Inline static mixers are widely used in process operations that involve mixing of viscous fluids under laminar flow regime. Their low operating cost, small reactor volumes, and enhanced safety add to their superiority over conventional mixers. In addition, their simple geometry and recent advances in CFD facilitate the proper characterization of their mixing performance.

Recently, a novel mixer made of plain square woven meshes/screens was used to process flow under turbulent regime resulting in near plug flow conditions. It proved very efficient at promoting multiphase dispersions and mass transfer operations at low energy consumption rates \[1-2\]. Its superior performance under turbulent regime served as a stimulus to investigate its mixing performance under laminar flow regime. In this quest, the mixing performance of screen type static mixers (STSM) was numerically investigated using the Lagrangian particle method and the commercial CFD solver ANSYS Fluent^®^.

Mixing within static mixers is typically divided into distributive and dispersive mixing. The former illustrates the spatial distribution of fluid elements within a cross-section, while the latter reveals the breakup of fluid elements flowing through the mixer. In the current work, these two modes of mixing were characterized both qualitatively and quantitatively using two techniques, namely, the point-to-nearest-neighbor (PNN) \[3\] and extensional efficiency \[4\]. The distributive mixing was investigated using the former technique which reports the position of particles at various locations after injecting them from a small area at the inlet. Using the filtered variance of the PNN distribution, the distributive mixing was quantified. Furthermore, the extensional efficiency was used to study the dispersive mixing both qualitatively, using contour plots at different locations to show whether the flow is rotational, elongational, or pure shear; and quantitatively, by calculating the area-average values of the extensional efficiency at these locations. A visual method that consists of mixing the same fluid using two different colors was also used as a qualitative mean to characterize mixing.

In this study, the effect of changing the mixer geometry was investigated. In addition, the effect of changing the number of screens, inter-screen spacing, and operating conditions on the mixing performance was also considered.

The results indicate that a central injection scheme should be coupled with a short inter-screen spacing to better spread the particles and enhance mixing when compared to a larger inter-screen spacing. While an off-centered injection (near the wall) would benefit from a larger inter-screen spacing to achieve good mixing. These results were predicted qualitatively using the PNN method by comparing the distribution of particles with a random Poisson distribution, and quantitatively by calculating low filtration values. From a dispersive mixing perspective, the extensional efficiency contours revealed the presence of all three modes of flow behavior depending on the location with respect to the screen. In addition, extensional efficiency values of *β* ≈ 0.61 were attainable which is another indicator of good dispersive mixing. Finally, it was also interesting to find that a coarser screen geometry consistently outperformed finer screens in spreading and mixing the particles.

Keywords: Laminar regime, screens, woven mesh, static mixer, mixing, PNN method, extensional efficiency.

References:

\[1\] Al Taweel et al., Chem. Eng. Process. 72 (2013) 51–62.

\[2\] Azizi et al. Ind. Eng. Chem. Res. 54 (2015) 11635–11652

\[3\] Kukukova et al., Can. J. Chem. Eng. 89 (2011) 1122–1138

\[4\] Meng et al. Ind. Eng. Chem. Res. 53 (2014) 4084–4095.


Cfd Simulation of Wall-Bounded Laminar Flow Through Screens. Part Ii: Mixing Characterization

Division / Sponsors: 
Heat Transfer Division (HTD), Fluids Engineering Division (FED)

Heat Transfer Summer Conference
Paper Proceedings: https://asmedigitalcollection.asme.org/HT/HT2020/volume/83709

18th International Conference on Nanochannels, Microchannels, and Minichannels
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