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We consider two-phase fluid deformable surfaces as model systems for biomembranes. Such surfaces are modeled by incompressible surface Navier-Stokes-Cahn-Hilliard-like equations with bending forces. We derive this model using the…

Numerical Analysis · Mathematics 2023-08-03 Elena Bachini , Veit Krause , Ingo Nitschke , Axel Voigt

High Reynolds numbers Navier-Stokes equations are believed to break self-similarity concerning both spatial and temporal properties: correlation functions of different orders exhibit distinct decorrelation times and anomalous spatial…

Fluid Dynamics · Physics 2012-10-04 Luca Biferale , Enrico Calzavarini , Federico Toschi

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

By means of high-resolution numerical simulations, we compare the statistical properties of homogeneous and isotropic turbulence to those of the Navier-Stokes equation where small-scale vortex filaments are strongly depleted, thanks to a…

Fluid Dynamics · Physics 2020-03-04 Michele Buzzicotti , Luca Biferale , Federico Toschi

Nudging is an important data assimilation technique where partial field measurements are used to control the evolution of a dynamical system and/or to reconstruct the entire phase-space configuration of the supplied flow. Here, we apply it…

Fluid Dynamics · Physics 2020-02-12 P. Clark Di Leoni , A. Mazzino , L. Biferale

We show that Lagrangian measurements in active turbulence bear imprints of turbulent and anomalous streaky hydrodynamics leading to a self-selection of persistent trajectories - Levy walks - over diffusive ones. This emergent dynamical…

Fluid Dynamics · Physics 2022-08-26 Rahul K. Singh , Siddhartha Mukherjee , Samriddhi Sankar Ray

The constants and functions in Reynolds-averaged Navier Stokes (RANS) turbulence models are coupled. Consequently, modifications of a RANS model often negatively impact its basic calibrations, which is why machine-learned augmentations are…

Fluid Dynamics · Physics 2023-10-17 Yuanwei Bin , George Huang , Robert Kunz , Xiang I A Yang

This paper introduces a new robust formulation for local correlation-based laminar-to-turbulent transition models. This mechanism is incorporated into Reynolds-Averaged Navier-Stokes (RANS) equations, coupled with the Spalart-Allmaras (SA)…

Fluid Dynamics · Physics 2025-11-03 Valerio D'Alessandro , Matteo Falone , Luca Giammichele , Renato Ricci

We study the two-dimensional incompressible Navier-Stokes equations in a channel $\Omega=(0,L)\times(0,H)$ with small viscosity $\varepsilon\ll1$, an $\varepsilon$-Navier slip condition on the horizontal walls, and a viscous inflow…

Analysis of PDEs · Mathematics 2026-02-24 Yan Guo , Zhuolun Yang

We study the statistical properties of stationary, isotropic and homogeneous turbulence in two-dimensional (2D) flows, focusing on the direct cascade, that is on wave-numbers large compared to the integral scale, where both energy and…

Statistical Mechanics · Physics 2024-08-29 Malo Tarpin , Léonie Canet , Carlo Pagani , Nicolás Wschebor

Reynolds-averaged Navier-Stokes (RANS) equations are widely used in engineering turbulent flow simulations. However, RANS predictions may have large discrepancies due to the uncertainties in modeled Reynolds stresses. Recently, Wang et al.…

Fluid Dynamics · Physics 2018-09-11 Jin-Long Wu , Heng Xiao , Eric Paterson

Accurate simulation of turbulent flows remains a challenge due to the high computational cost of direct numerical simulations (DNS) and the limitations of traditional turbulence models. This paper explores a novel approach to augmenting…

Fluid Dynamics · Physics 2025-02-17 Jonas Luther , Patrick Jenny

Turbulence remains one of the central open problems in classical physics, largely due to the absence of a closed dynamical description of the Reynolds stress. Existing approaches typically rely either on local constitutive assumptions or on…

Fluid Dynamics · Physics 2026-03-25 Alejandro Sevilla

In this paper, we investigate the hemodynamics of a left atrium (LA) by proposing a computational model suitable to provide physically meaningful fluid dynamics indications and detailed blood flow characterization. In particular, we…

Fluid Dynamics · Physics 2022-07-08 Alberto Zingaro , Luca Dede' , Filippo Menghini , Alfio Quarteroni

Computational fluid dynamics models based on Reynolds-averaged Navier--Stokes equations with turbulence closures still play important roles in engineering design and analysis. However, the development of turbulence models has been stagnant…

Fluid Dynamics · Physics 2019-10-04 Heng Xiao , Jin-Long Wu , Sylvain Laizet , Lian Duan

Motivated by a similar approach for Born-Oppenheimer molecular dynamics, this paper proposes an extended "shadow" Lagrangian density for quantum states of superfluids. The extended Lagrangian contains an additional field variable that is…

Numerical Analysis · Mathematics 2021-01-13 Patrick Henning , Anders M. N. Niklasson

The dynamics of transitional flows are governed by an interplay between the non-normal linear dynamics and quadratic nonlinearity in the incompressible Navier-Stokes equations. In this work, we propose a framework for nonlinear stability…

Fluid Dynamics · Physics 2021-04-28 Aniketh Kalur , Peter Seiler , Maziar S. Hemati

We consider incompressible flows between two transversely vibrating solid walls and construct an asymptotic expansion of solutions of the Navier-Stokes equations in the limit when both the amplitude of vibrations and the thickness of the…

Fluid Dynamics · Physics 2011-08-16 Konstantin Ilin , Andrey Morgulis

Two-dimensional turbulence governed by the so-called $\alpha$ turbulence equations, which include the surface quasi-geostrophic equation ($\alpha=1$), the Navier--Stokes system ($\alpha=2$), and the governing equation for a shallow flow on…

Chaotic Dynamics · Physics 2007-05-23 Chuong V. Tran

We propose a method for the data-driven inference of temporal evolutions of physical functions with deep learning. More specifically, we target fluid flows, i.e. Navier-Stokes problems, and we propose a novel LSTM-based approach to predict…

Machine Learning · Computer Science 2019-03-06 Steffen Wiewel , Moritz Becher , Nils Thuerey