A Quantitative Comparison of Physical Accuracy and Numerical Stability of Lattice Boltzmann Color Gradient and Pseudopotential Multicomponent Models for Microfluidic Applications (Communications in Computational Physics, 2022)
The performances of the Color-Gradient (CG) and the Shan-Chen (SC) multicomponent Lattice Boltzmann models are quantitatively compared side-by-side onmultiple physical flow problems where breakup, coalescence and contraction of fluidligaments are important. The flow problems are relevant to microfluidic applications,jetting of microdroplets as seen in inkjet printing, as well as emulsion dynamics. Asignificantly wider range of parameters is shown to be accessible for CG in terms ofdensity-ratio, viscosity-ratio and surface tension values. Numerical stability for a highdensity ratio $\mathcal{O}(1000)$ is required for simulating the drop formation process duringinkjet printing which we show here to be achievable using the CG model but not usingthe SC model. Our results show that the CG model is a suitable choice for challengingsimulations of droplet formation, due to a combination of both numerical stability andphysical accuracy. We also present a novel approach to incorporate repulsion forcesbetween interfaces for CG, with possible applications to the study of stabilized emulsions. Specifically, we show that the CG model can produce similar results to a knownmultirange potentials extension of the SC model for modelling a disjoining pressure,opening up its use for the study of dense stabilized emulsions.
Keywords: Lattice Boltzmann method; multiphase flow; multicomponent flow; inkjet printing; turbulent emulsion.