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The aim of this paper is to give a systematic mathematical interpretation of the diffusion problem on which Graph Neural Networks (GNNs) models are based. The starting point of our approach is a dissipative functional leading to dynamical…

Numerical Analysis · Mathematics 2023-12-19 Lidia Aceto , Pietro Antonio Grassi

We extend the entropy stable high order nodal discontinuous Galerkin spectral element approximation for the non-linear two dimensional shallow water equations presented by Wintermeyer et al. [N. Wintermeyer, A. R. Winters, G. J. Gassner,…

Numerical Analysis · Mathematics 2018-09-26 Niklas Wintermeyer , Andrew R. Winters , Gregor J. Gassner , Timothy Warburton

We present an entropy stable nodal discontinuous Galerkin spectral element method (DGSEM) for the two-layer shallow water equations on two dimensional curvilinear meshes. We mimic the continuous entropy analysis on the semi-discrete level…

Numerical Analysis · Mathematics 2024-02-14 Patrick Ersing , Andrew R. Winters

We propose a new family of high order staggered semi-implicit discontinuous Galerkin (DG) methods for the simulation of natural convection problems. Assuming small temperature fluctuations, the Boussinesq approximation is valid and the flow…

Computational Physics · Physics 2019-12-05 Saray Busto , Maurizio Tavelli , Walter Boscheri , Michael Dumbser

Partial differential equations (PDEs) provide a mathematical foundation for simulating and understanding intricate behaviors in both physical sciences and engineering. With the growing capabilities of deep learning, data$-$driven approaches…

Machine Learning · Computer Science 2025-10-14 Narayan S Iyer , Bivas Bhaumik , Ram S Iyer , Satyasaran Changdar

Numerical simulation of flow problems and wave propagation in heterogeneous media has important applications in many engineering areas. However, numerical solutions on the fine grid are often prohibitively expensive, and multiscale model…

Numerical Analysis · Mathematics 2019-09-30 Siu Wun Cheung , Eric T. Chung , Wing Tat Leung

This work discusses the application of an affine reconstructed nodal DG method for unstructured grids of triangles. Solving the diffusion terms in the DG method is non-trivial due to the solution representations being piecewise continuous.…

Computational Physics · Physics 2021-04-20 Yang Song , Bhuvana Srinivasan

Kinetic schemes for compressible flow of gases are constructed by exploiting the connection between Boltzmann equation and the Navier-Stokes equations. This connection allows us to construct a flux splitting for the Navier-Stokes equations…

Numerical Analysis · Computer Science 2015-06-11 Praveen Chandrashekar

The discontinuous Galerkin (DG) algorithm is a representative high order method in Computational Fluid Dynamics (CFD) area which possesses considerable mathematical advantages such as high resolution, low dissipation, and dispersion.…

Mathematical Software · Computer Science 2022-09-07 Zhe Dai , Liang D , Yueqin Wang , Fang Wang , Li Ming , Jian Zhang

Discontinuous Galerkin (DG) methods are promising high order discretizations for unsteady compressible flows. Here, we focus on Numerical Weather Prediction (NWP). These flows are characterized by a fine resolution in $z$-direction and low…

Numerical Analysis · Mathematics 2025-06-02 Philipp Birken , Andreas Dedner , Robert Klöfkorn

We present the recent development of hybridizable and embedded discontinuous Galerkin (DG) methods for wave propagation problems in fluids, solids, and electromagnetism. In each of these areas, we describe the methods, discuss their main…

Numerical Analysis · Mathematics 2018-07-03 Pablo Fernandez , Alexandra Christophe , Sebastien Terrana , Ngoc-Cuong Nguyen , Jaime Peraire

This paper generalizes the earlier work on the energy-based discontinuous Galerkin method for second-order wave equations to fourth-order semilinear wave equations. We first rewrite the problem into a system with a second-order spatial…

Numerical Analysis · Mathematics 2022-07-25 Lu Zhang

This work examines the development of an entropy conservative (for smooth solutions) or entropy stable (for discontinuous solutions) space-time discontinuous Galerkin (DG) method for systems of non-linear hyperbolic conservation laws. The…

Physics-informed neural networks (PINNs) are promising to replace conventional partial differential equation (PDE) solvers by offering more accurate and flexible PDE solutions. However, they are hampered by the relatively slow convergence…

Machine Learning · Computer Science 2023-05-16 Mohammad H. Taufik , Tariq Alkhalifah

Nonlinear differential equations are challenging to solve numerically and are important to understanding the dynamics of many physical systems. Deep neural networks have been applied to help alleviate the computational cost that is…

Numerical Analysis · Mathematics 2020-10-27 Bryce Chudomelka , Youngjoon Hong , Hyunwoo Kim , Jinyoung Park

We develop an entropy-stable nodal discontinuous Galerkin (DG) scheme for the Euler equations with gravity, which is also well-balanced with respect to general equilibrium solutions, including both hydrostatic and moving equilibria. The…

Numerical Analysis · Mathematics 2026-03-10 Yuchang Liu , Wei Guo , Yan Jiang , Mengping Zhang

In this paper, we demonstrate the efficiency of using semi-Lagrangian discontinuous Galerkin methods to solve the drift-kinetic equation using graphic processing units (GPUs). In this setting we propose a second order splitting scheme and a…

Computational Physics · Physics 2023-03-23 Lukas Einkemmer , Alexander Moriggl

In this paper, we present consistent and inconsistent discontinuous Galerkin methods for incompressible Euler and Navier-Stokes equations with the kinematic pressure, Bernoulli function and EMAC function. Semi- and fully discrete energy…

Numerical Analysis · Mathematics 2021-03-02 Xi Chen , Yuwen Li , Corina Drapaca , John Cimbala

This paper investigates a numerical solution of Allen-Cahn equation with constant and degenerate mobility, with polynomial and logarithmic energy functionals, with deterministic and random initial functions, and with advective term in one,…

Numerical Analysis · Mathematics 2025-03-13 Mustafa Kütük , Hamdullah Yücel

We present a new approach to using neural networks to approximate the solutions of variational equations, based on the adaptive construction of a sequence of finite-dimensional subspaces whose basis functions are realizations of a sequence…

Machine Learning · Computer Science 2021-06-01 Mark Ainsworth , Justin Dong
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