This paper considers and proposes some algorithms to compute the mean curvature flow under topological changes. Instead of solving the fully nonlinear partial differential equations based on the level set approach, we propose some minimization algorithms based on the phase field approach. It is well known that zero-level set of the Allen-Cahn equation approaches the mean curvature flow before the onset of the topological changes; however, there are few papers systematically studying the evolution of the mean curvature flow under the topological changes. There are three main contributions of this paper. First, in order to consider various random initial conditions, we design several benchmark problems with topological changes, and we find different patterns of the evolutions of the solutions can be obtained if the interaction length (width of the interface) is slightly changed, which is different from the problems without topological changes. Second, we propose an energy penalized minimization algorithm which works very well for these benchmark problems, and thus furthermore, for the problems with random initial conditions. Third, we propose a multilevel minimization algorithm. This algorithm is shown to be more tolerant of the unsatisfying initial guess when there are and there are no topological changes in the evolutions of the solutions.
翻译:本文考虑并提出一些算法, 以计算表层变化下的平均曲线流。 我们不是根据水平设定方法解决完全非线性部分差异方程式,而是根据阶段字段法提出一些最小化算法。 众所周知, Allen- Cahn 等式的零等级组合在地形变化开始之前就接近平均曲线流; 然而, 很少有文件系统地研究在表层变化下的平均曲线流的演变情况。 本文有三个主要贡献。 首先, 为了考虑各种随机初始条件, 我们设计了几个表层变化的基准问题, 我们发现如果交互长度( 界面的宽度) 略微改变, 与没有表面变化的问题不同, 解决方案的进化模式就会不同。 其次, 我们提出一种能抵减最小化算法, 这对于这些基准问题非常有效, 因此, 对于随机初始条件的问题, 我们提出一个多级最小化算法。 我们提出一个多层次的算法, 为了考虑各种随机的初始条件, 我们设计了几个基准问题, 并且我们发现这些算法的进化模式比较宽容, 当出现进化的最初猜想的解决方案时, 上没有顶级变化。