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Related papers: Machine learning for hydrodynamic stability

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In this paper, we train turbulence models based on convolutional neural networks. These learned turbulence models improve under-resolved low resolution solutions to the incompressible Navier-Stokes equations at simulation time. Our study…

Fluid Dynamics · Physics 2022-10-12 Björn List , Li-Wei Chen , Nils Thuerey

Solving the Reynolds-averaged Navier-Stokes equations (RANS) closed with an eddy viscosity computed through a turbulence model is still the leading approach for Computational Fluid Dynamics simulations. Unfortunately, universal models with…

Fluid Dynamics · Physics 2025-09-18 Marco Castelletti , Maurizio Quadrio

Linearized stability of incompressible viscous fluid flows in a thin spherical shell is studied by using the two-dimensional Navier--Stokes equations on a sphere. The stationary flow on the sphere has two singularities (a sink and a source)…

Classical Analysis and ODEs · Mathematics 2009-11-11 Ranis N. Ibragimov , Dmitry E. Pelinovsky

Complex spatial and temporal structures are inherent characteristics of turbulent fluid flows and comprehending them poses a major challenge. This comprehesion necessitates an understanding of the space of turbulent fluid flow…

Fluid Dynamics · Physics 2024-07-16 Tim Whittaker , Romuald A. Janik , Yaron Oz

Recent studies suggest that unstable, non-chaotic solutions of the Navier-Stokes equation may provide deep insights into fluid turbulence. In this article, we present a combined experimental and numerical study exploring the dynamical role…

Fluid Dynamics · Physics 2018-08-29 Balachandra Suri , Jeffrey Tithof , Roman O. Grigoriev , Michael F. Schatz

Conventional fluid simulations can be time consuming and energy intensive. We researched the viability of a neural network for simulating incompressible fluids in a randomized obstacle-heavy environment, as an alternative to the numerical…

Fluid Dynamics · Physics 2025-10-28 Rui Hespanha , Elliot McGuire , João Hespanha

Real-time accurate solutions of large-scale complex dynamical systems are in critical need for control, optimization, uncertainty quantification, and decision-making in practical engineering and science applications, especially digital twin…

Machine Learning · Computer Science 2023-02-22 Hai V. Nguyen , Tan Bui-Thanh

We present a space-time continuous-Galerkin finite element method for solving incompressible Navier-Stokes equations. To ensure stability of the discrete variational problem, we apply ideas from the variational multi-scale method. The…

Numerical Analysis · Mathematics 2024-11-25 Biswajit Khara , Robert Dyja , Kumar Saurabh , Anupam Sharma , Baskar Ganapathysubramanian

This paper proposes a novel particle scheme that provides convergent approximations of a weak solution of the Navier-Stokes equations for the 1-D flow of a viscous compressible fluid. Moreover, it is shown that all differential inequalities…

Analysis of PDEs · Mathematics 2023-01-12 Iasson Karafyllis , Markos Papageorgiou

This paper is concerned with probabilistic techniques for forecasting dynamical systems described by partial differential equations (such as, for example, the Navier-Stokes equations). In particular, it is investigating and comparing…

Machine Learning · Computer Science 2025-11-07 Hans Harder , Abhijeet Vishwasrao , Luca Guastoni , Ricardo Vinuesa , Sebastian Peitz

Despite its numerical challenges, finite element method is used to compute viscous fluid flow. A consensus on the cause of numerical problems has been reached; however, general algorithms---allowing a robust and accurate simulation for any…

Computational Engineering, Finance, and Science · Computer Science 2019-02-05 Bilen Emek Abali

Nonlinear and non-stationary processes are prevalent in various natural and physical phenomena, where system dynamics can change qualitatively due to bifurcation phenomena. Traditional machine learning methods have advanced our ability to…

Machine Learning · Statistics 2024-06-21 Keita Tokuda , Yuichi Katori

The predictive accuracy of the Navier-Stokes equations is known to degrade at the limits of the continuum assumption, thereby necessitating expensive and often highly approximate solutions to the Boltzmann equation. While tractable in one…

Fluid Dynamics · Physics 2023-07-25 Ashish S. Nair , Justin Sirignano , Marco Panesi , Jonathan F. MacArt

We show a case of steady flow in a granular gas that, for small shear rates, is accurately described by Navier-Stokes hydrodynamics, even for high inelasticity. The (low density) granular gas is composed of identical inelastic spheres and…

Soft Condensed Matter · Physics 2013-10-15 Francisco Vega Reyes

We develop a novel and efficient iterative scheme for solving incompressible steady Navier-Stokes equations. The method is an adaptation of the Incremental Viscosity Splitting approximation for unsteady flows to steady equations. At each…

Numerical Analysis · Mathematics 2026-05-07 Aziz Takhirov , Driss Yakoubi

We consider the inverse problem of the detection of a single body, immersed in a bounded container filled with a fluid which obeys the stationary Navier-Stokes equations, from a single measurement of force and velocity on a portion of the…

Analysis of PDEs · Mathematics 2011-07-28 Andrea Ballerini

The design of film cooling systems relies heavily on Reynolds-Averaged Navier-Stokes (RANS) simulations, which solve for mean quantities and model all turbulent scales. Most turbulent heat flux models, which are based on isotropic diffusion…

Fluid Dynamics · Physics 2019-10-09 Pedro M. Milani , Julia Ling , John K. Eaton

We develop new variational principles to study stability and equilibrium of axisymmetric flows. We show that there is an infinite number of steady state solutions. We show that these steady states maximize a (non-universal) $H$-function. We…

Fluid Dynamics · Physics 2016-08-16 Nicolas Leprovost , Bérengère Dubrulle , Pierre-Henri Chavanis

We consider a stabilization method for divergence-conforming B-spline discretizations of the incompressible Navier--Stokes problem wherein jumps in high-order normal derivatives of the velocity field are penalized across interior mesh…

Numerical Analysis · Mathematics 2022-01-28 Guoxiang Grayson Tong , David Kamensky , John A. Evans

Fluid simulation is an important research topic in computer graphics (CG) and animation in video games. Traditional methods based on Navier-Stokes equations are computationally expensive. In this paper, we treat fluid motion as point cloud…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Yu Chen , Shuai Zheng , Nianyi Wang , Menglong Jin , Yan Chang
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