scispace - formally typeset
V

Veselin Dobrev

Researcher at Lawrence Livermore National Laboratory

Publications -  52
Citations -  1348

Veselin Dobrev is an academic researcher from Lawrence Livermore National Laboratory. The author has contributed to research in topics: Finite element method & Polygon mesh. The author has an hindex of 16, co-authored 50 publications receiving 958 citations. Previous affiliations of Veselin Dobrev include Texas A&M University.

Papers
More filters
Journal ArticleDOI

High-Order Curvilinear Finite Element Methods for Lagrangian Hydrodynamics

TL;DR: This paper presents a general framework for high-order Lagrangian discretization of these compressible shock hydrodynamics equations using curvilinear finite elements for any finite dimensional approximation of the kinematic and thermodynamic fields.
Journal ArticleDOI

MFEM: a modular finite element methods library

TL;DR: MFEM as mentioned in this paper is an open-source, lightweight, flexible and scalable C++ library for modular finite element methods that features arbitrary high-order finite element meshes and spaces, support for a wide variety of discretization approaches and emphasis on usability, portability, and highperformance computing efficiency.
Journal ArticleDOI

Two‐level preconditioning of discontinuous Galerkin approximations of second‐order elliptic equations

TL;DR: This paper reviews some known and proposes some new preconditioning methods for a number of discontinuous Galerkin finite element approximations for elliptic problems of second order and presents numerical experiments for 3‐D model problem showing uniform convergence of the constructed methods.
Journal ArticleDOI

Two-Level Convergence Theory for Multigrid Reduction in Time (MGRIT)

TL;DR: A two-grid convergence theory for the parallel-in-time scheme known as multigrid reduction in time (MGRIT), as it is implemented in the open-source package XBraid, and presents a two-level MGRIT convergence analysis for linear problems where the spatial discretization matrix can be diagonalized.