TY - JOUR
T1 - Non-local model for surface tension in fluid-fluid simulations
AU - Howard, Amanda A.
AU - Tartakovsky, Alexandre M.
N1 - Funding Information:
This work was supported by The U.S. Department of Energy (DOE) Office of Science, Office of Advanced Scientific Computing Research as part of the New Dimension Reduction Methods and Scalable Algorithms for Nonlinear Phenomena project. Pacific Northwest National Laboratory is operated by Battelle for the DOE under Contract DE-AC05-76RL01830 .
Publisher Copyright:
© 2020
PY - 2020/11/15
Y1 - 2020/11/15
N2 - We propose a non-local model for surface tension obtained in the form of an integral of a molecular-force-like function with support 3.5ε added to the Navier-Stokes momentum conservation equation. We demonstrate analytically and numerically that with the non-local model interfaces with a radius of curvature larger than the support length behave macroscopically and microscopically, otherwise. For static droplets, the pressure difference Pε,in−Pε,out satisfies the Young-Laplace law for droplet radius greater than 3.5ε and otherwise deviates from the Young-Laplace law. The latter indicates that the surface tension in the proposed model decreases with decreasing radius of curvature, which agrees with molecular dynamics and experimental studies of nanodroplets. Using the non-local model we perform numerical simulations of droplets under dynamic conditions, including a rising droplet, a droplet in shear flow, and two colliding droplets in shear flow, and compare results with a standard Navier-Stokes model subject to the Young-Laplace boundary condition at the fluid-fluid interface implemented via the Conservative Level Set (CLS) method. We find good agreement with existing numerical methods and analytical results for a rising macroscopic droplet and a droplet in a shear flow. For colliding droplets in shear flow, the non-local model converges (with respect to the grid size) to the correct behavior, including sliding, coalescence, and merging and breaking of two droplets depending on the capillary number. In contrast, we find that the results of the CLS model are highly grid-size dependent.
AB - We propose a non-local model for surface tension obtained in the form of an integral of a molecular-force-like function with support 3.5ε added to the Navier-Stokes momentum conservation equation. We demonstrate analytically and numerically that with the non-local model interfaces with a radius of curvature larger than the support length behave macroscopically and microscopically, otherwise. For static droplets, the pressure difference Pε,in−Pε,out satisfies the Young-Laplace law for droplet radius greater than 3.5ε and otherwise deviates from the Young-Laplace law. The latter indicates that the surface tension in the proposed model decreases with decreasing radius of curvature, which agrees with molecular dynamics and experimental studies of nanodroplets. Using the non-local model we perform numerical simulations of droplets under dynamic conditions, including a rising droplet, a droplet in shear flow, and two colliding droplets in shear flow, and compare results with a standard Navier-Stokes model subject to the Young-Laplace boundary condition at the fluid-fluid interface implemented via the Conservative Level Set (CLS) method. We find good agreement with existing numerical methods and analytical results for a rising macroscopic droplet and a droplet in a shear flow. For colliding droplets in shear flow, the non-local model converges (with respect to the grid size) to the correct behavior, including sliding, coalescence, and merging and breaking of two droplets depending on the capillary number. In contrast, we find that the results of the CLS model are highly grid-size dependent.
KW - Finite volume
KW - Level set method
KW - Non-local method
KW - Spurious currents
KW - Surface tension
KW - Two-phase flows
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U2 - 10.1016/j.jcp.2020.109732
DO - 10.1016/j.jcp.2020.109732
M3 - Article
AN - SCOPUS:85089384749
SN - 0021-9991
VL - 421
JO - Journal of Computational Physics
JF - Journal of Computational Physics
M1 - 109732
ER -