Flow regimes probed at the pore scale in porous materials using micro-particle image velocimetry


The fluid flow through natural and artificial porous materials is a popular research topic in industry and science owing to its numerous applications. Porous media typically exhibit unique structural characteristics attributed to the tortuous channels and high surface area to volume ratio. These characteristics, combined with the obstruction of the flow paths, make fluid flow through porous media a complex phenomenon. Nevertheless, understanding the fluid flow behaviors through these materials is of great significance for heat transfer, catalysis, preparation of composites, oil and gas extraction, and must not be overlooked. Effective fluid flow characterization requires the knowledge of the different flow regimes and their relationship with other critical aspects of fluid dynamics such as flow rates, and pressure gradient.

To date, various flow regimes in porous media have been extensively studied using various techniques. However, these methods were largely based on either traditional flow visualization or pressure gradient measurements and provided inadequate data to elucidate fluid flow characteristics. For instance, they cannot accurately determine the flow regime boundaries, the stress and velocity distributions that are of significant interest in studying flow dynamics in porous materials. Micro-particle image velocimetry (µ-PIV) has emerged as a promising technique for studying flow behaviors at micro-scale levels.

Despite the good progress, obtaining high-quality experimental data remains a great challenge due to several drawbacks. Moreover, there are no studies in which the flow velocity measurements in porous materials cover all the known flow regimes. To address these challenges, Dr Xianke Lu, Professor Yuyuan Zhao, and Dr David Dennis from the University of Liverpool investigated the velocity distributions and flow hydrodynamics in a randomly packed micro-porous media made of different sphere sizes, using a combination of pressure-drop and µ-PIV measurements. The aim was to provide a better understanding of flow characteristics at different flow regimes. Their study is subsequently published in the journal, Experimental Thermal and Fluid Science.

In their approach, the porous media comprised of slightly sintered structures made up of three glass samples with mean diameters of 170, 430 and 710 µm. The velocity distributions and fluctuations were measured by µ-PIV while the flow regimes were identified through pressure-drop measurements. The relationship between the flow regimes, permeability, glass sphere sizes, pore geometries and Reynolds number were also discussed. Finally, the obtained results were compared with the existing experimental data.

For all the sintered samples, the authors identified four different flow regimes associated with porous media: pre-Darcy, Darcy, turbulent and Forchheimer. Both the Reynolds number of the corresponding regime and permeability increased with an increase in the sizes of the glass spheres attributed to lower surface area and less tortuous flow path. The pressure drop was strongly influenced by the particle sizes. The pressure drop increased with an increase in the Reynolds number in the Darcy flow regime. The relationship was, however, non-linear in the other three regimes. On the other hand, the velocity profiles in the Darcy and Forchheimer regimes were found to be near-parabolic, whereas the inertial effects were more pronounced in the turbulent regime. Even though the flow distributions remain similar in geometries with 170 μm and 430 μm diameter samples, they were significantly different in the sample with a diameter of 710 μm.

In summary, the study provided a detailed fluid flow characterization in a microscale porous media in all the flow regimes. The statistical analysis highlighted a strong dependency of the pressure drops of the particle size and velocity distribution on the local geometry in the different flow regimes. Results showed a good agreement between the average velocity fluctuations and pressure drop measurements throughout the regimes. In a statement to Advances in Engineering, the authors explained their micro-PIV measurements show that the velocity distribution within a porous material is highly dependent on the local geometric features, with localised regions of flow apparently in a different flow regime to that of the bulk flow. However, the total magnitude of the fluctuations throughout the whole geometry is shown to be a good indicator of the flow regime and is commensurate with the pressure drop measurements..

About the author

Xianke Lu is currently a lecturer at the School of Materials Science and Engineering at Anhui Polytechnic University. He received his BS degree from Nanjing University of Science and Technology in 2013. After that, he continued his study in materials science and engineering and received a MS degree from Nanjing University of Science and Technology in 2016. Then, he joined the porous material and fluid group in the School of Engineering at the University of Liverpool, where he was awarded a Ph.D degree in 2020. His research interests include heat transfer and fluid flow behavior in porous media, fabrication and characterization of advanced porous metal.

About the author

David JC Dennis is a lecturer in the School of Engineering at the University of Liverpool. He obtained his PhD in wall-bounded turbulence from the University of Cambridge in 2009. The focus of his research is using experimental techniques to investigate different types of Newtonian and non-Newtonian fluid flows, particularly those involving instabilities, transition or turbulence. In addition to his work on porous materials and large-scale turbulent flows, he has also published on slurry flows, instabilities in microfluidic devices, vortex breakdown and magmatic flows.


Lu, X., Zhao, Y., & Dennis, D.J.C. (2020). Fluid flow characterisation in randomly packed microscale porous beds with different sphere sizes using micro-particle image velocimetryExperimental Thermal and Fluid Science, 118, 110136.

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