法,用于细丝界面重建

DOI:
10.1016/j.jcp.2023.112719
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发表时间:
2024
影响因子:
4.1
通讯作者:
Hergibo P
Hergibo P
中科院分区:
物理与天体物理2区
文献类型:
--
作者:
Hergibo P

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在一种界面捕捉方法的背景下,提出了四叉树自适应网格加密(AMR)到流体矩(MOF)方法的实现。细丝,薄于细胞大小,解决了使用计算效率高的技术上的无约束的四叉树结构。相对于其细胞大小的质心缺陷被用作细化标准,连同增强的细化计算和随后的体积守恒。此外,提出了不同的方法,以确保在计算过程中的质量守恒。这MOF-AMR框架验证了一系列的基准问题,在文献中广泛研究。这里考虑的纯拉格朗日平流方法对CFL数的选择没有限制,这在与AMR结合时具有优势。与均匀网格相比,当前的四叉树MOF-AMR方法相对于其网格大小导致大大提高的计算效率和精度。更高级别的细化可能是昂贵的,因此,网格分辨率的效率进一步讨论的时间步长和AMR级别的数量的选择。
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.
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发表时间: 2020-08
影响因子: 1.8
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影响因子: 4.1
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