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We explore the potential of a formulation of the Navier-Stokes equations incorporating a random description of the small-scale velocity component. This model, established from a version of the Reynolds transport theorem adapted to a…

流体动力学 · 物理学 2016-11-11 S. Kadri Harouna , E. Mémin

A method for finding reduced-order approximations of turbulent flow models is presented. The method preserves bounds on the production of turbulent energy in the sense of the $\curly{L}_2$ norm of perturbations from a notional laminar…

流体动力学 · 物理学 2013-01-22 A S Sharma

Analyzing large-scale data from simulations of turbulent flows is memory intensive, requiring significant resources. This major challenge highlights the need for data compression techniques. In this study, we apply a physics-informed Deep…

流体动力学 · 物理学 2022-04-20 Mohammadreza Momenifar , Enmao Diao , Vahid Tarokh , Andrew D. Bragg

We combine resolvent-mode decomposition with techniques from convex optimization to optimally approximate velocity spectra in a turbulent channel. The velocity is expressed as a weighted sum of resolvent modes that are dynamically…

流体动力学 · 物理学 2014-05-22 R. Moarref , M. R. Jovanovic , J. A. Tropp , A. S. Sharma , B. J. McKeon

The pressure strain correlation plays a critical role in the Reynolds stress transport modelling. Accurate modelling of the pressure strain correlation leads to proper prediction of turbulence stresses and subsequently the other terms of…

流体动力学 · 物理学 2021-03-02 J P Panda , H V Warrior

Using only a limited number of computationally expensive functions, we show a way how to construct accurate and computationally efficient approximations of the Colebrook equation for flow friction. The presented approximations are based on…

数值分析 · 数学 2020-09-07 Pavel Praks , Dejan Brkic

Direct numerical simulations are used to investigate the individual dynamics of large spherical particles suspended in a developed homogeneous turbulent flow. A definition of the direction of the particle motion relative to the surrounding…

流体动力学 · 物理学 2015-06-16 Mamadou Cisse , Holger Homann , Jeremie Bec

A turbulent mean profile for pipe flow is prescribed which closely matches experimental observations. The nature of perturbations superimposed upon this profile is then considered. Optimal growth calculations predict two distinct classes of…

流体动力学 · 物理学 2009-08-27 A. P. Willis , Y. Hwang , C. Cossu

We present measurements of relativistic scaling relations in $(2+1)$-dimensional conformal fluid turbulence from direct numerical simulations, in the weakly compressible regime. These relations were analytically derived previously in…

高能物理 - 理论 · 物理学 2017-09-13 John Ryan Westernacher-Schneider , Luis Lehner

We provide numerical simulations of an incompressible pressure-thickening and shear-thinning lubricant flowing in a plane slider bearing. We study the influence of several parameters, namely the ratio of the characteristic lengths…

流体动力学 · 物理学 2017-09-15 M. Lanzendörfer , J. Málek , K. R. Rajagopal

A central obstacle to understanding the route to turbulence in wall-bounded flows is that the flows are composed of complex, highly fluctuating, and strongly nonlinear states. In the case of pipe flow, models have deepened our understanding…

流体动力学 · 物理学 2026-02-24 Santiago J. Benavides , Dwight Barkley

Direct numerical simulations, performed with a high-order spectral-element method, are used to study coherent structures in turbulent pipe flow at friction Reynolds numbers $Re_{\tau} = 180$ and $550$. The database was analysed using…

流体动力学 · 物理学 2023-07-19 Leandra Abreu , André Cavalieri , Philipp Schlatter , Ricardo Vinuesa , Dan Henningson

We show how a complete mathematical description of a complicated physical phenomenon can be learned from observational data via a hybrid approach combining three simple and general ingredients: physical assumptions of smoothness, locality,…

流体动力学 · 物理学 2024-11-20 Daniel R. Gurevich , Matthew R. Golden , Patrick A. K. Reinbold , Roman O. Grigoriev

This paper presents a reduced-order model for the Reynolds equation for deformable structure and large displacements. It is based on the model established in [11] which is piece-wise linearized using two different methods. The advantages…

其他计算机科学 · 计算机科学 2009-11-13 A. Missoffe , J. Juillard , Denis Aubry

This study presents an experimental dataset documenting the evolution of a turbulent boundary layer downstream of a rough-to-smooth surface transition. To investigate the effect of upstream flow conditions, two groups of experiments are…

流体动力学 · 物理学 2023-08-08 Mogeng Li , Charitha M. de Silva , Daniel Chung , Dale I. Pullin , Ivan Marusic , Nicholas Hutchins

In this study, we investigate the Shallow Water Equations incorporating source terms accounting for Manning friction and a non-flat bottom topology. Our primary focus is on developing and validating numerical schemes that serve a dual…

数值分析 · 数学 2023-10-24 Guanlan Huang , Sebastiano Boscarino , Tao Xiong

This paper employs an input-output based approach to analyze convective velocities and the transport of fluctuations in turbulent channel flows. The convective velocity for a fluctuating quantity associated with streamwise-spanwise…

流体动力学 · 物理学 2021-11-16 Chang Liu , Dennice F. Gayme

Positional ordering of a two-dimensional fluid of hard disks is examined in such narrow tubes where only the nearest-neighbor interactions take place. Using the exact transfer-matrix method the transverse and longitudinal pressure…

统计力学 · 物理学 2015-05-30 S. Varga , G. Balló , P. Gurin

The reverse perturbation method [Phys. Rev. E 59, 4894 (1999)] for shearing simple liquids and measuring their viscosity is extended to the Vicsek-model (VM) of active particles [Phys. Rev. Lett. 75, 1226 (1995)] and its metric-free…

软凝聚态物质 · 物理学 2019-10-23 Arash Nikoubashman , Thomas Ihle

A resolvent-based reduced-order representation is used to capture time-averaged second-order statistics in turbulent channel flow. The recently-proposed decomposition of the resolvent operator into two distinct families related to the…

流体动力学 · 物理学 2020-08-26 Ryan M. McMullen , Kevin Rosenberg , Beverley J. McKeon