Many viscous liquids behave effectively as incompressible under high pressures but display a pronounced dependence of viscosity on pressure. The classical incompressible Navier-Stokes model cannot account for both features, and a simple pressure-dependent modification introduces questions about the well-posedness of the resulting equations. This paper presents the first study of a second-gradient extension of the incompressible Navier-Stokes model, recently introduced by the authors, which includes higher-order spatial derivatives, pressure-sensitive viscosities, and complementary boundary conditions. Focusing on steady flow down an inclined plane, we adopt Barus' exponential law and impose weak adherence at the lower boundary and a prescribed ambient pressure at the free surface. Through numerical simulations, we examine how the flow profile varies with the angle of inclination, ambient pressure, viscosity sensitivity to pressure, and internal length scale.
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Ionic current driven by a viscosity gradient
Gradients of voltage, pressure, temperature, and salinity can transport objects in micro- and nanofluidic systems by well-known mechanisms. This paper explores the dynamics of particles in a viscosity gradient with numerical simulations. The different stochastic rules used to integrate the random motion of Brownian particles affect the steady-state distribution of particles in a diffusivity gradient. Importantly, the simulations illuminate the important role that the boundary conditions play, disallowing a steady-state flux when the boundary conditions mimic those of a closed container, but allowing flux when they mimic electrodes. These results provide an interpretation for measurements of a steady ionic current flowing between electrodes separated by a nanofluidic channel with a liquid viscosity gradient.
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- Award ID(s):
- 1904511
- PAR ID:
- 10472688
- Publisher / Repository:
- The Royal Society of Chemistry
- Date Published:
- Journal Name:
- Faraday Discussions
- Volume:
- 246
- ISSN:
- 1359-6640
- Page Range / eLocation ID:
- 47 to 59
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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