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Neural network observers (NNOs) are proposed for real-time estimation of fluid flows, addressing a key challenge in flow control: obtaining real-time flow states from a limited set of sparse and noisy sensor data. For this task, we propose…

Fluid Dynamics · Physics 2025-11-06 Tarcísio C. Déda , William R. Wolf , Scott T. M. Dawson , Brener L. O. Ramos

We investigate a lattice model representing a granular gas in a thin channel. We deduce the hydrodynamic description for the model from the microscopic dynamics in the large system limit, including the lowest finite-size corrections. The…

Soft Condensed Matter · Physics 2018-06-19 A. Baldassarri , A. Puglisi , A. Prados

For low enough flow rates, turbulent channel flow displays spatial modulations of large wavelengths. This phenomenon has recently been interpreted as a linear instability of the turbulent flow. We question here the ability of linear…

Fluid Dynamics · Physics 2024-06-21 P. V. Kashyap , Y. Duguet , O. Dauchot

Estimation of the initial state of turbulent channel flow from limited data is investigated using an adjoint-variational approach. The data are generated from a reference direct numerical simulation (DNS) which is sub-sampled at different…

Fluid Dynamics · Physics 2021-07-01 Mengze Wang , Tamer A. Zaki

In this paper, we propose normalizing flows (NF) as a novel probability density function (PDF) turbulence model (NF-PDF model) for the Reynolds-averaged Navier-Stokes (RANS) equations. We propose to use normalizing flows in two different…

Fluid Dynamics · Physics 2021-01-12 Deniz A. Bezgin , Nikolaus A. Adams

The nonequilibrium dynamics of a binary Lennard-Jones mixture in a simple shear flow is investigated by means of molecular dynamics simulations. The range of temperature investigated covers both the liquid, supercooled and glassy states,…

Soft Condensed Matter · Physics 2009-11-07 Ludovic Berthier , Jean-Louis Barrat

We propose a general formalism, within large deviation theory, giving access to the exact statistics of fluctuations of ballistically transported conserved quantities in homogeneous, stationary states. The formalism is expected to apply to…

Statistical Mechanics · Physics 2020-12-09 Benjamin Doyon , Jason Myers

We propose a unified method for the large space-time scaling limit of \emph{linear} collisional kinetic equations in the whole space. The limit is of \emph{fractional} diffusion type for heavy tail equilibria with slow enough decay, and of…

Analysis of PDEs · Mathematics 2023-02-22 Emeric Bouin , Clément Mouhot

Despite their well-known limitations, Reynolds-Averaged Navier-Stokes (RANS) models are still the workhorse tools for turbulent flow simulations in today's engineering application. For many practical flows, the turbulence models are by far…

Computational Physics · Physics 2018-09-11 H. Xiao , J. -L. Wu , J. -X. Wang , R. Sun , C. J. Roy

The no-slip boundary condition results in a velocity shear forming in fluid flow near a solid surface. This shear flow supports the turbulence characteristic of fluid flow near boundaries at Reynolds numbers above $\approx1000$ by making…

Fluid Dynamics · Physics 2018-08-28 Brian F. Farrell , Petros J. Ioannou , Marios-Andreas Nikolaidis

First-order relativistic conformal hydrodynamics in a general (hydrodynamic) frame is characterized by a shear viscosity coefficient and two UV-regulator parameters. Within a certain range of these parameters, the equilibrium is stable and…

High Energy Physics - Theory · Physics 2023-12-12 Navid Abbasi , Ali Davody , Sara Tahery

The integration of interpretability and generalisability in data-driven turbulence modelling remains a fundamental challenge for computational fluid dynamics applications. This study yields a generalisable advancement of the $k$-$\omega$…

Fluid Dynamics · Physics 2025-07-02 Mario J. Rincón , Martino Reclari , Xiang I. A. Yang , Mahdi Abkar

Normalizing Flows (NF) are Generative models which transform a simple prior distribution into the desired target. They however require the design of an invertible mapping whose Jacobian determinant has to be computable. Recently introduced,…

Machine Learning · Computer Science 2025-09-18 Vincent Souveton , Arnaud Guillin , Jens Jasche , Guilhem Lavaux , Manon Michel

We use Direct Numerical Simulations (DNS) of the forced Navier-Stokes equation for a 3-dimensional incompressible fluid in order to test recent theoretical predictions. We study the two- and three-point spatio-temporal correlation functions…

Global stability analysis and direct numerical simulation (DNS) are performed to study boundary layer flows with an isolated roughness element. Wall-attached cuboids with aspect ratios $\eta=1$ and $\eta=0.5$ are investigated for fixed…

Fluid Dynamics · Physics 2022-10-05 Rong Ma , Krishnan Mahesh

Stationary states of Navier-Stokes fluids have been proposed to be described equivalently by several alternative equations, besides the NS equation itself. In particular equivalence between the NS evolution and a reversible. It is natural…

Statistical Mechanics · Physics 2020-06-30 Giovanni Gallavotti

Numerical simulations of turbulent flows at realistic Reynolds numbers generally rely on filtering out small scales from the Navier Stokes equations and modeling their impact through the Reynolds stress tensor ${\tau}_{ij}$. Traditional…

Fluid Dynamics · Physics 2026-01-28 Flavio Tuteri , Alexandros Alexakis , Sergio Chibbaro

We consider the hydrodynamic limit in the macroscopic regime of the coupled system of stochastic differential equations, $ d\lambda_t^i=\frac{1}{\sqrt{N}} dW_t^i - V'(\lambda_t^i) dt+ \frac{\beta}{2N} \sum_{j\not=i}…

Probability · Mathematics 2019-03-05 Jeremie Unterberger

We study correlations of hydrodynamic fluctuations in shear flow analytically and also by dissipative particle dynamics~(DPD) simulations. The hydrodynamic equations are linearized around the macroscopic velocity field and then solved by a…

Fluid Dynamics · Physics 2019-05-02 Xin Bian , Mingge Deng , George Em Karniadakis

The success of recurrent neural networks (RNNs) has been demonstrated in many applications related to turbulence, including flow control, optimization, turbulent features reproduction as well as turbulence prediction and modeling. With this…

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