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We introduce a provably stable variant of neural ordinary differential equations (neural ODEs) whose trajectories evolve on an energy functional parametrised by a neural network. Stable neural flows provide an implicit guarantee on…

Machine Learning · Computer Science 2020-03-19 Stefano Massaroli , Michael Poli , Michelangelo Bin , Jinkyoo Park , Atsushi Yamashita , Hajime Asama

By analogy with the kinetic theory of gases, most turbulence modeling strate- gies rely on an eddy viscosity to model the unresolved turbulent fluctuations. How- ever, the ratio of unresolved to resolved scales - very much like a degree of…

Fluid Dynamics · Physics 2016-08-24 Marcello Righi

In this paper, we consider numerical approximations of a binary fluid-surfactant phase-field model coupled with the fluid flow, in which the system is highly nonlinear that couples the incompressible Navier-Stokes equations and two…

Numerical Analysis · Mathematics 2018-04-13 Xiaofeng Yang

We develop a method to estimate space-time flow statistics from a limited set of known data. While previous work has focused on modeling spatial or temporal statistics independently, space-time statistics carry fundamental information about…

Fluid Dynamics · Physics 2020-01-08 Aaron Towne , Adrian Lozano-Duran , Xiang Yang

The lattice Boltzmann method can be used to simulate flow through porous media with full geometrical resolution. With such a direct numerical simulation, it becomes possible to study fundamental effects which are difficult to assess either…

Computational Engineering, Finance, and Science · Computer Science 2015-08-13 Ehsan Fattahia , Christian Waluga , Barbara Wohlmuth , Ulrich Rüde , Michael Manhart , Rainer Helmig

We calculate in this work the Navier-Stokes transport coefficients from the Boltzmann equation for $d$-dimensional inelastic Maxwell models. By granular gas we mean here a low density system of identical spheres that lose a fraction of…

Statistical Mechanics · Physics 2015-06-18 Moisés G. Chamorro , Vicente Garzó , Francisco Vega Reyes

Numerical simulations of turbulence provide non-intrusive access to all the resolved scales, although they often invoke idealizations that can compromise realism. In contrast, experimental measurements probe the true flow with lesser…

Fluid Dynamics · Physics 2021-09-22 Tamer A. Zaki , Mengze Wang

Accurately modeling the dynamics of high-density ratio ($\mathcal{O}(10^5)$) two-phase flows is important for many material science and manufacturing applications. This work considers numerical simulations of molten metal oscillations in…

Fluid Dynamics · Physics 2025-01-03 Ali Rabeh , Makrand A. Khanwale , John J. Lee , Baskar Ganapathysubramanian

Hybrid Reynolds-averaged Navier Stokes large eddy simulation (RANS LES) methods have become popular for simulation of massively separated flows at high Reynolds numbers due to their reduced computational cost and good accuracy. The current…

Fluid Dynamics · Physics 2021-02-19 Gaurav Kumar , Ashoke De , Harish Gopalan

We evaluate an efficient overset grid method for two-dimensional and three-dimensional particulate flows for small numbers of particles at finite Reynolds number. The rigid particles are discretised using moving overset grids overlaid on a…

Computational Physics · Physics 2017-05-24 A. R. Koblitz , S. Lovett , N. Nikiforakis , W. D. Henshaw

The study of fluids has been a topic of intense research for several hundred years. Over the years, this has further increased due to improved computational facility, which makes it easy to numerically simulate the fluid dynamics, which was…

Fluid Dynamics · Physics 2021-03-05 Soumen Roy

This work is concerned with the numerical investigation of the dynamics of stopping vortex formation in the uniform flow past a wedge mounted on a wall for channel Reynolds number $Re_c=1560$. The streamfunction-vorticity ($\psi$-$\omega$)…

Fluid Dynamics · Physics 2024-05-06 Jiten C Kalita

Efficient simulation of the Navier-Stokes equations for fluid flow is a long standing problem in applied mathematics, for which state-of-the-art methods require large compute resources. In this work, we propose a data-driven approach that…

Computer Vision and Pattern Recognition · Computer Science 2022-11-10 Jonathan Tompson , Kristofer Schlachter , Pablo Sprechmann , Ken Perlin

Numerical simulation of fluids plays an essential role in modeling many physical phenomena, such as weather, climate, aerodynamics and plasma physics. Fluids are well described by the Navier-Stokes equations, but solving these equations at…

Fluid Dynamics · Physics 2022-04-27 Dmitrii Kochkov , Jamie A. Smith , Ayya Alieva , Qing Wang , Michael P. Brenner , Stephan Hoyer

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

There are two components in this work that allow solutions of the turbulent channel problem: one is the Galilean-transformed Navier-Stokes equation which gives a theoretical expression for the Reynolds stress; and the second the maximum…

Fluid Dynamics · Physics 2019-07-24 T. -W. Lee

We performed numerical simulations of a homogeneous swarm of bubbles rising at large Reynolds number, Re = 760 with volume fractions ranging from 1% to 10%. We consider a simplified model in which the interfaces are not resolved, but which…

Fluid Dynamics · Physics 2024-03-06 Rémi Zamansky , Florian Le Roy de Bonneville , Frederic Risso

Modelling interfacial dynamics with soluble surfactants in a multiphase system is a challenging task. Here, we consider the numerical approximation of a phase-field surfactant model with fluid flow. The nonlinearly coupled model consists of…

Computational Physics · Physics 2020-03-02 Guangpu Zhu , Jisheng Kou , Shuyu Sun , Jun Yao , Aifen Li

Normalizing flows have shown great promise for modelling flexible probability distributions in a computationally tractable way. However, whilst data is often naturally described on Riemannian manifolds such as spheres, torii, and hyperbolic…

Machine Learning · Statistics 2020-12-10 Emile Mathieu , Maximilian Nickel

In this visualisation the instantaneous local velocity is expressed in terms of four components to capture the development of and interactions between coherent structures in turbulent flows. It is then possible to isolate the terms linked…

Fluid Dynamics · Physics 2009-10-13 Trinh Khanh Tuoc