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In this paper we consider fully discrete approximations with inf-sup stable mixed finite element methods in space to approximate the Navier-Stokes equations. A continuous downscaling data assimilation algorithm is analyzed in which…

Numerical Analysis · Mathematics 2019-04-15 Bosco García-Archilla , Julia Novo

We present a fourth-order projection method with adaptive mesh refinement (AMR) for numerically solving the incompressible Navier-Stokes equations (INSE) with subcycling in time. Our method features (i) a reformulation of INSE so that the…

Numerical Analysis · Mathematics 2025-09-08 Shubo Zhao , Qinghai Zhang

Generating an accurate solution of the Navier--Stokes equations using physics--informed neural networks (PINNs) for higher Reynolds numbers in the corners of a lid--driven cavity problem is challenging. In this paper, we improve the…

Computational Physics · Physics 2025-01-03 Nityananda Roy , Robert Dürr , Andreas Bück , S. Sundar

In this article, we design and analyze an arbitrary-order stabilized finite element method to approximate the unique continuation problem for laminar steady flow described by the linearized incompressible Navier--Stokes equation. We derive…

Numerical Analysis · Mathematics 2023-01-16 Erik Burman , Deepika Garg , Janosch Preuss

The paper introduces a geometrically unfitted finite element method for the numerical solution of the tangential Navier--Stokes equations posed on a passively evolving smooth closed surface embedded in $\mathbb{R}^3$. The discrete…

Numerical Analysis · Mathematics 2023-10-16 Maxim A. Olshanskii , Arnold Reusken , Paul Schwering

We present a second-order monolithic method for solving incompressible Navier--Stokes equations on irregular domains with quadtree grids. A semi-collocated grid layout is adopted, where velocity variables are located at cell vertices, and…

Numerical Analysis · Mathematics 2022-06-01 Hyuntae Cho , Yesom Park , Myungjoo Kang

We introduce a family of bi-grid schemes in finite elements for solving 2D incompressible Navier-Stokes equations in velocity and pressure $(u,p)$. The new schemes are based on projection methods and use two pairs of FEM spaces, a sparse…

Numerical Analysis · Mathematics 2018-08-29 Hyam Abboud , Clara Al Kosseifi , Jean-Paul Chehab

Nonlinear feedback design via state-dependent Riccati equations is well established but unfeasible for large-scale systems because of computational costs. If the system can be embedded in the class of linear parameter-varying (LPV) systems…

Optimization and Control · Mathematics 2023-07-27 Jan Heiland , Steffen W. R. Werner

Predicting outcomes and planning interactions with the physical world are long-standing goals for machine learning. A variety of such tasks involves continuous physical systems, which can be described by partial differential equations…

Machine Learning · Computer Science 2020-01-22 Philipp Holl , Vladlen Koltun , Nils Thuerey

We consider a numerical approach for the incompressible surface Navier-Stokes equation. The approach is based on the covariant form and uses discrete exterior calculus (DEC) in space and a semi-implicit discretization in time. The…

Numerical Analysis · Mathematics 2020-11-26 Ingo Nitschke , Sebastian Reuther , Axel Voigt

We investigate the temporal accuracy of two generalized-$\alpha$ schemes for the incompressible Navier-Stokes equations. The conventional approach treats the pressure with the backward Euler method while discretizing the remainder of the…

Numerical Analysis · Mathematics 2020-09-28 Ju Liu , Ingrid S. Lan , Oguz Z. Tikenogullari , Alison L. Marsden

The treatment of complex geometries in Computational Fluid Dynamics applications is a challenging endeavor, which immersed boundary and cut-cell techniques can significantly simplify by alleviating the meshing process required by…

Computational Physics · Physics 2022-11-22 Alejandro Quirós Rodríguez , Tomas Fullana , Vincent Le Chenadec , Taraneh Sayadi

Exponential stabilization to time-dependent trajectories for the incompressible Navier-Stokes equations is achieved with explicit feedback controls. The fluid is contained in two-dimensional spatial domains and the control force is, at each…

Analysis of PDEs · Mathematics 2025-03-10 Sérgio S. Rodrigues , Dagmawi A. Seifu

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

Accurate simulation of fluid flow in porous media is challenging due to complex pore-space geometries and the computational cost of solving the Navier-Stokes equations. This difficulty is particularly important when repeated simulations are…

Machine Learning · Computer Science 2026-05-21 Rafał Topolnicki , Paweł Dłotko , Maciej Matyka

This paper provides mathematical analysis of an elementary fully discrete finite difference method applied to inhomogeneous (non-constant density and viscosity) incompressible Navier-Stokes system on a bounded domain. The proposed method…

Numerical Analysis · Mathematics 2023-02-28 Kohei Soga

In this paper, we investigate the incompressible steady Navier-Stokes system with Navier slip boundary condition in a two-dimensional channel. As long as the width of cross-section of the channel grows more slowly than the linear growth,…

Analysis of PDEs · Mathematics 2022-11-23 Kaijian Sha , Yun Wang , Chunjing Xie

Stabilised mixed velocity-pressure formulations are one of the widely-used finite element schemes for computing the numerical solutions of laminar incompressible Navier-Stokes. In these formulations, the Newton-Raphson scheme is employed to…

Computational Engineering, Finance, and Science · Computer Science 2020-07-15 Chennakesava Kadapa , Wulf G Dettmer , Djordje Peric

We provide a convergence analysis for a new fractional time-stepping technique for the incompressible Navier-Stokes equations based on direction splitting. This new technique is of linear complexity, unconditionally stable and convergent,…

Numerical Analysis · Mathematics 2011-01-20 Jean-Luc Guermond , Peter D. Minev , Abner J. Salgado

Machine learning (ML) tools such as encoder-decoder convolutional neural networks (CNN) can represent incredibly complex nonlinear functions which map between combinations of images and scalars. For example, CNNs can be used to map…

Machine Learning · Computer Science 2021-10-27 Alexander Scheinker
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