English
Related papers

Related papers: SPARSE: A Subgrid Particle Averaged Reynolds Stres…

200 papers

Using the volume averaging technique of Jackson (1997), we derive a set of two-fluid equations that describe the dynamics of a mono-disperse non-Brownian colloidal suspension in the semi-dilute regime. The equations are tensorial and can be…

Fluid Dynamics · Physics 2025-01-06 Dalton J. E. Harvie

The aim of this paper is to introduce a consistent velocity smoothing method for smoothed particle hydrodynamics (SPH). First the locally averaged Navier-Stokes equations are derived in a mathematically rigorous way to demonstrate the…

Fluid Dynamics · Physics 2018-07-31 Kalale Chola

The streaming instability, as an example of instabilities driven by particle feedback on a gas flow, has been proven to have a major role in controlling the formation of planetesimals. Here, we present experiments to approach this situation…

Earth and Planetary Astrophysics · Physics 2019-02-08 Niclas Schneider , Gerhard Wurm , Jens Teiser , Hubert Klahr , Vincent Carpenter

We investigate relationships between statistics obtained from filtering and from ensemble or Reynolds-averaging turbulence flow fields as a function of length scale. Generalized central moments in the filtering approach are expressed as…

Fluid Dynamics · Physics 2021-03-17 J. A. Saenz , D. Aslangil , D. Livescu

The interacting lattice gas model is used to simulate fluid flow through an open percolating porous medium with the fluid entering at the source-end and leaving from the opposite end. The shape of the steady-state concentration profile and…

Statistical Mechanics · Physics 2009-11-07 R. B. Pandey , J. F. Gettrust , D. Stauffer

The morphology of nanostructured materials exhibiting a polydisperse porous space, such as aerogels, is very open porous and fine grained. Therefore, a simulation of the deformation of a large aerogel structure resolving the nanostructure…

Numerical Analysis · Mathematics 2024-03-04 Axel Klawonn , Martin Lanser , Lucas Mager , Ameya Rege

Closure models for the turbulent scalar flux are an important source of uncertainty in Reynolds-averaged-Navier-Stokes (RANS) simulations of scalar transport. This paper presents an approach to quantify this uncertainty in simulations of…

Fluid Dynamics · Physics 2020-08-12 Zengrong Hao , Catherine Gorlé

Stress-strain relations for random packings of entangling chains under triaxial compression can exhibit strain stiffening and sustain stresses several orders-of-magnitude beyond typical granular materials. X-ray tomography reveals the…

Soft Condensed Matter · Physics 2025-02-12 Eric Brown , Kevin A. Mitchell , Alice Nasto , Athanasios Athanassiadis , Heinrich M. Jaeger

We introduce a field-wide benchmark challenge for machine learning in Reynolds-averaged Navier-Stokes (RANS) turbulence modelling. Though open-source datasets exist for training data-driven turbulence closure models, the field has been…

Fluid Dynamics · Physics 2026-04-01 Ryley McConkey , Tyler Buchanan , Tess Smidt , Abigail Bodner , Richard Dwight , Paola Cinnella

A new parallel algorithm utilizing partitioned global address space (PGAS) programming model to achieve high scalability is reported for particle tracking in direct numerical simulations of turbulent flow. The work is motivated by the…

Computational Physics · Physics 2020-05-28 Dhawal Buaria , P. K. Yeung

High Reynolds Homogeneous Isotropic Turbulence is fully described within the Navier-Stokes (NS) equations, which are notoriously difficult to solve numerically. Engineers, interested primarily in describing turbulence at a reduced range of…

Using the Lagrangian transport of momentum, the Reynolds stress can be expressed in terms of basic turbulence parameters. The Reynolds stress gradient represents the lateral transport of stream-wise momentum, balanced by the u2 transport,…

Fluid Dynamics · Physics 2019-12-11 T. -W. Lee

Eulerian-Lagrangian models of particle-laden (multiphase) flows describe fluid flow and particle dynamics in the Eulerian and Lagrangian frameworks respectively. Regardless of whether the flow is turbulent or laminar, the particle dynamics…

Deep learning-based point cloud processing plays an important role in various vision tasks, such as autonomous driving, virtual reality (VR), and augmented reality (AR). The submanifold sparse convolutional network (SSCN) has been widely…

Signal Processing · Electrical Eng. & Systems 2022-10-17 Zilun Wang , Wendong Mao , Peixiang Yang , Zhongfeng Wang , Jun Lin

We develop a stochastic model for Lagrangian velocity as it is observed in experimental and numerical fully developed turbulent flows. We define it as the unique statistically stationary solution of a causal dynamics, given by a stochastic…

Smoothed particle hydrodynamics (SPH) has been extensively studied in computer graphics to animate fluids with versatile effects. However, SPH still suffers from two numerical difficulties: the particle deficiency problem, which will…

Graphics · Computer Science 2020-01-29 Xiaowei He , Huamin Wang , Guoping Wang , Hongan Wang , Enhua Wu

Despite a cost-effective option in practical engineering, Reynolds-averaged Navier-Stokes simulations are facing the ever-growing demand for more accurate turbulence models. Recently, emerging machine learning techniques are making…

Fluid Dynamics · Physics 2021-05-04 Chao Jiang

A large eddy simulation wall model is developed based on a formal interpretation of quasi-equilibrium that governs the momentum balance integrated in the wall-normal direction. The model substitutes the law-of-the-wall velocity profile for…

Fluid Dynamics · Physics 2022-02-02 Mitchell Fowler , Tamer A. Zaki , Charles Meneveau

Dynamics of a one-dimensional system of Brownian particles with short-range repulsive interaction (diameter sigma) is studied with a liquid-theoretical approach. The mean square displacement, the two-particle displacement correlation, and…

Statistical Mechanics · Physics 2013-12-06 T. Ooshida , S. Goto , T. Matsumoto , A. Nakahara , M. Otsuki

Cloud microphysics has important consequences for climate and weather phenomena, and inaccurate representations can limit forecast accuracy. While atmospheric models increasingly resolve storms and clouds, the accuracy of the underlying…

Atmospheric and Oceanic Physics · Physics 2024-03-04 Shivani Sharma , David Greenberg