scholarly journals Competing flow and collision effects in a monodispersed liquid–solid fluidized bed at a moderate Archimedes number

2021 ◽  
Vol 927 ◽  
Author(s):  
Yinuo Yao ◽  
Craig S. Criddle ◽  
Oliver B. Fringer
Keyword(s):  
Reynolds Number ◽  
Particle Velocity ◽  
Reynolds Numbers ◽  
Particle Dynamics ◽  
Velocity Fluctuations ◽  
Anisotropic Particle ◽  
Particle Reynolds Number ◽  
Intermediate Particle ◽  
Archimedes Number ◽  
Hydrodynamic Effects

We study the effects of fluid–particle and particle–particle interactions in a three-dimensional monodispersed reactor with unstable fluidization. Simulations were conducted using the immersed boundary method for particle Reynolds numbers of 20–70 with an Archimedes number of 23 600. Two different flow regimes were identified as a function of the particle Reynolds number. For low particle Reynolds numbers ( $20 < Re_p < 40$ ), the porosity is relatively low and the particle dynamics are dominated by interparticle collisions that produce anisotropic particle velocity fluctuations. The relative importance of hydrodynamic effects increases with increasing particle Reynolds number, leading to a minimized anisotropy in the particle velocity fluctuations at an intermediate particle Reynolds number. For high particle Reynolds numbers ( $Re_p > 40$ ), the particle dynamics are dominated by hydrodynamic effects, leading to decreasing and more anisotropic particle velocity fluctuations. A sharp increase in the anisotropy occurs when the particle Reynolds number increases from 40 to 50, corresponding to a transition from a regime in which collision and hydrodynamic effects are equally important (regime 1) to a hydrodynamic-dominated regime (regime 2). The results imply an optimum particle Reynolds number of roughly 40 for the investigated Archimedes number of 23 600 at which mixing in the reactor is expected to peak, which is consistent with reactor studies showing peak performance at a similar particle Reynolds number and with a similar Archimedes number. Results also show that maximum effective collisions are attained at intermediate particle Reynolds number. Future work is required to relate optimum particle Reynolds number to Archimedes number.

scholarly journals Hydrodynamic Trapping of Particles in an Expansion-Contraction Microfluidic Device

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Ruijin Wang
Keyword(s):  
Reynolds Number ◽  
Microfluidic Device ◽  
Hot Spot ◽  
Force Balance ◽  
Trapping Efficiency ◽  
Particle Sizes ◽  
Particle Trapping ◽  
Particle Reynolds Number ◽  
Drag Forces ◽  
Hydrodynamic Effects

Manipulation and sorting of particles utilizing microfluidic phenomena have been a hot spot in recent years. Here, we present numerical investigations on particle trapping techniques by using intrinsic hydrodynamic effects in an expansion-contraction microfluidic device. One emphasis is on the underlying fluid dynamical mechanisms causing cross-streamlines migration of the particles in shear and vortical flows. The results show us that the expansion-contraction geometric structure is beneficial to particle trapping according to its size. Particle Reynolds number and aspect ratio of the channel will influence the trapping efficiency greatly because the force balance between inertial lift and vortex drag forces is the intrinsic reason. Especially, obvious inline particles contribution presented when the particle Reynolds number being unit. In addition, we selected three particle sizes (2, 7, and 15 μm) to examine the trapping efficiency.

scholarly journals Reynolds number trend of hierarchies and scale interactions in turbulent boundary layers

2017 ◽  
Vol 375 (2089) ◽  
pp. 20160077 ◽  
Author(s):  
W. J. Baars ◽  
N. Hutchins ◽  
I. Marusic
Keyword(s):  
Reynolds Number ◽  
Large Scale ◽  
Reynolds Numbers ◽  
Shear Layers ◽  
Wall Turbulence ◽  
Small Scale ◽  
Velocity Fluctuations ◽  
Scale Interaction ◽  
High Reynolds ◽  
Near Wall

Small-scale velocity fluctuations in turbulent boundary layers are often coupled with the larger-scale motions. Studying the nature and extent of this scale interaction allows for a statistically representative description of the small scales over a time scale of the larger, coherent scales. In this study, we consider temporal data from hot-wire anemometry at Reynolds numbers ranging from Re τ ≈2800 to 22 800, in order to reveal how the scale interaction varies with Reynolds number. Large-scale conditional views of the representative amplitude and frequency of the small-scale turbulence, relative to the large-scale features, complement the existing consensus on large-scale modulation of the small-scale dynamics in the near-wall region. Modulation is a type of scale interaction, where the amplitude of the small-scale fluctuations is continuously proportional to the near-wall footprint of the large-scale velocity fluctuations. Aside from this amplitude modulation phenomenon, we reveal the influence of the large-scale motions on the characteristic frequency of the small scales, known as frequency modulation. From the wall-normal trends in the conditional averages of the small-scale properties, it is revealed how the near-wall modulation transitions to an intermittent-type scale arrangement in the log-region. On average, the amplitude of the small-scale velocity fluctuations only deviates from its mean value in a confined temporal domain, the duration of which is fixed in terms of the local Taylor time scale. These concentrated temporal regions are centred on the internal shear layers of the large-scale uniform momentum zones, which exhibit regions of positive and negative streamwise velocity fluctuations. With an increasing scale separation at high Reynolds numbers, this interaction pattern encompasses the features found in studies on internal shear layers and concentrated vorticity fluctuations in high-Reynolds-number wall turbulence. This article is part of the themed issue ‘Toward the development of high-fidelity models of wall turbulence at large Reynolds number’.

Mixing of Matter by a Falling Spherical Particle in a Still Liquid

2015 ◽  
Author(s):  
Toru Koso
Keyword(s):  
Reynolds Number ◽  
Spherical Particle ◽  
Mixing Time ◽  
Reynolds Numbers ◽  
Fluid Viscosity ◽  
Liquid Viscosity ◽  
Turbulent Diffusion Coefficient ◽  
Number Range ◽  
Particle Reynolds Number ◽  
Photochromic Dye

The mixing of liquid mass caused by a spherical solid particle falling in a still liquid in a pipe was investigated by visualization and noninvasive concentration measurement using a photochromic dye. A spherical particle with diameter of 4.76 mm was dropped in a kerosene-paraffin mixture liquid with a photochromic dye. The photochromic dye was activated by an ultraviolet light and was subjected to the mixing by the particle wake. The falling velocity of particle was changed by using 8 different densities of particle. The effect of the particle Reynolds number on the mixing was investigated for the Reynolds number range from 10 to 2490. The effect of liquid viscosity on the mixing time was also investigated using two liquids having different viscosity. The visualized dye patterns indicated the mixing process depended strongly on the particle Reynolds number. For the Reynolds numbers higher than 300, the particle shed the vortices behind the particle and the dye was mixed isotropically by large-scale vortices. For the Reynolds numbers lower than 300, the dye was drawn straightly by a laminar wake of the particle. The concentration of the mixed dye was measured using the photochromic concentration measuring (PCM) technique to discuss the mass mixing quantitatively. The turbulent diffusion coefficient (TDC) was evaluated for the cases the dye was mixed by the vortices. It was found that the evaluated TDCs showed strong time-dependency, which was attributed to the change in scale and whirling velocity of wake vortices. The maximum TDC depended on the falling velocity regardless of the fluid viscosity. The mixing time depended strongly on the liquid viscosity. The mixing time of the TDC was suggested to be governed by the viscous decay time and expanding time of vortices in the pipe. The amount of dye drift was evaluated for the cases the particle wake was laminar. It was found that the dye drift increased sharply just after the particle passing and then saturated. The final dye drift increased gradually with increasing Reynolds number.

Inertial migration of a small sphere in linear shear flows

1991 ◽  
Vol 224 ◽  
pp. 261-274 ◽  
Author(s):  
John B. McLaughlin
Keyword(s):  
Reynolds Number ◽  
Shear Rate ◽  
Slip Velocity ◽  
Reynolds Numbers ◽  
Rigid Sphere ◽  
Square Root ◽  
Small Sphere ◽  
Inertial Migration ◽  
Particle Reynolds Number ◽  
Linear Shear

The motion of a small, rigid sphere in a linear shear flow is considered. Saffman's analysis is extended to other asymptotic cases in which the particle Reynolds number based on its slip velocity is comparable with or larger than the square root of the particle Reynolds number based on the velocity gradient. In all cases, both particle Reynolds numbers are assumed to be small compared to unity. It is shown that, as the Reynolds number based on particle slip velocity becomes larger than the square root of the Reynolds number based on particle shear rate, the magnitude of the inertial migration velocity rapidly decreases to very small values. The latter behaviour suggests that contributions that are higher order in the particle radius may become important in some situations of interest.

Numerical Simulation of Cell Motility at Low Reynolds Number

2012 ◽  
Author(s):  
Thomas F. Scherr ◽  
Chunliang Wu ◽  
W. Todd Monroe ◽  
Krishnaswamy Nandakumar
Keyword(s):  
Numerical Simulation ◽  
Reynolds Number ◽  
Cell Motility ◽  
Reynolds Numbers ◽  
Fluid Viscosity ◽  
Forward Movement ◽  
Fluid System ◽  
Length Scales ◽  
Velocity Fluctuations ◽  
Fluid Movement

As length scales decrease to microns, the mechanism for swimming becomes unfortunately counter-intuitive. In the macro-world, where human intuition has developed, we swim by accelerating the liquid around us. For microorganisms, which swim at Reynolds numbers much less than unity, Stokes law does not permit accelerations. As such, the fluid movement is governed entirely by the local boundaries of the microorganism and the fluid viscosity dampens velocity fluctuations rapidly as distance away from the swimmer increases. A well known byproduct of this, Purcell’s “Scallop Theorem”, forbids reciprocal motions to generate net forward movement [1]. To overcome this, flagella propagate waves down their length and cilia have asymmetric beats. This type of motility has been described as zero-thrust swimming since the net force on the organism-fluid system must be zero [2].

Measurements of Velocity and Turbulence in Vertical Axisymmetric Isothermal and Buoyant Jets

1992 ◽  
Vol 114 (1) ◽  
pp. 135-142 ◽  
Author(s):  
J. Peterson ◽  
Y. Bayazitoglu
Keyword(s):  
Reynolds Number ◽  
Flow Field ◽  
Transition Region ◽  
Nozzle Exit ◽  
Low Reynolds Number ◽  
Reynolds Numbers ◽  
Buoyant Jets ◽  
Velocity Fluctuations ◽  
Curve Fit ◽  
Low Reynolds

The current study examines the transition region of axisymmetric isothermal and buoyant jets of low Reynolds number, directed vertically upward into a stagnant, unstratified ambient. The region in which measurements were obtained allows examination of two types of transition occurring in the jet: from nozzle exit dominated to fully developed, and from momentum to buoyancy-dominated flow. Isothermal velocity data were acquired using a two-channel laser-Doppler anemometer for Reynolds numbers ranging from 850 to 7405. The buoyant cases studied had Froude numbers ranging from 12 to 6425 and Reynolds numbers from 525 to 6500. In each case data were taken from 5 to 44 nozzle diameters downstream. Curve fit approximations of the data were developed by assuming polynomial similarity profiles for the measured quantities. Each profile was individually curve fit because in the transition region under consideration the flow field is not necessarily similar. Profile constants were then curve fit to determine profile variation as a function of nozzle exit parameters and downstream location. These allow prediction of the downstream velocity flow field and turbulent flow field as a function of the Reynolds number, Froude number, and density ratio at the nozzle exit. Profile width and entrainment increased at low Reynolds number. Axial and radial velocity fluctuations were found to increase at low Reynolds number. The buoyant cases studied were found to have lower velocity fluctuations and significantly lower Reynolds stresses than isothermal cases of similar Reynolds number.

scholarly journals The discrete Green's function paradigm for two-way coupled Euler–Lagrange simulation

2021 ◽  
Vol 931 ◽  
Author(s):  
J.A.K. Horwitz ◽  
G. Iaccarino ◽  
J.K. Eaton ◽  
A. Mani
Keyword(s):  
Reynolds Number ◽  
Green’S Function ◽  
Green's Function ◽  
Stokes Equations ◽  
Fluid Velocity ◽  
Reynolds Numbers ◽  
Function Approach ◽  
Particle Reynolds Number ◽  
Discrete Green’S Function ◽  
Particle Laden Flows

We outline a methodology for the simulation of two-way coupled particle-laden flows. The drag force that couples fluid and particle momentum depends on the undisturbed fluid velocity at the particle location, and this latter quantity requires modelling. We demonstrate that the undisturbed fluid velocity, in the low particle Reynolds number limit, can be related exactly to the discrete Green's function of the discrete Stokes equations. In addition to hydrodynamics, the method can be extended to other physics present in particle-laden flows such as heat transfer and electromagnetism. The discrete Green's functions for the Navier–Stokes equations are obtained at low particle Reynolds number in a two-plane channel geometry. We perform verification at different Reynolds numbers for a particle settling under gravity parallel to a plane wall, for different wall-normal separations. Compared with other point-particle schemes, the Stokesian discrete Green's function approach is the most robust at low particle Reynolds number, accurate at all wall-normal separations. To account for degradation in accuracy away from the wall at finite Reynolds number, we extend the present methodology to an Oseen-like discrete Green's function. The extended discrete Green's function method is found to be accurate within $6\,\%$ at all wall-normal separations for particle Reynolds numbers up to 24. The discrete Green's function approach is well suited to dilute systems with significant mass loading and this is highlighted by comparison against other Euler–Lagrange as well as particle-resolved simulations of gas–solid turbulent channel flow. Strong particle–turbulence coupling is observed in the form of turbulence modification and turbophoresis suppression, and these observations are placed in context of the different methods.

Low Reynolds number flow around and heat transfer from a heated circular cylinder

2010 ◽  
Vol 1 (1-2) ◽  
pp. 15-20 ◽  
Author(s):  
B. Bolló
Keyword(s):  
Reynolds Number ◽  
Circular Cylinder ◽  
Lift Coefficient ◽  
Reynolds Numbers ◽  
Low Reynolds Numbers ◽  
Reynolds Number Flow ◽  
Two Dimensional Flow ◽  
Number Flow ◽  
Low Reynolds ◽  
Increasing Temperature

Abstract The two-dimensional flow around a stationary heated circular cylinder at low Reynolds numbers of 50 < Re < 210 is investigated numerically using the FLUENT commercial software package. The dimensionless vortex shedding frequency (St) reduces with increasing temperature at a given Reynolds number. The effective temperature concept was used and St-Re data were successfully transformed to the St-Reeff curve. Comparisons include root-mean-square values of the lift coefficient and Nusselt number. The results agree well with available data in the literature.

scholarly journals Turbulence model performance for ventilation components pressure losses

2021 ◽  
Author(s):  
Karsten Tawackolian ◽  
Martin Kriegel
Keyword(s):  
Reynolds Number ◽  
Turbulence Model ◽  
Pressure Loss ◽  
Low Reynolds Number ◽  
Turbulence Models ◽  
Reynolds Numbers ◽  
Test Case ◽  
Pressure Losses ◽  
Loss Coefficients ◽  
Near Wall

AbstractThis study looks to find a suitable turbulence model for calculating pressure losses of ventilation components. In building ventilation, the most relevant Reynolds number range is between 3×104 and 6×105, depending on the duct dimensions and airflow rates. Pressure loss coefficients can increase considerably for some components at Reynolds numbers below 2×105. An initial survey of popular turbulence models was conducted for a selected test case of a bend with such a strong Reynolds number dependence. Most of the turbulence models failed in reproducing this dependence and predicted curve progressions that were too flat and only applicable for higher Reynolds numbers. Viscous effects near walls played an important role in the present simulations. In turbulence modelling, near-wall damping functions are used to account for this influence. A model that implements near-wall modelling is the lag elliptic blending k-ε model. This model gave reasonable predictions for pressure loss coefficients at lower Reynolds numbers. Another example is the low Reynolds number k-ε turbulence model of Wilcox (LRN). The modification uses damping functions and was initially developed for simulating profiles such as aircraft wings. It has not been widely used for internal flows such as air duct flows. Based on selected reference cases, the three closure coefficients of the LRN model were adapted in this work to simulate ventilation components. Improved predictions were obtained with new coefficients (LRNM model). This underlined that low Reynolds number effects are relevant in ventilation ductworks and give first insights for suitable turbulence models for this application. Both the lag elliptic blending model and the modified LRNM model predicted the pressure losses relatively well for the test case where the other tested models failed.

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