General computational methodology for modeling electrohydrodynamic flows: prediction and optimization capability for the generation of bubbles and fibers

Babatunde Aramide, Anjana Kothandaraman, Mohan Edirisinghe, Suwan N. Jayasinghe, Yiannis Ventikos

Research output: Contribution to journalArticleResearchpeer-review

18 Citations (Scopus)

Abstract

The application of an electric field on a fluid in motion gives rise to unique features and flow manipulation capabilities. Technologies ranging from bubble formation, droplet generation, fiber spinning, and many others are predicated on this type of flows, often referred to as Electrohydrodynamics (EHD). In this paper, we present a numerical methodology that allows for the modeling of such processes in a generalized way. The method can account for the premixing of various liquid species, the injection of gases in the mixture and the interaction of such complex multiphase flow with an electric field, static or AC. The domain in which these processes take place can be of arbitrary geometric complexity, allowing for design and optimization of complex EHD devices. Our study looks at the critical phases of some of these processes and emphasizes the strong coupling of fluid mechanics and electric fields and the influence of the electric field on fluid flow and vice versa. The conservation of mass and momentum, with appropriate additional force terms coming from the presence of the electric field, and the electrostatic equations are coupled together and solved using the Finite Volume method. The Volume of Fluid (VoF) technique is used to track free surfaces dynamically. The solution procedure iteratively computes electric body and surface forces and then includes those into the Navier-Stokes equation to predict the velocity field and other fluid parameters. No initial shape is assumed for the fluid(s) and charge distributions. The methodology presented handles two-dimensional, axisymmetric. and full three-dimensional cases of arbitrary geometric complexity, allowing for mixing and microfluidic configurations of high levels of realism. We highlight the capability of the method by demonstrating cases like the formation of a Taylor cone, microfluidic bubble generation, jet evolution, and droplet breakup. Results agree well with both existing experimental and computational reports.

Original languageEnglish
Pages (from-to)10203-10212
Number of pages10
JournalLangmuir
Volume35
Issue number31
DOIs
Publication statusPublished - 6 Aug 2019
Externally publishedYes

Cite this