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In this paper, we develop the numerical theory of decoupled modified characteristic finite element method with different subdomain time steps for the mixed stabilized formulation of nonstationary dual-porosity-Navier-Stokes model. Based on…

Numerical Analysis · Mathematics 2020-08-19 Luling Cao , Yinnian He , Jian Li

In this paper we propose a novel arbitrary high order accurate semi-implicit space-time discontinuous Galerkin method for the solution of the two dimensional incompressible Navier-Stokes equations on staggered unstructured triangular…

Numerical Analysis · Mathematics 2014-12-04 Maurizio Tavelli , Michael Dumbser

Combining the characteristic method and the local discontinuous Galerkin method with carefully constructing numerical fluxes, we design the variational formulations for the time-dependent convection-dominated Navier-Stokes equations in…

Computational Physics · Physics 2017-04-03 Shuqin Wang , Weihua Deng , Yujiang Wu , Jinyun Yuan

The Navier--Stokes (NS) equations describe fluid dynamics through a high-dimensional, nonlinear system of partial differential equations (PDEs). Despite their fundamental importance, their behavior in turbulent regimes remains incompletely…

Mathematical Physics · Physics 2025-04-04 Alexander Migdal

A discontinuous Galerkin pressure correction numerical method for solving the incompressible Navier-Stokes equations is formulated and analyzed. We prove unconditional stability of the propose scheme. Convergence of the discrete velocity is…

Numerical Analysis · Mathematics 2021-09-24 Rami Masri , Chen Liu , Beatrice Riviere

This article aims at developing a high order pressure-based solver for the solution of the 3D compressible Navier-Stokes system at all Mach numbers. We propose a cell-centered discretization of the governing equations that splits the fluxes…

Numerical Analysis · Mathematics 2021-03-17 Walter Boscheri , Lorenzo Pareschi

We present a parametric family of semi-implicit second order accurate numerical methods for non-conservative and conservative advection equation for which the numerical solutions can be obtained in a fixed number of forward and backward…

Numerical Analysis · Mathematics 2023-12-01 Peter Frolkovič , Svetlana Krišková , Michaela Rohová , Michal Žeravý

In this paper, we present an original derivation process of a non-hydrostatic shallow water-type model which aims at approximating the incompressible Euler and Navier-Stokes systems with free surface. The closure relations are obtained by…

Numerical Analysis · Mathematics 2016-08-24 Marie-Odile Bristeau , Anne Mangeney , Jacques Sainte-Marie , Nicolas Seguin

This paper deals with a fully discrete numerical scheme for the incompressible Chemotaxis(Keller-Segel)-Navier-Stokes system. Based on a discontinuous Galerkin finite element scheme in the spatial directions, a semi-implicit first-order…

Numerical Analysis · Mathematics 2026-04-16 Bikram Bir , Harsha Hutridurga , Amiya K. Pani

We aim to solve the incompressible Navier-Stokes equations within the complex microstructure of a porous material. Discretizing the equations on a fine grid using a staggered (e.g., marker-and-cell, mixed FEM) scheme results in a nonlinear…

Numerical Analysis · Mathematics 2025-10-28 Kangan Li , Yashar Mehmani

The developments over the last five decades concerning numerical discretisations of the incompressible Navier--Stokes equations have lead to reliable tools for their approximation: those include stable methods to properly address the…

Numerical Analysis · Mathematics 2025-08-12 Dominic Breit , Andreas Prohl , Jörn Wichmann

In recent years, Physics-Informed Neural Networks (PINNs) have emerged as a powerful and robust framework for solving nonlinear differential equations across a wide range of scientific and engineering disciplines, including biology,…

Fluid Dynamics · Physics 2025-11-19 Ritik Pal , Soubhik Mukherjee , Urmi Dutta , Arghya Choudhury

We propose a method for the data-driven inference of temporal evolutions of physical functions with deep learning. More specifically, we target fluid flows, i.e. Navier-Stokes problems, and we propose a novel LSTM-based approach to predict…

Machine Learning · Computer Science 2019-03-06 Steffen Wiewel , Moritz Becher , Nils Thuerey

This paper presents an enriched Galerkin (EG) finite element method for the incompressible Navier--Stokes equations. The method augments continuous piecewise linear velocity spaces with elementwise bubble functions, yielding a locally…

Numerical Analysis · Mathematics 2025-11-26 Chun Song , Minfu Feng

Efficient and energy stable high order time marching schemes are very important but not easy to construct for the study of nonlinear phase dynamics. In this paper, we propose and study two linearly stabilized second order semi-implicit…

Numerical Analysis · Mathematics 2019-09-04 Lin Wang , Haijun Yu

Recently, a new approach for the stabilization of the incompressible Navier-Stokes equations for higher Reynolds numbers was introduced based on the nonlinear differential filtering of solutions on every time step of a discrete scheme. In…

Numerical Analysis · Mathematics 2013-04-16 Maxim A. Olshanskii , Xin Xiong

When dealing with shallow water simulations, the velocity profile is often assumed to be constant along the vertical axis. However, since in many applications this is not the case, modeling errors can be significant. Hence, in this work, we…

Numerical Analysis · Mathematics 2025-01-15 C. Caballero-Cárdenas , I. Gómez-Bueno , A. del Grosso , J. Koellermeier , T. Morales de Luna

The numerical solution of the Stokes equations on an evolving domain with a moving boundary is studied based on the arbitrary Lagrangian-Eulerian finite element method and a second-order projection method along the trajectories of the…

Numerical Analysis · Mathematics 2023-10-13 Qiqi Rao , Jilu Wang , Yupei Xie

Symplectic integrators offer vastly superior performance over traditional numerical techniques for conservative dynamical systems, but their application to \emph{dissipative} systems is inherently difficult due to dissipative systems' lack…

A machine-learning strategy for investigating the stability of fluid flow problems is proposed herein. The goal is to provide a simple yet robust methodology to find a nonlinear mapping from the parametric space to an indicator representing…

Fluid Dynamics · Physics 2026-01-06 David J. Silvester