变量(数学)
类型(生物学)
放松(心理学)
标量(数学)
要素(刑法)
数学
应用数学
数学优化
艾伦-卡恩方程
数学分析
计算机科学
经典力学
物理
几何学
地质学
心理学
政治学
社会心理学
古生物学
法学
作者
Yanping Chen,Qiling Gu,Jian Huang
标识
DOI:10.1142/s0218202524500453
摘要
In this paper, we consider integrating the scalar auxiliary variable time discretization with the virtual element method spatial discretization to obtain energy-stable schemes for Allen–Cahn-type gradient flow problems. In order to optimize CPU time during calculations, we propose two step-by-step solving SAV algorithms by introducing a novel auxiliary variable to replace the original one. Then, linear, decoupled, and unconditionally energy-stable numerical schemes are constructed. However, due to truncation errors, the auxiliary variable is not equivalent to the continuous case in the original definition. Therefore, we propose a novel relaxation technique to preserve the original energy dissipation rule. It not only retains all the advantages of the above algorithms but also improves accuracy and consistency. Finally, a series of numerical experiments are conducted to demonstrate the effectiveness of our method.
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