共 26 条
A class of weighted energy-preserving Du Fort-Frankel difference schemes for solving sine-Gordon-type equations
被引:0
|作者:
Deng, Dingwen
[1
]
Wang, Qihong
[1
]
机构:
[1] Nanchang Hangkong Univ, Coll Math & Informat Sci, Nanchang 330063, Peoples R China
来源:
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
|
2023年
/
117卷
基金:
中国国家自然科学基金;
关键词:
Auxiliary functions;
sine-Gordon-type equations;
Du Fort-Frankel-type finite difference;
schemes;
Energy conservation;
Numerical convergence;
D O I:
暂无
中图分类号:
O29 [应用数学];
学科分类号:
070104 ;
摘要:
Recently, invariant energy-quadratization methods (IEQMs) have been introduced by Xiaofeng Yang's group to develop linear and energy-dissipation-preserving methods for nonlinear energy-dissipation systems. Following their work, two auxiliary functions are firstly introduced to rewrite the sine-Gordon equation (SGE) and coupled sine-Gordon equations (CSGEs) into equivalent systems, respectively. Then, two energy-preserving Du Fort-Frankel-type finite difference methods (EP-DFFT-FDMs) have been suggested for them, respectively. By using the discrete energy methods, the discrete energy conservative laws and convergence rates in the H1-norm have been derived, rigorously. It is worth mentioning that the proposed discrete energy is an approximation to the exact energy of the continuous problem. As hx = O( increment t), hy = O( increment t) and parameter lambda > 1/4, the current methods are stable in the H1-norm because numerical solutions obtained by them are bounded in the H1-norm. What is more, as parameter lambda > 1/4, the current methods are unconditionally stable in the L2-norm because numerical solutions obtained by them are uniformly bounded in the L2-norm. Moreover, our methods are explicit, and very easy to be implemented. However, a shortcoming of the current increment t increment t methods is that they are conditionally consistent. Namely, and hx tend to zero hy as time step increment t, spatial mesh sizes hx in x-direction and hy in y-direction tend to zero. Numerical findings support the correctness of theoretical analyses and the performance of the algorithms.(c) 2022 Elsevier B.V. All rights reserved.
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