Efficient finite element strategy using enhanced high-order and second-derivative-free variants of Newton's method

IF 3.5 2区 数学 Q1 MATHEMATICS, APPLIED Applied Mathematics and Computation Pub Date : 2024-09-13 DOI:10.1016/j.amc.2024.129058
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Abstract

In this work, we propose a stable finite element approximation by extending higher-order Newton's method to the multidimensional case for solving nonlinear systems of partial differential equations. This approach relies solely on the evaluation of Jacobian matrices and residuals, eliminating the need for computing higher-order derivatives. Achieving third and fifth-order convergence, it ensures stability and allows for significantly larger time steps compared to explicit methods. We thoroughly address accuracy and convergence, focusing on the singular p-Laplacian problem and the time-dependent lid-driven cavity benchmark. A globalized variant incorporating a continuation technique is employed to effectively handle high Reynolds number regimes. Through two-dimensional and three-dimensional numerical experiments, we demonstrate that the improved cubically convergent variant outperforms others, leading to substantial computational savings, notably halving the computational cost for the lid-driven cavity test at large Reynolds numbers.

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使用牛顿法的增强型高阶和无二次衍生变体的高效有限元策略
在这项工作中,我们提出了一种稳定的有限元近似方法,将高阶牛顿法扩展到多维情况下,用于求解非线性偏微分方程系统。这种方法仅依赖于雅各布矩阵和残差的评估,无需计算高阶导数。与显式方法相比,它能实现三阶和五阶收敛,确保稳定性,并允许显著增大时间步长。我们深入探讨了精度和收敛性问题,重点是奇异 p-Laplacian 问题和随时间变化的顶盖驱动空腔基准。我们采用了包含延续技术的全局化变体,以有效处理高雷诺数情况。通过二维和三维数值实验,我们证明了改进的立方收敛变体优于其他变体,从而节省了大量计算成本,尤其是在大雷诺数下,将盖子驱动空腔测试的计算成本降低了一半。
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来源期刊
CiteScore
7.90
自引率
10.00%
发文量
755
审稿时长
36 days
期刊介绍: Applied Mathematics and Computation addresses work at the interface between applied mathematics, numerical computation, and applications of systems – oriented ideas to the physical, biological, social, and behavioral sciences, and emphasizes papers of a computational nature focusing on new algorithms, their analysis and numerical results. In addition to presenting research papers, Applied Mathematics and Computation publishes review articles and single–topics issues.
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