针对梯度流的具有原始耗散规律的部分和完全隐式多步 SAV 方法

IF 3.4 2区 数学 Q1 MATHEMATICS, APPLIED
Yanping Chen , Zhengguang Liu , Xiaoqing Meng
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引用次数: 0

摘要

Shen 等人(2019)考虑了标量辅助变量(SAV)方法,并广泛用于模拟一系列梯度流。然而,基于 SAV 的方案以 "修正 "能量的稳定性著称。本文基于对经典 SAV 方法的若干改进,构建了一系列具有无条件能量耗散规律的修正 SAV 方法。首先,通过引入三步技术,我们可以减少每个时间步需要求解的常数系数线性方程的数量,同时保留其所有其他优点。其次,能量优化技术和拉格朗日乘法器技术的加入可以使数值方案具有保留原有能量消耗的优势。第三,我们在 GSAV 方法中使用了能量平衡方程的一阶近似,而不是将辅助变量的动态方程离散化,从而可以构建高阶无条件原始能量稳定数值方案。最后,有代表性的数值示例表明,所提方案的效率和精度都有所提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Partially and fully implicit multi-step SAV approaches with original dissipation law for gradient flows
The scalar auxiliary variable (SAV) approach was considered by Shen et al. in Shen et al. (2019) and has been widely used to simulate a series of gradient flows. However, the SAV-based schemes are known for the stability of a ‘modified’ energy. In this paper, we construct a series of modified SAV approaches with unconditional energy dissipation law based on several improvements to the classic SAV approach. Firstly, by introducing the three-step technique, we can reduce the number of constant coefficient linear equations that need to be solved at each time step, while retaining all of its other advantages. Secondly, the addition of energy-optimal technique and Lagrange multiplier technique can make the numerical schemes have the advantage of preserving the original energy dissipation. Thirdly, we use the first-order approximation of the energy balance equation in the GSAV approach, instead of discretizing the dynamic equation of the auxiliary variable, so that we can construct the high-order unconditional original energy stable numerical schemes. Finally, representative numerical examples show that the efficiency and accuracy of the proposed schemes are improved.
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来源期刊
Communications in Nonlinear Science and Numerical Simulation
Communications in Nonlinear Science and Numerical Simulation MATHEMATICS, APPLIED-MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
CiteScore
6.80
自引率
7.70%
发文量
378
审稿时长
78 days
期刊介绍: The journal publishes original research findings on experimental observation, mathematical modeling, theoretical analysis and numerical simulation, for more accurate description, better prediction or novel application, of nonlinear phenomena in science and engineering. It offers a venue for researchers to make rapid exchange of ideas and techniques in nonlinear science and complexity. The submission of manuscripts with cross-disciplinary approaches in nonlinear science and complexity is particularly encouraged. Topics of interest: Nonlinear differential or delay equations, Lie group analysis and asymptotic methods, Discontinuous systems, Fractals, Fractional calculus and dynamics, Nonlinear effects in quantum mechanics, Nonlinear stochastic processes, Experimental nonlinear science, Time-series and signal analysis, Computational methods and simulations in nonlinear science and engineering, Control of dynamical systems, Synchronization, Lyapunov analysis, High-dimensional chaos and turbulence, Chaos in Hamiltonian systems, Integrable systems and solitons, Collective behavior in many-body systems, Biological physics and networks, Nonlinear mechanical systems, Complex systems and complexity. No length limitation for contributions is set, but only concisely written manuscripts are published. Brief papers are published on the basis of Rapid Communications. Discussions of previously published papers are welcome.
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