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Continuum fluid dynamic models based on the Navier-Stokes equations have previously been used to simulate granular media undergoing fluid-like shearing. These models, however, typically fail to predict the flow behaviour in confined…

Fluid Dynamics · Physics 2024-03-05 Duncan Dockar , M. H. Lakshminarayana Reddy , Matthew K. Borg , S. Kokou Dadzie

Almost all investigations of turbulent flows in academia and in the industry utilize some degree of turbulence modeling. Of the available approaches to turbulence modeling Reynolds Stress Models have the highest potential to replicate…

Fluid Dynamics · Physics 2018-03-07 J. P. Panda , H. V. Warrior

The flow-induced deformation of a thin, elastic splitter plate attached to the rear of a circular cylinder and subjected to laminar pulsatile inflow is investigated. The cylinder and elastic splitter plate are contained within a narrow…

Fluid Dynamics · Physics 2016-12-21 Anup Kundu , Atul K. Soti , Rajneesh Bhardwaj , Mark C. Thompson

A new class of integro-partial differential equation models is derived for the prediction of granular flow dynamics. These models are obtained using a novel limiting averaging method (inspired by techniques employed in the derivation of…

Chaotic Dynamics · Physics 2015-06-26 Denis Blackmore , Roman Samulyak , Anthony Rosato

Turbulent flow past an equilateral triangular cylinder with splitter plate inserted downstream is numerically tested for different gap ratios (0, 0.5, 1, 1.5, 2) and plate dimensions (0, 1, 1.5) on the flow field and heat transfer…

Fluid Dynamics · Physics 2022-06-28 Smruti Ranjan Jena , Amit Kumar Naik , Amaresh Dalal , Ganesh Natarajan

This paper addresses the problem of obtaining low-order models of fluid flows for the purpose of designing robust feedback controllers. This is challenging since whilst many flows are governed by a set of nonlinear, partial…

Proper-orthogonal decomposition (POD) based reduced-order models (ROM) of structurally dominant fluid flow can support a wide range of engineering applications. Yet, although they perform well for unsteady laminar flows, their…

Fluid Dynamics · Physics 2025-03-11 Haroon Imtiaz , Imran Akhtar , Muhammad R. Hajj

Mixed-dimensional mathematical models for flow in fractured media have been prevalent in the modeling community for almost two decades, utilizing the explicit representation of fractures by lower-dimensional manifolds embedded in the…

Design exploration or optimization using computational fluid dynamics (CFD) is commonly used in the industry. Geometric variation is a key component of such design problems, especially in turbulent flow scenarios, which involves running…

Machine Learning · Computer Science 2024-12-04 Shinjan Ghosh , Julian Busch , Georgia Olympia Brikis , Biswadip Dey

This paper presents a new Computational Fluid Dynamics database, developed at ONERA, to support the advancement of machine learning techniques for aerodynamic field prediction. It contains 468 Reynolds-Averaged Navier-Stokes simulations…

Machine Learning · Computer Science 2025-05-13 Jacques Peter , Quentin Bennehard , Sébastien Heib , Jean-Luc Hantrais-Gervois , Frédéric Moëns

We describe a method to address efficiently problems of two-phase flow in the regime of low particle Reynolds number and negligible Brownian motion. One of the phases is an incompressible continuous fluid and the other a discrete…

Condensed Matter · Physics 2016-08-31 Stefan Schwarzer

We present a model appropriate to the initial motion (2-3 chords of travel) of a flat-plate airfoil accelerating in an inviscid fluid. The separated flow structures are represented as vortex sheets in the conventional manner and similarity…

Fluid Dynamics · Physics 2021-05-19 A. C. DeVoria , K. Mohseni

We present numerical simulations of laminar and turbulent channel flow of an elastoviscoplastic fluid. The non-Newtonian flow is simulated by solving the full incompressible Navier-Stokes equations coupled with the evolution equation for…

Fluid Dynamics · Physics 2018-07-17 Marco Edoardo Rosti , Daulet Izbassarov , Outi Tammisola , Sarah Hormozi , Luca Brandt

This paper presents a model to simulate behavior of particle-laden slurry in a horizontal perforated wellbore with the goal of quantifying fluid and particle distribution between the perforations. There are two primary phenomena that…

Fluid Dynamics · Physics 2024-07-24 Egor Dontsov

Flow through porous, elastically deforming media is present in a variety of natural contexts ranging from large-scale geophysics to cellular biology. In the case of incompressible constituents, the porefluid pressure acts as a Lagrange…

Fluid Dynamics · Physics 2022-06-30 Nicholas J. Derr , Chris H. Rycroft

The present study assesses RANS-based turbulence models to simulate isothermal flow in a combustor representing a constituent can combustor of can-annular configuration used in jet engines. Two-equation models (standard $k-\epsilon$,…

Fluid Dynamics · Physics 2024-06-25 Aishvarya Kumar , Ram Prakash Bharti

In this work, a two-dimensional mathematical model is developed to study the flow patterns and volumetric flow penetrations in the flow channel over the porous electrode layered system in vanadium flow battery with serpentine flow field…

Soft Condensed Matter · Physics 2016-11-01 Xinyou Ke , Joseph M. Prahl , J. Iwan D. Alexander , Robert F. Savinell

Detailed understanding of the coupling between fluid flow and solid deformation in porous media is crucial for the development biomedical devices and novel energy technologies relating to a wide range of geological and biological processes.…

Fluid Dynamics · Physics 2021-09-22 Francisco J. Carrillo

In fluid physics, data-driven models to enhance or accelerate solution methods are becoming increasingly popular for many application domains, such as alternatives to turbulence closures, system surrogates, or for new physics discovery. In…

Computational fluid dynamics (CFD) solvers employing two-equation eddy viscosity models are the industry standard for simulating turbulent flows using the Reynolds-averaged Navier-Stokes (RANS) formulation. While these methods are…

Machine Learning · Computer Science 2024-10-25 Shinjan Ghosh , Amit Chakraborty , Georgia Olympia Brikis , Biswadip Dey