Pore-scale numerical study of intrinsic permeability for fluid flow through asymmetric ceramic microfiltration membranes

2022 ◽  
Vol 642 ◽  
pp. 119920
Author(s):  
Shuang Song ◽  
Liangwan Rong ◽  
Kejun Dong ◽  
Xuefei Liu ◽  
Pierre Le-Clech ◽  
...  
Keyword(s):  
Fluid Flow ◽  
Numerical Study ◽  
Pore Scale ◽  
Intrinsic Permeability ◽  
Microfiltration Membranes ◽  
Flow Through

Numerical study of the hydraulic tortuosity for fluid flow through elliptical particle packings

2021 ◽  
pp. 117047
Author(s):  
Shuang Song ◽  
Liangwan Rong ◽  
Kejun Dong ◽  
Yansong Shen
Keyword(s):  
Fluid Flow ◽  
Numerical Study ◽  
Flow Through ◽  
Particle Packings

Pore-Scale Modeling of Non-Newtonian Fluid Flow Through Micro-CT Images of Rocks

2018 ◽  
pp. 363-375
Author(s):  
Moussa Tembely ◽  
Ali M. AlSumaiti ◽  
Khurshed Rahimov ◽  
Mohamed S. Jouini
Keyword(s):  
Fluid Flow ◽  
Newtonian Fluid ◽  
Ct Images ◽  
Micro Ct ◽  
Pore Scale ◽  
Scale Modeling ◽  
Pore Scale Modeling ◽  
Flow Through

scholarly journals Numerical Analysis of Fluid Flow on Wall Cylinder Circular with K-ε Modeling for a High Reynolds Rate

2019 ◽  
Vol 1 (3) ◽  
pp. 43-50
Author(s):  
M. Yasep Setiawan ◽  
Wawan Purwanto ◽  
Wanda Afnison ◽  
Nuzul Hidayat
Keyword(s):  
Fluid Flow ◽  
Numerical Study ◽  
General Procedure ◽  
Circular Cylinders ◽  
Cylinder Wall ◽  
Two Dimensional ◽  
Third Order ◽  
Physical Information ◽  
Flow Through ◽  
High Reynolds

This study discusses the numerical study of two-dimensional analysis of flow through circular cylinders. The original physical information entered in the equation governing most of the modeling is transferred into a numerical solution. Fluid flow on two-dimensional circular cylinder wall using high Reynolds k-ε modeling (Re = 106), Here we will do 3 modeling first oder upwind, second order upwind and third order MUSCL by using k-ε standard.  The general procedure for this research is formulated in detail for allocations in the dynamic analysis of fluid computing. The results of this study suggest that MUSCL's third order modeling gives more accurate results better than other models.

Control of Dielectric Fluid Flow Distribution in Micro-Tubes With EHD Conduction Pumping: Numerical Study

2011 ◽  
Author(s):  
Miad Yazdani ◽  
Jamal Seyed-Yagoobi
Keyword(s):  
Fluid Flow ◽  
Electric Field ◽  
Conduction Mechanism ◽  
Numerical Study ◽  
Fluid Motion ◽  
Flow Distribution ◽  
Operating Conditions ◽  
Dielectric Fluid ◽  
Total Flow ◽  
Flow Through

The control of fluid flow distribution in micro-scale tubes is numerically investigated. The flow distribution control is achieved via electric conduction mechanism. In electrohydrodynamic (EHD) conduction pumping, when an electric field is applied to a fluid, dissociation and recombination of electrolytic species produces heterocharge layers in the vicinity of electrodes. Attraction between electrodes and heterocharge layers induces a fluid motion and a net flow is generated if the electrodes are asymmetric. The numerical domain comprises a 2-D manifold attached to two bifurcated tubes with one of the tubes equipped with a bank of uniquely designed EHD-conduction electrodes. In the absence of electric field, the total flow supplied at the manifold’s inlet is equally distributed among the tubes. The EHD-conduction, however, operates as a mechanism to manipulate the flow distribution to allow the flow through one branch surpasses the counterpart of the other branch. Its performance is evaluated under various operating conditions.

scholarly journals Network architecture strongly influences the fluid flow pattern through the lacunocanalicular network in human osteons

2019 ◽  
Vol 19 (3) ◽  
pp. 823-840 ◽  
Author(s):  
Alexander F. van Tol ◽  
A. Roschger ◽  
F. Repp ◽  
J. Chen ◽  
P. Roschger ◽  
...  
Keyword(s):  
Fluid Flow ◽  
Network Architecture ◽  
Path Length ◽  
Fluid Velocity ◽  
Network Connectivity ◽  
Computational Techniques ◽  
Structural Parameter ◽  
Haversian Canal ◽  
Intrinsic Permeability ◽  
Flow Through

AbstractA popular hypothesis explains the mechanosensitivity of bone due to osteocytes sensing the load-induced flow of interstitial fluid squeezed through the lacunocanalicular network (LCN). However, the way in which the intricate structure of the LCN influences fluid flow through the network is largely unexplored. We therefore aimed to quantify fluid flow through real LCNs from human osteons using a combination of experimental and computational techniques. Bone samples were stained with rhodamine to image the LCN with 3D confocal microscopy. Image analysis was then performed to convert image stacks into mathematical network structures, in order to estimate the intrinsic permeability of the osteons as well as the load-induced fluid flow using hydraulic circuit theory. Fluid flow was studied in both ordinary osteons with a rather homogeneous LCN as well as a frequent subtype of osteons—so-called osteon-in-osteons—which are characterized by a ring-like zone of low network connectivity between the inner and the outer parts of these osteons. We analyzed 8 ordinary osteons and 9 osteon-in-osteons from the femur midshaft of a 57-year-old woman without any known disease. While the intrinsic permeability was 2.7 times smaller in osteon-in-osteons compared to ordinary osteons, the load-induced fluid velocity was 2.3 times higher. This increased fluid velocity in osteon-in-osteons can be explained by the longer path length, needed to cross the osteon from the cement line to the Haversian canal, including more fluid-filled lacunae and canaliculi. This explanation was corroborated by the observation that a purely structural parameter—the mean path length to the Haversian canal—is an excellent predictor for the average fluid flow velocity. We conclude that osteon-in-osteons may be particularly significant contributors to the mechanosensitivity of cortical bone, due to the higher fluid flow in this type of osteons.

A NUMERICAL STUDY OF THE HEAT TRANSFER TO FLUID FLOW THROUGH CIRCULAR POROUS PASSAGES

2004 ◽  
Vol 46 (10) ◽  
pp. 929-955 ◽  
Author(s):  
A. Haji-Sheikh ◽  
W. J. Minkowycz ◽  
E. M. Sparrow
Keyword(s):  
Heat Transfer ◽  
Fluid Flow ◽  
Numerical Study ◽  
Flow Through

scholarly journals Numerical study of fluid flow at pore scale in packed bed of spheres and grains to obtain the REV

2020 ◽  
Vol 348 (8-9) ◽  
pp. 769-779
Author(s):  
Luis Carlos Martínez-Mendoza ◽  
Florencio Sánchez-Silva ◽  
Erik Fernando Martínez-Mendoza ◽  
Juan Antonio Cruz-Maya
Keyword(s):  
Fluid Flow ◽  
Numerical Study ◽  
Packed Bed ◽  
Pore Scale

scholarly journals The Complexity of Porous Media Flow Characterized in a Microfluidic Model Based on Confocal Laser Scanning Microscopy and Micro-PIV

2020 ◽  
Author(s):  
D. A. M. de Winter ◽  
K. Weishaupt ◽  
S. Scheller ◽  
S. Frey ◽  
A. Raoof ◽  
...  
Keyword(s):  
Porous Media ◽  
Fluid Flow ◽  
Confocal Laser Scanning Microscopy ◽  
Laser Scanning ◽  
Laser Scanning Microscopy ◽  
Confocal Laser Scanning ◽  
Confocal Laser ◽  
Pore Scale ◽  
Micro Piv ◽  
Flow Through

Abstract In this study, the complexity of a steady-state flow through porous media is revealed using confocal laser scanning microscopy (CLSM). Micro-particle image velocimetry (micro-PIV) is applied to construct movies of colloidal particles. The calculated velocity vector fields from images are further utilized to obtain laminar flow streamlines. Fluid flow through a single straight channel is used to confirm that quantitative CLSM measurements can be conducted. Next, the coupling between the flow in a channel and the movement within an intersecting dead-end region is studied. Quantitative CLSM measurements confirm the numerically determined coupling parameter from earlier work of the authors. The fluid flow complexity is demonstrated using a porous medium consisting of a regular grid of pores in contact with a flowing fluid channel. The porous media structure was further used as the simulation domain for numerical modeling. Both the simulation, based on solving Stokes equations, and the experimental data show presence of non-trivial streamline trajectories across the pore structures. In view of the results, we argue that the hydrodynamic mixing is a combination of non-trivial streamline routing and Brownian motion by pore-scale diffusion. The results provide insight into challenges in upscaling hydrodynamic dispersion from pore scale to representative elementary volume (REV) scale. Furthermore, the successful quantitative validation of CLSM-based data from a microfluidic model fed by an electrical syringe pump provided a valuable benchmark for qualitative validation of computer simulation results. Graphic Abstract

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