Blanca Ayuso de Dios
University of Hamburg
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Publication
Featured researches published by Blanca Ayuso de Dios.
Mathematical Models and Methods in Applied Sciences | 2012
Blanca Ayuso de Dios; José A. Carrillo; Chi-Wang Shu
We introduce and analyze two new semi-discrete numerical methods for the multi-dimensional Vlasov–Poisson system. The schemes are constructed by combining a discontinuous Galerkin approximation to the Vlasov equation together with a mixed finite element method for the Poisson problem. We show optimal error estimates in the case of smooth compactly supported initial data. We propose a scheme that preserves the total energy of the system.
Mathematics of Computation | 2013
Blanca Ayuso de Dios; Michael Holst; Yunrong Zhu; Ludmil Zikatanov
In this article we develop and analyze two-level and multi-level methods for the family of Interior Penalty (IP) discontinuous Galerkin (DG) discretizations of second order elliptic problems with rough coecients (exhibiting large jumps across interfaces in the domain). These methods are based on a decomposition of the DG nite element space that inherently hinges on the diusion coecient of the problem. Our analysis of the proposed preconditioners is presented for both symmetric and non-symmetric IP schemes, and we establish both robustness with respect to the jump in the coecient and near-optimality with respect to the mesh size. Following the analysis, we present a sequence of detailed numerical results which verify the theory and illustrate the performance of the methods.
Journal of Scientific Computing | 2014
Blanca Ayuso de Dios; Franco Brezzi; L. Donatella Marini; Jinchao Xu; Ludmil Zikatanov
In this paper we construct Discontinuous Galerkin approximations of the Stokes problem where the velocity field is
Computational Methods in Applied Mathematics Comput | 2012
Paola F. Antonietti; Blanca Ayuso de Dios; Susanne C. Brenner; Li-Yeng Sung
Journal of Scientific Computing | 2016
Paola F. Antonietti; Blanca Ayuso de Dios; Ilario Mazzieri; Alfio Quarteroni
H(\mathrm{div},\Omega )
arXiv: Numerical Analysis | 2013
Blanca Ayuso de Dios; Ariel L. Lombardi; Paola Pietra; Ludmil Zikatanov
arXiv: Numerical Analysis | 2013
Blanca Ayuso de Dios; Michael Holst; Yunrong Zhu; Ludmil Zikatanov
H(div,Ω)-conforming. This implies that the velocity solution is divergence-free in the whole domain. This property can be exploited to design a simple and effective preconditioner for the final linear system.
arXiv: Numerical Analysis | 2014
Blanca Ayuso de Dios; Ludmil Zikatanov
Abstract We propose and analyze several two-level non-overlapping Schwarz methods for a preconditioned weakly over-penalized symmetric interior penalty (WOPSIP) discretization of a second order boundary value problem. We show that the preconditioners are scalable and that the condition number of the resulting preconditioned linear systems of equations is independent of the penalty parameter and is of order H/h, where H and h represent the mesh sizes of the coarse and fine partitions, respectively. Numerical experiments that illustrate the performance of the proposed two-level Schwarz methods are also presented.
Mathematical Modelling and Numerical Analysis | 2016
Blanca Ayuso de Dios; Konstantin Lipnikov; Gianmarco Manzini
We consider semi-discrete discontinuous Galerkin approximations of both displacement and displacement-stress formulations of the elastodynamics problem. We prove the stability analysis in the natural energy norm and derive optimal a-priori error estimates. For the displacement-stress formulation, schemes preserving the total energy of the system are introduced and discussed. We verify our theoretical estimates on two and three dimensions test problems.
Mathematical Modelling and Numerical Analysis | 2013
Blanca Ayuso de Dios; Ivan Georgiev; Johannes Kraus; Ludmil Zikatanov
We consider an exponentially fitted discontinuous Galerkin method for advection dominated problems and propose a block solver for the resulting linear systems. In the case of strong advection the solver is robust with respect to the advection direction and the number of unknowns.