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Over the last few years there have been dramatic advances in our understanding of mathematical and computational models of complex systems in the presence of uncertainty. This has led to a growth in the area of uncertainty quantification as…

Numerical Analysis · Mathematics 2013-06-04 Maziar Raissi , Padmanabhan Seshaiyer

We present and analyze a discontinuous Galerkin method for the numerical modeling of a Kelvin-Voigt thermo/poro-viscoelastic problem. We present the derivation of the model and we develop a stability analysis in the continuous setting that…

Numerical Analysis · Mathematics 2025-08-01 Stefano Bonetti , Mattia Corti

Mathematical modeling often yields linear dynamical systems in science and engineering. We change physical parameters of the system into random variables to perform an uncertainty quantification. The stochastic Galerkin method yields a…

Numerical Analysis · Mathematics 2019-09-17 Roland Pulch

We introduce and analyze a space-time hybridized discontinuous Galerkin method for the evolutionary Navier--Stokes equations. Key features of the numerical scheme include point-wise mass conservation, energy stability, and pressure…

Numerical Analysis · Mathematics 2023-07-07 Keegan L. A. Kirk , Tamás L. Horváth , Sander Rhebergen

We study an iterative low-rank approximation method for the solution of the steady-state stochastic Navier--Stokes equations with uncertain viscosity. The method is based on linearization schemes using Picard and Newton iterations and…

Numerical Analysis · Mathematics 2019-11-04 Kookjin Lee , Howard C. Elman , Bedřich Sousedík

The subject of this work is an adaptive stochastic Galerkin finite element method for parametric or random elliptic partial differential equations, which generates sparse product polynomial expansions with respect to the parametric…

Numerical Analysis · Mathematics 2025-03-28 Markus Bachmayr , Martin Eigel , Henrik Eisenmann , Igor Voulis

Although major advances have been achieved over the past decades for the reduction and identification of linear systems, deriving nonlinear low-order models still is a chal- lenging task. In this work, we develop a new data-driven framework…

Fluid Dynamics · Physics 2016-12-26 Jean-Christophe Loiseau , Steven L. Brunton

A stochastic Galerkin formulation for a stochastic system of balanced or conservation laws may fail to preserve hyperbolicity of the original system. In this work, we develop hyperbolicity-preserving stochastic Galerkin formulation for the…

Numerical Analysis · Mathematics 2020-12-21 Dihan Dai , Yekaterina Epshteyn , Akil Narayan

We study the weak Galerkin finite element method for Stokes problem. A new weak Galerkin finite element velocity-pressure space pair is presented which satisfies the discrete inf-sup condition. Based on this space pair, we establish a…

Numerical Analysis · Mathematics 2018-01-30 Tie Zhang , Tao Lin

A new discontinuous Galerkin finite element method for the Stokes equations is developed in the primary velocity-pressure formulation. This method employs discontinuous polynomials for both velocity and pressure on general…

Numerical Analysis · Mathematics 2021-05-05 Xiu Ye , Shangyou Zhang

This paper develops and analyses semi-discrete numerical method for two dimensional Vlasov-Stokes' system with periodic boundary condition. The method is based on coupling of semi-discrete discontinuous Galerkin method for the Vlasov…

Numerical Analysis · Mathematics 2023-12-18 Harsha Hutridurga , Krishan Kumar , Amiya K. Pani

It is known that standard stochastic Galerkin methods encounter challenges when solving partial differential equations with high-dimensional random inputs, which are typically caused by the large number of stochastic basis functions…

Numerical Analysis · Mathematics 2024-01-30 Guanjie Wang , Smita Sahu , Qifeng Liao

In this paper, we propose a unified numerical framework for the time-dependent incompressible Navier--Stokes equation which yields the $H^1$-, $H(\text{div})$-conforming, and discontinuous Galerkin methods with the use of different viscous…

Numerical Analysis · Mathematics 2020-11-16 Xi Chen , Yuwen Li , Corina Drapaca , John Cimbala

We present a computational study of several preconditioning techniques for the GMRES algorithm applied to the stochastic diffusion equation with a lognormal coefficient discretized with the stochastic Galerkin method. The clear block…

Numerical Analysis · Mathematics 2022-08-12 Eugenio Aulisa , Giacomo Capodaglio , Guoyi Ke

In several studies it has been observed that, when using stabilised $\mathbb{P}_k^{}\times\mathbb{P}_k^{}$ elements for both velocity and pressure, the error for the pressure is smaller, or even of a higher order in some cases, than the one…

Numerical Analysis · Mathematics 2020-09-23 Gabriel R. Barrenechea , Michał Bosy , Victorita Dolean

We present a Lagrange--Galerkin scheme free from numerical quadrature for the Navier--Stokes equations. Our idea is to use a locally linearized velocity and the backward Euler method in finding the position of fluid particle at the previous…

Numerical Analysis · Mathematics 2015-05-26 Masahisa Tabata , Shinya Uchiumi

Near-optimal computational complexity of an adaptive stochastic Galerkin method with independently refined spatial meshes for elliptic partial differential equations is shown. The method takes advantage of multilevel structure in expansions…

Numerical Analysis · Mathematics 2025-03-25 Markus Bachmayr , Henrik Eisenmann , Igor Voulis

In this work we consider a discontinuous Galerkin method for the discretization of the Stokes problem. We use $H(\textrm{div})$-conforming finite elements as they provide major benefits such as exact mass conservation and…

Numerical Analysis · Mathematics 2016-12-06 Philip L. Lederer , Joachim Schöberl

We present a reduced basis stochastic Galerkin method for partial differential equations with random inputs. In this method, the reduced basis methodology is integrated into the stochastic Galerkin method, resulting in a significant…

Numerical Analysis · Mathematics 2023-10-02 Guanjie Wang , Qifeng Liao

We present a novel approach to determine the evolution of level sets under uncertainties in the velocity fields. This leads to a stochastic description of the level sets. To compute the quantiles of random level sets, we use the stochastic…

Probability · Mathematics 2023-05-10 Markus Bambach , Stephan Gerster , Michael Herty , Aleksey Sikstel