Journal of Function Spaces (Jan 2022)

An Adaptive Time-Stepping Algorithm for the Allen–Cahn Equation

  • Chaeyoung Lee,
  • Jintae Park,
  • Soobin Kwak,
  • Sangkwon Kim,
  • Yongho Choi,
  • Seokjun Ham,
  • Junseok Kim

DOI
https://doi.org/10.1155/2022/2731593
Journal volume & issue
Vol. 2022

Abstract

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In this paper, we present a simple and accurate adaptive time-stepping algorithm for the Allen–Cahn (AC) equation. The AC equation is a nonlinear partial differential equation, which was first proposed by Allen and Cahn for antiphase boundary motion and antiphase domain coarsening. The mathematical equation is a building block for modelling many interesting interfacial phenomena such as dendritic crystal growth, multiphase fluid flows, and motion by mean curvature. The proposed adaptive time-stepping algorithm is based on the Runge–Kutta–Fehlberg method, where the local truncation error is estimated by using fourth- and fifth-order numerical schemes. Computational experiments demonstrate that the proposed time-stepping technique is efficient in multiscale computations, i.e., both the fast and slow dynamics.