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In this paper, we develop a new discontinuous Galerkin method for solving several types of partial differential equations (PDEs) with high order spatial derivatives. We combine the advantages of local discontinuous Galerkin (LDG) method and…

Numerical Analysis · Mathematics 2020-03-13 Qi Tao , Yan Xu , Chi-Wang Shu

We discuss the development, verification, and performance of a GPU accelerated discontinuous Galerkin method for the solutions of two dimensional nonlinear shallow water equations. The shallow water equations are hyperbolic partial…

Numerical Analysis · Mathematics 2023-07-19 R Gandham , D S Medina , T Warburton

For a class of fourth order gradient flow problems, integration of the scalar auxiliary variable (SAV) time discretization with the penalty-free discontinuous Galerkin (DG) spatial discretization leads to SAV-DG schemes. These schemes are…

Numerical Analysis · Mathematics 2020-08-28 Hailiang Liu , Peimeng Yin

The high-order accurate continuous Galerkin finite element method offers attractive computational efficiency for computational fluid dynamics. A challenge is however spurious oscillations which result for convection dominated flows over…

Numerical Analysis · Mathematics 2023-11-10 Arnaud G. Malan , Jan Nordstrom

Autoregressive next-step prediction models have become the de-facto standard for building data-driven neural solvers to forecast time-dependent partial differential equations (PDEs). Denoise training that is closely related to diffusion…

Machine Learning · Computer Science 2025-03-31 Zijie Li , Anthony Zhou , Amir Barati Farimani

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

Some properties of a Local discontinuous Galerkin (LDG) algorithm are demonstrated for the problem of evaluting a second derivative $g = f_{xx}$ for a given $f$. (This is a somewhat unusual problem, but it is useful for understanding the…

Computational Physics · Physics 2014-05-26 A. H. Hakim , G. W. Hammett , E. L. Shi

Finite element-based high-order solvers of conservation laws offer large accuracy but face challenges near discontinuities due to the Gibbs phenomenon. Artificial viscosity is a popular and effective solution to this problem based on…

Numerical Analysis · Mathematics 2025-06-18 Matteo Caldana , Paola F. Antonietti , Luca Dede'

In this work, we consider the discretization of nonlinear hyperbolic systems in nonconservative form with the high-order discontinuous Galerkin spectral element method (DGSEM) based on collocation of quadrature and interpolation points…

Numerical Analysis · Mathematics 2019-02-20 Florent Renac

This work uses high-order discontinuous Galerkin discretization techniques as a generic, parameter-free, and reliable tool to accurately predict transitional and turbulent flows through medical devices. Flows through medical devices are…

Fluid Dynamics · Physics 2018-11-19 Niklas Fehn , Wolfgang A. Wall , Martin Kronbichler

We present a GPU-accelerated version of a high-order discontinuous Galerkin discretization of the unsteady incompressible Navier-Stokes equations. The equations are discretized in time using a semi-implicit scheme with explicit treatment of…

Numerical Analysis · Mathematics 2018-05-08 Ali Karakus , Noel Chalmers , Kasia Swirydowicz , Timothy Warburton

The Local Randomized Neural Networks with Discontinuous Galerkin (LRNN-DG) methods, introduced in [42], were originally designed for solving linear partial differential equations. In this paper, we extend the LRNN-DG methods to solve…

Numerical Analysis · Mathematics 2024-10-01 Jingbo Sun , Fei Wang

The incompressible Euler equations are an important model system in computational fluid dynamics. Fast high-order methods for the solution of this time-dependent system of partial differential equations are of particular interest: due to…

Numerical Analysis · Mathematics 2024-10-15 Eike Hermann Müller

In this paper, we present results of a discontinuous Galerkin (DG) scheme applied to deterministic computations of the transients for the Boltzmann-Poisson system describing electron transport in semiconductor devices. The collisional term…

Numerical Analysis · Mathematics 2015-05-13 Yingda Cheng , Irene M. Gamba , Armando Majorana , Chi-Wang Shu

The deep neural network multigrid solver (DNN-MG) combines a coarse-grid finite element simulation with a deep neural network that corrects the solution on finer grid levels, thereby improving the computational efficiency. In this work, we…

Numerical Analysis · Mathematics 2026-01-26 Robert Jendersie , Nils Margenberg , Christian Lessig , Thomas Richter

Both compressible and incompressible Navier-Stokes solvers can be used and are used to solve incompressible turbulent flow problems. In the compressible case, the Mach number is then considered as a solver parameter that is set to a small…

Fluid Dynamics · Physics 2018-12-26 Niklas Fehn , Wolfgang A. Wall , Martin Kronbichler

We study in this paper three variants of the high-order Discontinuous Galerkin (DG) method with Runge-Kutta (RK) time integration for the induction equation, analysing their ability to preserve the divergence free constraint of the magnetic…

Numerical Analysis · Mathematics 2021-03-25 Maria Han Veiga , David A Velasco-Romero , Quentin Wenger , Romain Teyssier

In this paper, we propose and analyze a numerically stable and convergent scheme for a convection-diffusion-reaction equation in the convection-dominated regime. Discontinuous Galerkin (DG) methods are considered since standard finite…

Numerical Analysis · Mathematics 2024-04-10 Satyajith Bommana Boyana , Thomas Lewis , Sijing Liu , Yi Zhang

The increasing application of cardiorespiratory simulations for diagnosis and surgical planning necessitates the development of computational methods significantly faster than the current technology. To achieve this objective, we leverage…

Numerical Analysis · Mathematics 2024-03-21 Mahdi Esmaily , Dongjie Jia

In recent years, a significant amount of attention has been paid to solve partial differential equations (PDEs) by deep learning. For example, deep Galerkin method (DGM) uses the PDE residual in the least-squares sense as the loss function…

Numerical Analysis · Mathematics 2020-06-09 Liyao Lyu , Zhen Zhang , Minxin Chen , Jingrun Chen