The Efficient Variable Time-stepping DLN Algorithms for the Allen-Cahn Model
Abstract
We consider a family of variable time-stepping Dahlquist-Liniger-Nevanlinna (DLN) schemes, which is unconditional non-linear stable and second order accurate, for the Allen-Cahn equation. The finite element methods are used for the spatial discretization. For the non-linear term, we combine the DLN scheme with two efficient temporal algorithms: partially implicit modified algorithm and scalar auxiliary variable algorithm. For both approaches, we prove the unconditional, long-term stability of the model energy under any arbitrary time step sequence. Moreover, we provide rigorous error analysis for the partially implicit modified algorithm with variable time-stepping. Efficient time adaptive algorithms based on these schemes are also proposed. Several one- and two-dimensional numerical tests are presented to verify the properties of the proposed time adaptive DLN methods.
Cite
@article{arxiv.2409.19481,
title = {The Efficient Variable Time-stepping DLN Algorithms for the Allen-Cahn Model},
author = {YiMing Chen and Dianlun Luo and Wenlong Pei and Yulong Xing},
journal= {arXiv preprint arXiv:2409.19481},
year = {2024}
}