NMR imaging of velocity profiles and velocity distributions in bead packs

Kutsovsky, Y. E.; Scriven, L. E.; Davis, H. T.; Hammer, Bruce E.

doi:10.1063/1.868867

Cited by 147 publications

(105 citation statements)

References 18 publications

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“…The local counter diffusive flux, as well as the Darcy counter flow (Kutsovsky et al 1996;Maier et al 1998;Ogawa et al 2001;Li et al 2010), was observed in the present study (Figs. 9c, 11c).…”

Section: Negative Tail and Long Positive Tailsupporting

confidence: 54%

“…(i) The local counter flow was already found for the Darcy flow (not diffusion) in porous media (Kutsovsky et al 1996;Maier et al 1998;Ogawa et al 2001;Li et al 2010). The local flux obeys the log-normal distribution for the random resistor network (de Arcangelis et al 1985) and for the Darcy flow (Cenedese and Viotti 1996;Lebon et al 1996).…”

Section: Introductionmentioning

confidence: 99%

“…For a system with a sufficiently large Péclet number, the local tracer flux vector mostly agrees with the local Darcy flux vector. Then the histogram of the local tracer flux depends on the Reynolds number (Maier et al 1998), the negligible local counter flux occurs (Kutsovsky et al 1996;Ogawa et al 2001;Li et al 2010), and the Jz component obeys the log-normal distribution (Cenedese and Viotti 1996;Lebon et al 1996). It should be also noted that the 3D migration trajectory of tracers dissolved in the flowing fluid would switch from the less tortuous path to more tortuous one having larger local pore diameters (Zhang and Knackstedt 1995).…”

Section: Concept Ofmentioning

confidence: 99%

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Steady-State Local Diffusive Fluxes in Porous Geo-Materials Obtained by Pore-Scale Simulations

Nakashima

Nakano

2012

Transp Porous Med

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Computer simulations of non-sorbing tracers diffusing in fluid-saturated porous sediment/rock were performed using pore-scale X-ray microtomographic images to reveal the following. (i) The histogram of the magnitude of the local diffusive flux vector obeys a unimodal log-normal distribution having a long positive tail. Simulations using model images were also performed to show that the flux broadening in large pores and the flux mixing at the pore network junctions are responsible for the log-normal shape. (ii) The simulation enabled us to directly visualize pore voxels with large and small fluxes, confirming the existence of transport pores and stagnant pores. Because of the unimodal nature, however, it was difficult to distinguish transport pores from stagnant pores using an objective threshold in the histogram. (iii) Another histogram of the flux vector component along the direction of the macroscopic concentration gradient was analyzed. A negative tail was found in the histogram, indicating that local counter diffusion exists in the porous geo-materials. However, the population and intensity of the counter diffusion fluxes are too small and weak to contribute to the overall diffusive transport across the porous media system. A long positive tail representing a large-flux diffusive pathway was also observed in the histogram. However, again, the population of the large-flux transport pores is small. As a result, the main conveyer of the tracer is the stagnant pores (not the transport pores), which have small positive flux values but a large population.

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Section: Negative Tail and Long Positive Tailsupporting

confidence: 54%

Section: Introductionmentioning

confidence: 99%

Section: Concept Ofmentioning

confidence: 99%

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Steady-State Local Diffusive Fluxes in Porous Geo-Materials Obtained by Pore-Scale Simulations

Nakashima

Nakano

2012

Transp Porous Med

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“…However for higher Re, e.g., Re = 4, their plots show a small plateau. This is also the case for results in Kutsovsky et al (1996) obtained with NMR. Here Re up to about 50 is studied and it is clear that the distribution profiles of u x (v z in their paper) attain a more plateau like shape as Re increases in accordance with our results.…”

Section: Detailed Studies Of the Flowmentioning

confidence: 74%

Measurements of Transitional and Turbulent Flow in a Randomly Packed Bed of Spheres with Particle Image Velocimetry

et al. 2016

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Particle image velocimetry (PIV) has been used to investigate transitional and turbulent flow in a randomly packed bed of mono-sized transparent spheres at particle Reynolds number, 20 < Re p < 3220. The refractive index of the liquid is matched with the spheres to provide optical access to the flow within the bed without distortions. Integrated pressure drop data yield that Darcy law is valid at Re p ≈ 80. The PIV measurements show that the velocity fluctuations increase and that the time-averaged velocity distribution start to change at lower Re p . The probability for relatively low and high velocities decreases with Re p and recirculation zones that appear in inertia dominated flows are suppressed by the turbulent flow at higher Re p . Hence there is a maximum of recirculation at about Re p ≈ 400. Finally, statistical analysis of the spatial distribution of time-averaged velocities shows that the velocity distribution is clearly and weakly self-similar with respect to Re p for turbulent and laminar flow, respectively.

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“…Both studies found an oscillatory radial velocity profi le. Kutsovsky et al 4 have been used a non-invasive Magnetic Resonance Imaging (MRI) experimental method to obtain local fl ow patterns in fi xed beds. The method has been restricted to low fl ow rates, Re < 100 and to fl uids which can produce a suitable signal for measurement.…”

Section: Introductionmentioning

confidence: 99%

Modelling of heat transfer in a packed bed column

Pianko‐Oprych

2011

Polish Journal of Chemical Technology

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The CFD modelling of heat transfer in the packed bed column in the laminar and turbulent fl ow regimes has been presented. Three numerical grids with different densities were generated for the packed bed column. The modelling was performed with the use of the Porous Media Model for treating the fl ow inside a porous structure. The standard k- model along with the logarithmic wall functions for the turbulent fl ow range was used. The infl uence of the mesh size on the accuracy of the fl uid fl ow was studied. Both radial and axial direction temperature distributions have been compared with the experimental data 1 and the values calculated from a 2DADPF model. A good agreement between the experimental and the predicted values of the pressure drop, temperature distributions and heat transfer coeffi cient was obtained.

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NMR imaging of velocity profiles and velocity distributions in bead packs

Cited by 147 publications

References 18 publications

Steady-State Local Diffusive Fluxes in Porous Geo-Materials Obtained by Pore-Scale Simulations

Steady-State Local Diffusive Fluxes in Porous Geo-Materials Obtained by Pore-Scale Simulations

Measurements of Transitional and Turbulent Flow in a Randomly Packed Bed of Spheres with Particle Image Velocimetry

Modelling of heat transfer in a packed bed column

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