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A fully coupled hybrid lattice Boltzmann and finite difference method-based study of transient electrokinetic flows
Author(s) -
Himadri Sekhar Basu,
Supreet Singh Bahga,
Sasidhar Kondaraju
Publication year - 2020
Publication title -
proceedings of the royal society a mathematical physical and engineering sciences
Language(s) - English
Resource type - Journals
eISSN - 1471-2946
pISSN - 1364-5021
DOI - 10.1098/rspa.2020.0423
Subject(s) - lattice boltzmann methods , electrokinetic phenomena , mechanics , finite difference , instability , finite difference method , boltzmann equation , statistical physics , transient (computer programming) , physics , electric field , materials science , thermodynamics , mathematical analysis , mathematics , computer science , quantum mechanics , nanotechnology , operating system
Transient electrokinetic (EK) flows involve the transport of conductivity gradients developed as a result of mixing of ionic species in the fluid, which in turn is affected by the electric field applied across the channel. The presence of three different coupled equations with corresponding different time scales makes it difficult to model the problem using the lattice Boltzmann method (LBM). The present work aims to develop a hybrid LBM and finite difference method (FDM)-based model which can be used to study the electro-osmotic flows (EOFs) and the onset of EK instabilities using an Ohmic model, where fluid and conductivity transport are solved using LBM and the electric field is solved using FDM. The model developed will be used to simulate three different problems: (i) EOF with varying zeta-potential on the wall, (ii) similitude in EOF, and (iii) EK instabilities due to the presence of conductivity gradients. Problems (i) and (ii) will be compared with the analytical results and problem (iii) will be compared with the simulations of a spectral method-based numerical model. The results obtained from the present simulations will show that the developed model is capable of studying transient EK flows and of predicting the onset of instability.

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