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We propose a novel stability criterion for incompressible shear flows by combining input-output analysis and the small-gain theorem. The criterion yields an explicit threshold on the magnitude of velocity perturbations about a given base…

Fluid Dynamics · Physics 2026-03-04 Ofek Frank-Shapir , Igal Gluzman

We propose a new application of random tensor theory to studies of non-linear random flows in many variables. Our focus is on non-linear resonant systems which often emerge as weakly non-linear approximations to problems whose linearized…

Mathematical Physics · Physics 2020-03-12 Stéphane Dartois , Oleg Evnin , Luca Lionni , Vincent Rivasseau , Guillaume Valette

Coherent structures are found in many different turbulent flows and are known to drive self-sustaining processes in wall turbulence. Identifying the triadic interactions which generate coherent structures can provide insights beyond what is…

Fluid Dynamics · Physics 2024-05-20 Ugur Karban , Eduardo Martini , André V. G. Cavalieri , Peter Jordan

This paper reports several new classes of weakly unstable recurrent solutions of the 2+1-dimensional Euler equation on a square domain with periodic boundary conditions. These solutions have a number of remarkable properties which…

Fluid Dynamics · Physics 2023-08-31 Dmitriy Zhigunov , Roman O. Grigoriev

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…

Blood flow in arterial systems can be described by the three-dimensional Navier-Stokes equations within a time-dependent spatial domain that accounts for the elasticity of the arterial walls. In this article blood is treated as an…

Numerical Analysis · Mathematics 2018-08-14 Francesco Fambri , Michael Dumbser , Vincenzo Casulli

The statistical mechanical description of two-dimensional inviscid fluid turbulence is reconsidered. Using this description, we make predictions about turbulent flow in a rapidly rotating laboratory annulus. Measurements on the continuously…

Soft Condensed Matter · Physics 2009-11-11 Sunghwan Jung , P. J. Morrison , Harry L. Swinney

The first consistent model for the turbulent tachocline is presented, with the turbulent diffusivity computed within the model instead of being specified arbitrarily. For the origin of the 3D turbulence a new mechanism is proposed. Owing to…

Astrophysics · Physics 2015-06-24 K. Petrovay

A novel route to instabilities and turbulence in fluid and plasma flows is presented in kinetic Vlasov-Maxwell model. New kind of flow instabilities is shown to arise due to the availability of new kinetic energy sources which are absent in…

Plasma Physics · Physics 2015-06-19 Dhurjati Prasad Datta , Sudip Sen

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

We advance the computation of physical modal expansions for unsteady incompressible flows. Point of departure is a linearization of the Navier-Stokes equations around its fixed point in a frequency domain formulation. While the most…

Fluid Dynamics · Physics 2018-04-24 Marek Morzynski , Wojciech Szeliga , Bernd R. Noack

In this paper we present a novel, closed three-dimensional (3D) random vortex dynamics system, which is equivalent to the Navier--Stokes equations for incompressible viscous fluid flows. The new random vortex dynamics system consists of a…

Mathematical Physics · Physics 2022-09-08 Zhongmin Qian , Endre Süli , Yihuang Zhang

In this paper, sparsity-promoting regression techniques are employed to automatically identify from data relevant triadic interactions between modal structures in large Galerkin-based models of two-dimensional unsteady flows. The approach…

Fluid Dynamics · Physics 2020-07-24 Riccardo Rubini , Davide Lasagna , Andrea Da Ronch

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

Couplings in complex real-world systems are often nonlinear and scale-dependent. In many cases, it is crucial to consider a multitude of interlinked variables and the strengths of their correlations to adequately fathom the dynamics of a…

Data Analysis, Statistics and Probability · Physics 2022-10-26 Tobias Braun , K. Hauke Kraemer , Norbert Marwan

The energy cascade and diverse turbulence properties of active-grid-generated turbulence were studied in a wind tunnel via hot-wire anemometry. To this aim, two active grid protocols were considered. The first protocol is the standard…

Fluid Dynamics · Physics 2019-10-09 D. O. Mora , E. Muñiz Pladellorens , P. Riera Turró , M. Lagauzere , M. Obligado

Simulations of turbulent flows in 3D are one of the most expensive simulations in computational fluid dynamics (CFD). Many works have been written on surrogate models to replace numerical solvers for fluid flows with faster, learned,…

Fluid Dynamics · Physics 2024-03-18 Marten Lienen , David Lüdke , Jan Hansen-Palmus , Stephan Günnemann

Elastic turbulence is a spatially and temporally disordered flow state appearing in viscoelastic fluids at vanishing fluid inertia and large elasticity. The resulting flows have broad technological interest, particularly to enhance mixing…

Fluid Dynamics · Physics 2026-04-02 Zhongxuan Hou , Stefano Berti , Teodor Burghelea , Francesco Romanò

We present data driven kinematic models for the motion of bubbles in high-Re turbulent fluid flows based on recurrent neural networks with long-short term memory enhancements. The models extend empirical relations, such as Maxey-Riley (MR)…

Fluid Dynamics · Physics 2019-10-07 Zhong Yi Wan , Petr Karnakov , Petros Koumoutsakos , Themistoklis P. Sapsis

This proposed work introduces a data-assimilation-assisted approach to train neural networks, aimed at effectively reducing epistemic uncertainty in state estimates of separated flows. This method, referred to as model-consistent training,…

Fluid Dynamics · Physics 2024-08-02 Minghan Chu
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