This paper investigates the path selection of bubbles suspended in different power-law carrier liquids in microfluidic channel networks. A finite volume-based numerical method is used to analyze the two-dimensional incompressible fluid flow in microchannels, while the volume of fluid method is used to capture the gas–liquid interface. To instill the influences of shear thinning, Newtonian, and shear-thickening fluids, the range of power-law indices (n) is varied from 0.3 to 1.5. We have validated our numerical model with the available literature data in good agreement. We have investigated the nonlinearity in the hydrodynamic resistance which arises due to single-phase non-Newtonian fluid flow. The path selection of a bubble in power-law fluids is examined from the perspective of velocity distribution and bubble deformation. We have found that the bubble indeed goes to the channel with a higher flow rate for all power-law fluids, but interestingly it did not always take the shorter route channel at a junction for n = 0.3. Our results suggest that long channels need not be more resistant for every fluid and that the longest arm becomes the least resistant resulting in the bubble leading into the long arm at a junction for shear-thinning fluid. We have proposed a deterministic model that enables predicting the second bubble path in a single bubble system for any location of the first bubble. We believe that the present study results will help design future generation microfluidic systems for efficient drug delivery and biomedical and biochemical applications.
We numerically investigate the effect of electrohydrodynamics on a non-Newtonian droplet pair suspended in a Newtonian medium. The leaky dielectric model is implemented to study the response of emulsion drops in an externally applied electric field. Subsequently, the non-Newtonian drop behavior is incorporated using the power law model, whereby three different fluid behaviors are considered for the drops: Newtonian, Shear thinning, and Shear thickening. We validated our numerical model with the available literature data, and the results are in good agreement. The droplets' deformation and net motion are investigated for a range of electrical permittivity ratios of the droplet medium with respect to the surrounding fluid. In this study, four distinct regimes are identified based on the net drop pair motion and the circulation pattern that develops due to the electric stresses inside and around the drops. Furthermore, it is observed that the droplet deformation and their net motion are fastest for the pseudo-plastic drops and slowest for dilatant drops. We devised a simple ratio-based model to understand this behavior. The inferences drawn from this study will help contribute to a better understanding of the behavior of nonlinear fluids under an electric field.
The overall purpose of this study is to critically analyze one of the important areas of Computational Fluid Dynamics i.e. the Linear Convection Problem. There had been, quite a significant research in this field. The main issue that is faced while numerically solving this problem whether in 1D,2D or 3D is the oscillation or diffusion which eventually makes the solution unstable. Hence, my study will deal with this in details and I had also incorporated the effect of mesh size and time step size on the solution and how they affect the stability individually. I had opted for Upwind Scheme to numerically solve this problem and to comment on the factor (CFL No.) which affects the stability. I had also derived the optimum condition for the CFL No., and the simulation results of the proposed scheme are also shown in this paper.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.