Research Outputs

Now showing 1 - 2 of 2
  • Publication
    Analysis of DG approximations for Stokes problem based on velocity-pseudostress formulation
    (Numerical Methods for Partial Differential Equations, 2017) ;
    Bustinza, Rommel
    ;
    SĂ¡nchez, Felipe
    In this article, we first discuss the well posedness of a modified LDG scheme of Stokes problem, considering a velocity-pseudostress formulation. The difficulty here relies on the fact that the application of classical Babuška-Brezzi theory is not easy, so we proceed in a nonstandard way. For uniqueness, we apply a discrete version of Fredholm's alternative theorem, while the a priori error analysis is done introducing suitable projections of exact solution. As a result, we prove that the method is convergent, and under suitable regularity assumptions on the exact solution, the optimal rate of convergence is guaranteed. Next, we explore two stabilizations to the previous scheme, by adding least squares type terms. For these cases, well posedness and the a priori error estimates are proved by the application of standard theory. We end this work with some numerical experiments considering our third scheme, whose results are in agreement with the theoretical properties we deduce.
  • Publication
    A posteriori error analysis of an augmented dual-mixed method in linear elasticity with mixed boundary conditions
    (International Journal of Numerical Analysis and Modeling, 2019) ; ;
    GonzĂ¡lez, MarĂ­a
    We consider the augmented mixed finite element method introduced in [7] for the equations of plane linear elasticity with mixed boundary conditions. We develop an a posteriori error analysis based on the Ritz projection of the error and obtain an a posteriori error estimator that is reliable and efficient, but that involves a non-local term. Then, introducing an auxiliary function, we derive fully local reliable a posteriori error estimates that are locally efficient up to the elements that touch the Neumann boundary. We provide numerical experiments that illustrate the performance of the corresponding adaptive algorithm and support its use in practice.