Applied Mathematics and Mechanics (English Edition) ›› 2010, Vol. 31 ›› Issue (7): 861-874.doi: https://doi.org/10.1007/s10483-010-1320-z

• Articles • 上一篇    下一篇

A streamline diffusion nonconforming finite element method for the time-dependent linearized Navier-Stokes equations

陈豫眉1,2 谢小平1   

  1. 1. School of Mathematics, Sichuan University, Chengdu 610064, P. R. China;
    2. College of Mathematics and Information, China West Normal University, Nanchong 637002, Sichuan Province, P. R. China
  • 收稿日期:2010-03-15 修回日期:2010-05-24 出版日期:2010-07-01 发布日期:2010-07-01

A streamline diffusion nonconforming finite element method for the time-dependent linearized Navier-Stokes equations

CHEN Yu-Mei1,2, XIE Xiao-Ping1   

  1. 1. School of Mathematics, Sichuan University, Chengdu 610064, P. R. China;
    2. College of Mathematics and Information, China West Normal University, Nanchong 637002, Sichuan Province, P. R. China
  • Received:2010-03-15 Revised:2010-05-24 Online:2010-07-01 Published:2010-07-01

摘要: A nonconforming finite element method of finite difference streamline diffusion type is proposed to solve the time-dependent linearized Navier-Stokes equations. The backward Euler scheme is used for time discretization. Crouzeix-Raviart nonconforming finite element approximation, namely, nonconforming (P1)2 − P0 element, is used for the velocity and pressure fields with the streamline diffusion technique to cope with usual instabilities caused by the convection and time terms. Stability and error estimates are derived with suitable norms.

Abstract: A nonconforming finite element method of finite difference streamline diffusion type is proposed to solve the time-dependent linearized Navier-Stokes equations. The backward Euler scheme is used for time discretization. Crouzeix-Raviart nonconforming finite element approximation, namely, nonconforming (P1)2 − P0 element, is used for the velocity and pressure fields with the streamline diffusion technique to cope with usual instabilities caused by the convection and time terms. Stability and error estimates are derived with suitable norms.

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