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This paper devises a novel lowest-order conforming virtual element method (VEM) for planar linear elasticity with the pure displacement/traction boundary condition. The main trick is to view a generic polygon $K$ as a new one…

Numerical Analysis · Mathematics 2022-01-13 Jianguo Huang , Sen Lin , Yue Yu

This paper presents a new numerical method for the compressible Navier-Stokes equations governing the flow of an ideal isentropic gas. To approximate the continuity equation, the method utilizes a discontinuous Galerkin discretization on…

Numerical Analysis · Mathematics 2012-06-21 Trygve K. Karper

We present a family of Virtual Element Methods for three-dimensional linear elasticity problems based on the Hellinger-Reissner variational principle. A convergence and stability analysis is developed. Moreover, using the hybridization…

Numerical Analysis · Mathematics 2023-06-01 Michele Visinoni

A constructive numerical approximation of the two-dimensional unsteady stochastic Navier-Stokes equations of an incompressible fluid is proposed via a pseudo-compressibility technique involving a parameter $\epsilon$. Space and time are…

Numerical Analysis · Mathematics 2022-05-02 Jad Doghman

In the present work we generalize the curvilinear Virtual Element technology, introduced for a simple linear scalar problem in a previous work, to generic 2D solid mechanic problems in small deformations. Such generalization also includes…

Numerical Analysis · Mathematics 2020-02-19 E. Artioli , L. Beirão da Veiga , F. Dassi

The classical Smagorinsky model's solution is an approximation to a (resolved) mean velocity. Since it is an eddy viscosity model, it cannot represent a flow of energy from unresolved fluctuations to the (resolved) mean velocity. This model…

Numerical Analysis · Mathematics 2022-05-04 Farjana Siddiqua , Xihui Xie

We consider the Navier-Stokes equations in a channel with a narrowing and walls of varying curvature. By applying the empirical interpolation method to generate an affine parameter dependency, the offline-online procedure can be used to…

Numerical Analysis · Mathematics 2020-06-24 Martin Hess , Annalisa Quaini , Gianluigi Rozza

We present a novel high order semi-implicit hybrid finite volume/virtual element numerical scheme for the solution of compressible flows on Voronoi tessellations. The method relies on the flux splitting of the compressible Navier-Stokes…

Numerical Analysis · Mathematics 2024-05-24 Walter Boscheri , Saray Busto , Michael Dumbser

We present a low order virtual element discretization for time dependent Maxwell's equations, which allow for the use of general polyhedral meshes. Both the semi- and fully-discrete schemes are considered. We derive optimal a priori…

Numerical Analysis · Mathematics 2021-05-26 L. Beirão da Veiga , F. Dassi , G. Manzini , L. Mascotto

A refined a priori error analysis of the lowest order (linear) nonconforming Virtual Element Method (VEM) for approximating a model Poisson problem is developed in both 2D and 3D. A set of new geometric assumptions is proposed on shape…

Numerical Analysis · Mathematics 2019-05-17 Shuhao Cao , Long Chen

We present recent finite element numerical results on a model convection-diffusion problem in the singular perturbed case when the convection term dominates the problem. We compare the standard Galerkin discretization using the linear…

Numerical Analysis · Mathematics 2023-02-16 Constantin Bacuta , Daniel Hayes , Tyler O'Grady

We develop a unified framework for the design and analysis of high-order nonconforming virtual element methods for nonlinear fourth-order reaction--diffusion problems in two dimensions, with emphasis on clamped, Navier, and…

Numerical Analysis · Mathematics 2026-02-17 Dibyendu Adak , David Mora , Alberth Silgado

It is well known that the solution of topology optimization problems may be affected both by the geometric properties of the computational mesh, which can steer the minimization process towards local (and non-physical) minima, and by the…

Numerical Analysis · Mathematics 2016-12-28 Paola F. Antonietti , Matteo Bruggi , Simone Scacchi , Marco Verani

We propose and analyze a space-time virtual element method for the discretization of the heat equation in a space-time cylinder, based on a standard Petrov-Galerkin formulation. Local discrete functions are solutions to a heat equation…

Numerical Analysis · Mathematics 2024-02-13 Sergio Gómez , Lorenzo Mascotto , Andrea Moiola , Ilaria Perugia

The focus of the present paper is on developing a Virtual Element Method for Darcy and Brinkman equations. In [15] we presented a family of Virtual Elements for Stokes equations and we defined a new Virtual Element space of velocities such…

Numerical Analysis · Mathematics 2017-02-06 Giuseppe Vacca

In this work we propose and analyze a novel Hybrid High-Order discretization of a class of (linear and) nonlinear elasticity models in the small deformation regime which are of common use in solid mechanics. The proposed method is valid in…

Numerical Analysis · Mathematics 2017-07-10 Michele Botti , Daniele Di Pietro , Pierre Sochala

In this present paper we consider a full divergence-free of high order virtual finite element algorithm to approximate the stationary inductionless magnetohydrodynamic model on polygonal meshes. More precisely, we choice appropriate virtual…

Analysis of PDEs · Mathematics 2023-10-19 Xianghai Zhou , Haiyan Su

We consider the Navier-Stokes equations in a channel with a narrowing of varying height. The model is discretized with high-order spectral element ansatz functions, resulting in 6372 degrees of freedom. The steady-state snapshot solutions…

Numerical Analysis · Mathematics 2019-04-29 Martin W. Hess , Annalisa Quaini , Gianluigi Rozza

This article presents a priori error estimates of the miscible displacement of one incompressible fluid by another through a porous medium characterized by a coupled system of nonlinear elliptic and parabolic equations. The study utilizes…

Numerical Analysis · Mathematics 2024-01-04 Sarvesh Kumar , Devika Shylaja

White paper: The aim of this work is to apply and analyze machine learning methods for uncertainty quantification of turbulence models. In this work we investigate the classical and data-driven variants of the eigenspace perturbation…

Fluid Dynamics · Physics 2022-11-04 Marcel Matha , Karsten Kucharczyk
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