Moreover, we combine this new stabilized finite element method with the two-level method to give a new two-level stabilized finite element method for the Stokes eigenvalue problem. The convergence of this new stabilized method is proved and the optimal priori error estimates for the eigenfunctions and eigenvalues are also obtained. This new method is based on multiscale enrichment, and is derived from the Stokes eigenvalue problem itself. In this paper, we first propose a new stabilized finite element method for the Stokes eigenvalue problem. Janu| Juan Wen, Pengzhan Huang, Ya-Ling He The Two-Level Stabilized Finite Element Method Based on Multiscale Enrichment for the Stokes Eigenvalue Problem Finally, we illustrate the analysis with some numerical experiments. Then, we formulate an iterative algorithm for the computation of the null control and we prove a convergence result. The proof relies on an appropriate inverse function argument. First, we establish a local controllability result. This paper is devoted to the theoretical and numerical analysis of the null controllability of a quasi-linear parabolic equation.
Marín-Gayte Theoretical and numerical local null controllability of a quasi-linear parabolic equation in dimensions 2 and 3 Finally, the superconvergence rate of O(h^3)-order is proved for the eigenvalue approximation and the numerical experiment is provided to confirm the theoretical analysis. Then a superconvergence result of O(h^3/2)-order for the pressure approximation and the velocity gradient approximation under the condition of strong regular mesh triangulation are obtained. Firstly, we derive the superclose property of the interpolation function. In this paper we consider the stable P1 – P1 finite element pair solving the Stokes eigenvalue problem and derive some superconvergence results based on the interpolation post-processing technique. Latest Articlesįebru| Ying Sheng, Tie Zhang, Zixing Pan Superconvergence of the finite element method for the Stokes eigenvalue problem Rescale offers academic users up to 500 core hours on their HPC cloud.
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