English
Related papers

Related papers: Bubbles in Turbulent Flows: Data-driven, kinematic…

200 papers

In the present paper, an aerodynamic investigation of a high-speed train is performed. In the first section of this article, a generic high-speed train against a turbulent flow is simulated, numerically. The Reynolds-Averaged Navier-Stokes…

When simulating multiscale systems, where some fields cannot be fully prescribed despite their effects on the simulation's accuracy, closure models are needed. This phenomenon is observed in turbulent fluid dynamics, where Large Eddy…

Fluid Dynamics · Physics 2025-12-01 Eduardo Vital , Jean-Marc Gratien , Yassine Ayoun , Thibault Faney , Julien Bohbot

The spatio-temporal dynamics of separation bubbles induced to form in a fully-developed turbulent boundary layer (with Reynolds number based on momentum thickness of the boundary layer of 490) over a flat plate are studied via direct…

Fluid Dynamics · Physics 2019-12-04 Wen Wu , Charles Meneveau , Rajat Mittal

We report on the Lagrangian statistics of acceleration of small (sub-Kolmogorov) bubbles and tracer particles with Stokes number St << 1 in turbulent flow. At decreasing Reynolds number, the bubble accelerations show deviations from that of…

Fluid Dynamics · Physics 2016-08-23 Varghese Mathai , Enrico Calzavarini , Jon Brons , Chao Sun , Detlef Lohse

In this paper, we address the problem of how to account for second-order statistics of turbulent flows using low-complexity stochastic dynamical models based on the linearized Navier-Stokes equations. The complexity is quantified by the…

Fluid Dynamics · Physics 2017-05-16 Armin Zare , Mihailo R. Jovanović , Tryphon T. Georgiou

Iterative coarse-graining procedure based on Wyld's perturbation expansion is applied to the problem of Navier-Stokes turbulence. It is shown that the low-order calculation gives the fixed-point Reynolds number $ Re_{fp}$ (coupling…

Fluid Dynamics · Physics 2013-08-21 Victor Yakhot

This work introduces a new neural model which follows the transport equation by design. A physical problem, the Taylor-Green vortex, defined on a bi-periodic domain, is used as a benchmark to evaluate the performance of both the standard…

Computational Engineering, Finance, and Science · Computer Science 2024-10-08 Amirmahdi Jafari

Many geophysical and astrophysical phenomena are driven by turbulent fluid dynamics, containing behaviors separated by tens of orders of magnitude in scale. While direct simulations have made large strides toward understanding geophysical…

Fluid Dynamics · Physics 2018-10-10 Jonathan S Cheng , Jonathan M Aurnou , Keith Julien , Rudie P J Kunnen

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…

Stochastic linear modelling proposed in Tissot, M\'emin & Cavalieri (J. Fluid Mech., vol. 912, 2021, A51) is based on classical conservation laws subject to a stochastic transport. Once linearised around the mean flow and expressed in the…

Fluid Dynamics · Physics 2022-07-27 Gilles Tissot , André Cavalieri , Etienne Mémin

The spatiotemporal evolution of pulsating turbulent pipe flow was predicted by deep learning. A convolutional neural network (CNN) and long short-term memory (LSTM) were employed for long-term prediction by recursively predicting the local…

Fluid Dynamics · Physics 2026-01-01 Sota Kumazawa , Yasuhiro Yoshida , Tomohiro Nimura , Akira Murata , Kaoru Iwamoto

We apply a continuous data assimilation method to the Navier-Stokes-Fourier system governing the evolution of a compressible, rotating and thermally driven fluid. A rigorous proof of the tracking property is given in the asymptotic regime…

Analysis of PDEs · Mathematics 2025-10-24 Eduard Feireisl , Wladimir Neves

In this work, we present a novel data-based approach to turbulence modelling for Large Eddy Simulation (LES) by artificial neural networks. We define the exact closure terms including the discretization operators and generate training data…

Computational Engineering, Finance, and Science · Computer Science 2019-10-09 Andrea D. Beck , David G. Flad , Claus-Dieter Munz

Recent experiments demonstrate the importance of substrate curvature for actively forced fluid dynamics. Yet, the covariant formulation and analysis of continuum models for non-equilibrium flows on curved surfaces still poses theoretical…

The fast and accurate prediction of unsteady flow becomes a serious challenge in fluid dynamics, due to the high-dimensional and nonlinear characteristics. A novel hybrid deep neural network (DNN) architecture was designed to capture the…

Fluid Dynamics · Physics 2020-01-08 Renkun Han , Yixing Wang , Yang Zhang , Gang Chen

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

We describe tests validating progress made toward acceleration and automation of hydrodynamic codes in the regime of developed turbulence by three Deep Learning (DL) Neural Network (NN) schemes trained on Direct Numerical Simulations of…

Fluid Dynamics · Physics 2018-12-06 Ryan King , Oliver Hennigh , Arvind Mohan , Michael Chertkov

In this dissertation two-dimensional buoyancy-driven flows are investigated. While usually the Navier-Stokes equations are equipped with no-slip boundary conditions here we focus on the Navier-slip conditions that, depending on the system…

Analysis of PDEs · Mathematics 2024-09-25 Fabian Bleitner

Turbulence remains a problem that is yet to be fully understood, with experimental and numerical studies aiming to fully characterise the statistical properties of turbulent flows. Such studies require huge amount of resources to capture,…

Fluid Dynamics · Physics 2022-05-31 Vijay Kag , Kannabiran Seshasayanan , Venkatesh Gopinath

We prove that there exists a weak solution to a system governing an unsteady flow of a viscoelastic fluid in three dimensions, for arbitrarily large time interval and data. The fluid is described by the incompressible Navier-Stokes…

Analysis of PDEs · Mathematics 2020-07-22 Michal Bathory , Miroslav Bulíček , Josef Málek