Laminar flow of two miscible fluids in a simple network

TL;DR

This paper investigates how simple networks with laminar flow of two miscible Newtonian fluids can exhibit multiple stable equilibrium states, combining theoretical modeling, experiments, and simulations to understand phase distribution and non-linear behavior.

Contribution

It demonstrates that even simple networks with Newtonian fluids can show multiple equilibria, providing a theoretical and experimental framework for understanding this phenomenon.

Findings

Multiple stable equilibria confirmed experimentally

Phase separation at a T-junction characterized

A predictive criterion for multiple equilibria developed

Abstract

When a fluid comprised of multiple phases or constituents flows through a network, non-linear phenomena such as multiple stable equilibrium states and spontaneous oscillations can occur. Such behavior has been observed or predicted in a number of networks including the flow of blood through the microcirculation, the flow of picoliter droplets through microfluidic devices, the flow of magma through lava tubes, and two-phase flow in refrigeration systems. While the existence of non-linear phenomena in a network with many inter-connections containing fluids with complex rheology may seem unsurprising, this paper demonstrates that even simple networks containing Newtonian fluids in laminar flow can demonstrate multiple equilibria. The paper describes a theoretical and experimental investigation of the laminar flow of two miscible Newtonian fluids of different density and viscosity through a simple network. The fluids stratify due to gravity and remain as nearly distinct phases with some mixing occurring only by diffusion. This fluid system has the advantage that it is easily controlled and modeled, yet contains the key ingredients for network non-linearities. Experiments and 3D simulations are first used to explore how phases distribute at a single T-junction. Once the phase separation at a single junction is known, a network model is developed which predicts multiple equilibria in the simplest of networks. The existence of multiple stable equilibria is confirmed experimentally and a criteria for their existence is developed. The network results are generic and could be applied to or found in different physical systems.