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Journal of Zhejiang University (Science Edition)  2022, Vol. 49 Issue (5): 564-569    DOI: 10.3785/j.issn.1008-9497.2022.05.007
Mathematics and Computer Science     
Simulation of multiscale finite element method on graded meshes for two-dimensional singularly perturbed twin boundary layers problems
Meiling SUN1,2(),Shan JIANG2()
1.Department of Mathematics,Nantong Vocational University,Nantong 226007,Jiangsu Province,China
2.School of Science,Nantong University,Nantong 226019,Jiangsu Province,China
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Abstract  

To solve a two-dimensional singularly perturbed model, a multiscale finite element method on graded meshes built from the perturbed parameter is presented for capturing the twin boundary layers of convection-diffusion equations effectively. Based on the graded meshes, the multiscale basis functions are capable of subtly describing the microscopic information in the boundary layers. No wonder, it just costs a handful of computing resource and short time to achieve the accurate and efficient results, and the results are independent of the perturbed parameter with uniform stability.



Key wordssingular perturbation      adaptive meshes      twin boundary layers      multiscale finite element      uniform stability     
Received: 24 August 2021      Published: 14 September 2022
CLC:  O 241.82  
Corresponding Authors: Shan JIANG     E-mail: sunmeiling81@163.com;jiangshan@ntu.edu.cn
Cite this article:

Meiling SUN,Shan JIANG. Simulation of multiscale finite element method on graded meshes for two-dimensional singularly perturbed twin boundary layers problems. Journal of Zhejiang University (Science Edition), 2022, 49(5): 564-569.

URL:

https://www.zjujournals.com/sci/EN/Y2022/V49/I5/564


多尺度有限元法结合分层网格模拟二维奇异摄动的两端边界层问题

通过摄动系数建立分层网格,用多尺度有限元法捕捉对流扩散方程的两端边界层,研究二维奇异摄动模型。基于分层网格并利用多尺度基函数刻画了边界层的微观信息,用有限的计算资源、较短的计算时间, 得到了不依赖于摄动系数、一致稳定的模拟结果。


关键词: 奇异摄动,  自适应网格,  两端边界层,  多尺度有限元,  一致稳定 
Fig.1 Sub-domains of domain Ω
Fig.2 Exact solutions when ε=10-1 and 10-5,respectively
Fig.3 The solutions of FEM(G) and MsFEM(G) when ε=10-5
hε=10-5ε=10-6ε=10-7
NFEM误差NFEM误差NFEM误差
2+01364.510×10-31604.664×10-31924.748×10-3
2-12401.310×10-32881.362×10-33281.402×10-3
2-24483.870×10-45364.054×10-46164.189×10-4
2-38881.083×10-41 0481.142×10-41 2001.186×10-4
Table 1 FEM(G) with different parameters for errors of energy norm
hε=10-5ε=10-6ε=10-7
NMsFEM误差NMsFEM误差NMsFEM误差
2+0348.866×10-2409.084×10-2489.083×10-2
2-1602.270×10-2722.303×10-2822.329×10-2
2-21124.686×10-31344.938×10-31544.955×10-3
2-32229.228×10-42629.565×10-43009.627×10-4
Table 2 MsFEM(G) with different parameters for errors of energy norm
Fig.4 Errors of FEM(G) on NFEM=136 and MsFEM(G) on NMsFEM=112 when ε=10-5
Fig.5 Errors of FEM(G) on NFEM=240 and MsFEM(G) on NMsFEM=222 when ε=10-5
NFEM2FEM(G)CPU时间/sNMsFEM2MsFEM(G)CPU时间/s
13624.13423.3
24024960212
4482659112284
888210 27722221 106
Table 3 FEM(G) and MsFEM(G)'s CPU time when ε=10-5
Fig.6 Two methods' log-log on partition N and CPU time when ε=10-6 and 10-7
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