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We consider flux-corrected finite element discretizations of 3D convection-dominated transport problems and assess the computational efficiency of algorithms based on such approximations. The methods under investigation include…

Numerical Analysis · Mathematics 2024-01-15 Abhinav Jha , Ondřej Pártl , Naveed Ahmed , Dmitri Kuzmin

This work discusses the performance of a modern numerical scheme for fluid dynamical problems on modern high-performance computing architectures. Our code implements a spatial nodal discontinuous Galerkin scheme that we test up to an order…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-08 Filipp Sporykhin , Holger Homann

Discontinuous Galerkin (DG) methods offer an enormous flexibility regarding local grid refinement and variation of polynomial degrees for a variety of different problem classes. With a focus on diffusion problems, we consider DG…

Numerical Analysis · Mathematics 2013-01-01 Kolja Brix , Claudio Canuto , Wolfgang Dahmen

In this work, an approximate family of implicit multiderivative Runge-Kutta (MDRK) time integrators for stiff initial value problems is presented. The approximation procedure is based on the recent Approximate Implicit Taylor method (Baeza…

Numerical Analysis · Mathematics 2023-02-07 Jeremy Chouchoulis , Jochen Schütz

In this work we exploit agglomeration based $h$-multigrid preconditioners to speed-up the iterative solution of discontinuous Galerkin discretizations of the Stokes and Navier-Stokes equations. As a distinctive feature $h$-coarsened mesh…

Computational Physics · Physics 2017-09-13 Lorenzo Botti , Alessandro Colombo , Francesco Bassi

This paper presents robust discontinuous Galerkin methods for the incompressible Navier-Stokes equations on moving meshes. High-order accurate arbitrary Lagrangian-Eulerian formulations are proposed in a unified framework for both…

Computational Physics · Physics 2021-03-17 Niklas Fehn , Johannes Heinz , Wolfgang A. Wall , Martin Kronbichler

For a large class of fully nonlinear parabolic equations, which include gradient flows for energy functionals that depend on the solution gradient, the semidiscretization in time by implicit Runge-Kutta methods such as the Radau IIA methods…

Numerical Analysis · Mathematics 2016-06-14 Peer C. Kunstmann , Buyang Li , Christian Lubich

We study temporal step size control of explicit Runge-Kutta methods for compressible computational fluid dynamics (CFD), including the Navier-Stokes equations and hyperbolic systems of conservation laws such as the Euler equations. We…

The incompressible Navier-Stokes equations are solved in a channel, using a Discontinuous Galerkin method over staggered grids. The resulting linear systems are studied both in terms of the structure and in terms of the spectral features of…

Numerical Analysis · Mathematics 2021-12-07 Mariarosa Mazza , Matteo Semplice , Stefano Serra-Capizzano , Elena Travaglia

A new high order accurate semi-implicit space-time Discontinuous Galerkin method on staggered grids, for the simulation of viscous incompressible flows on two-dimensional domains is presented. The designed scheme is of the Arbitrary…

Numerical Analysis · Mathematics 2020-03-17 Francesco Lohengrin Romeo

We provide a note on continuous-stage Runge-Kutta methods (csRK) for solving initial value problems of first-order ordinary differential equations. Such methods, as an interesting and creative extension of traditional Runge-Kutta (RK)…

Numerical Analysis · Mathematics 2018-05-28 Wensheng Tang

In this article we design a finite volume semi-implicit IMEX scheme for the incompressible Navier-Stokes equations on evolving Chimera meshes. We employ a time discretization technique that separates explicit and implicit terms which…

Numerical Analysis · Mathematics 2023-08-08 Michele Giuliano Carlino , Walter Boscheri

In this paper two new families of arbitrary high order accurate spectral DG finite element methods are derived on staggered Cartesian grids for the solution of the inc.NS equations in two and three space dimensions. Pressure and velocity…

Numerical Analysis · Mathematics 2016-12-06 Francesco Fambri , Michael Dumbser

We consider Implicit-Explicit (IMEX) Runge-Kutta (R-K) schemes for hyperbolic systems with stiff relaxation in the so-called diffusion limit. In such regime the system relaxes towards a convection-diffusion equation. The first objective of…

Numerical Analysis · Mathematics 2015-05-30 S. Boscarino , L. Pareschi , G. Russo

In this paper, we use an implicit two-derivative deferred correction time discretization approach and combine it with a spatial discretization of the discontinuous Galerkin spectral element method to solve (non-)linear PDEs. The resulting…

Numerical Analysis · Mathematics 2022-07-13 Jonas Zeifang , Jochen Schuetz

Parallel-in-time methods, such as multigrid reduction-in-time (MGRIT) and Parareal, provide an attractive option for increasing concurrency when simulating time-dependent PDEs in modern high-performance computing environments. While these…

Numerical Analysis · Mathematics 2021-03-04 Hans De Sterck , Robert D. Falgout , Stephanie Friedhoff , Oliver A. Krzysik , Scott P. MacLachlan

The present works is focused on studying bifurcating solutions in compressible fluid dynamics. On one side, the physics of the problem is thoroughly investigated using high-fidelity simulations of the compressible Navier-Stokes equations…

Numerical Analysis · Mathematics 2022-12-21 Niccolò Tonicello , Andrea Lario , Gianluigi Rozza , Gianmarco Mengaldo

This work provides reliable a posteriori error estimates for Runge-Kutta discontinuous Galerkin approximations of nonlinear convection-diffusion systems. The classes of systems we study are quite general with a focus on convection-dominated…

Numerical Analysis · Mathematics 2025-10-13 Andreas Dedner , Jan Giesselmann , Kiwoong Kwon , Tristan Pryer

Multiphysics systems are driven by multiple processes acting simultaneously, and their simulation leads to partitioned systems of differential equations. This paper studies the solution of partitioned systems of differential equations using…

Numerical Analysis · Mathematics 2019-12-04 Mahesh Narayanamurthi , Adrian Sandu

Neural networks have proven to be efficient surrogate models for tackling partial differential equations (PDEs). However, their applicability is often confined to specific PDEs under certain constraints, in contrast to classical PDE solvers…

Machine Learning · Computer Science 2023-10-03 Hoyun Choi , Sungyeop Lee , B. Kahng , Junghyo Jo
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