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Moving finite element methods for phase-field models of solidification.

机译:凝固相场模型的移动有限元方法。

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摘要

The phase-field approach is one of the main choices for simulating phenomena in solidification and other related systems. Since the solutions of the phase-field equations have large solution variations, adaptive grid methods have become important in their numerical simulations. This thesis is mainly concerned with the applications of one of the adaptive grid methods, namely, the so called moving mesh method (or r-adaptive method), to the finite element discretization of the phase-field equations arising from the solidification problem.;We begin by briefly discussing various models for phase-field approaches for solidification. We then present a simple moving mesh method for solving phase-field equations with isotropy surface energy. The mesh redistribution is realized by solving an elliptic boundary control problem. Moreover, an efficient alternating Crank-Nicolson time discretization scheme is developed for solving the nonlinear system resulting from a finite element approximation to the phase-field equations. The efficiency of the method is demonstrated by numerical experiments.;For a simple model problem, some existing moving mesh solutions do not agree with the numerical solutions on very fine fixed mesh. From our numerical studies, it is concluded that for the phase-field equations the numerical solutions are sensitive to the starting mesh and the monitor function. The present numerical evidences indicate that the under-resolution of the interface curvature maybe the source of the qualitatively error in the numerical solutions. This is mainly due to the use of some inappropriate starting meshes. Our computations suggest that the Delaunay mesh is in general a good choice of the starting mesh.;Based on the above results, we present an efficient moving finite element algorithm for the phase field model of dendritic growth in both two and three dimensions cases. The nodes redistribution was improved by a recently developed nonlinear multi-grid algorithm to make the 3D simulations possible. With a particularly designed monitor function, the quality of the redistributed mesh grids is improved significantly. Consequently, the numerical results with fewer degrees of freedom is comparable with the results on finer uniform meshes. It is illustrated by the numerical experiments that the tip velocity obtained by our numerical algorithm is in good agreement with the published ones. Due to the high efficiency of the proposed algorithm, both 2D and 3D simulations can be carried out on standard desktop computers.;We remark that although the monitor functions proposed in this work are specially designed for the dendritic growth problem, the basic idea of the approach seems applicable for designing monitor functions for more general problems involving interfaces.;Keywords. Phase field model, Moving mesh method, Crank-Nicolson scheme, Numerical sensitivity, Finite element method, Dendritic growth.
机译:相场方法是模拟凝固和其他相关系统中的现象的主要选择之一。由于相场方程的解具有较大的解变化,因此自适应网格方法在其数值模拟中变得非常重要。本文主要涉及一种自适应网格方法,即所谓的移动网格方法(或r自适应方法)在凝固问题引起的相场方程的有限元离散化中的应用。我们首先简要讨论用于凝固的相场方法的各种模型。然后,我们提出了一种用于求解具有各向同性表面能的相场方程的简单移动网格方法。网格的重新分布是通过解决椭圆边界控制问题来实现的。此外,开发了一种有效的交替Crank-Nicolson时间离散化方案,用于求解由对相场方程的有限元逼近产生的非线性系统。通过数值实验证明了该方法的有效性。对于一个简单的模型问题,一些现有的运动网格解与非常精细的固定网格上的数值解不一致。从我们的数值研究可以得出结论,对于相场方程,数值解对起始网格和监测函数敏感。目前的数值证据表明,界面曲率的分辨率不足可能是数值解中定性误差的来源。这主要是由于使用了一些不合适的起始网格。我们的计算表明,通常Delaunay网格是起始网格的一个很好的选择。基于以上结果,我们提出了一种有效的移动有限元算法,用于二维和三维情况下的树突生长相场模型。最近开发的非线性多网格算法改进了节点的重新分配,从而使3D仿真成为可能。通过特别设计的监视功能,可以大大提高重新分配的网格的质量。因此,具有较少自由度的数值结果与在较细的均匀网格上的结果相当。数值实验表明,我们的数值算法获得的叶尖速度与已公开的叶尖速度非常吻合。由于该算法的高效率,因此可以在标准台式计算机上进行2D和3D模拟。;我们注意到尽管本文中提出的监控功能是专门针对树突生长问题设计的,但其基本思想是这种方法似乎适用于针对涉及接口的更一般问题设计监视器功能。相场模型,移动网格法,Crank-Nicolson方案,数值灵敏度,有限元法,树枝状生长。

著录项

  • 作者

    Wang, Heyu.;

  • 作者单位

    Hong Kong Baptist University (Hong Kong).;

  • 授予单位 Hong Kong Baptist University (Hong Kong).;
  • 学科 Mathematics.
  • 学位 Ph.D.
  • 年度 2008
  • 页码 119 p.
  • 总页数 119
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:38:33

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