Flow of Yield-Stress Fluids in Confined Geometries: An Experimental and Computational Study

Abstract

Yield-stress fluids are ubiquitous in various industries, including food processing, personal care, and pharmaceuticals. These materials exhibit many interesting dynamical behaviours not found in Newtonian fluid flow. An inability to accurately predict pressure losses in the flow through industrial processes often results in the overpressurisation of pipelines to prevent blockages, a measure that significantly undermines process economic viability and sustainability. Additionally, the high cost and challenging nature of computational fluid dynamics (CFD) simulations for yield-stress fluids calls for models that can rapidly approximate the flow in large domains to optimise system design. This thesis investigates the dynamics and dissipative characteristics of yield-stress fluid flow in confined geometries common in industry, adopting a multifaceted approach utilising experimental and numerical techniques. A study of the flow through pipe bends reveals that inertial effects result in additional pressure losses in pipe fittings attributed to secondary flow structures, similar to Newtonian fluids. However, the high viscosity of a majority of these materials minimises the influence of inertia; thus, design calculations can typically neglect minor losses. Fluid elasticity also counteracts inertial effects, provided elastic instabilities do not occur. Bend flows also reveal a novel yielding mechanism, with the central unyielded plug found in straight pipes being destroyed far upstream of a flow disturbance due to kinematic time reversibility. The flow in pipe manifolds also shows the effect. A network model is developed to predict fluid behaviour and pressure drop in networked structures and applied to flow in pipe manifolds and porous media. The network model achieves convergence within minutes using a single CPU node, yielding a remarkable reduction in computational cost compared to CFD simulations. In manifolds, the model makes accurate predictions of the fluid distribution from each outlet. Accounting for wall slip is essential as it considerably changes the distribution profile, producing more uniform distributions than a no-slip condition by reducing the disparity in resistance between different outlet branches. Furthermore, the model can predict the velocity field and pressure drop in porous media without wall slip, validated against in-house simulations and simulations from the literature. Thus far, the model can predict weak wall slip effects in porous media and will be improved in future studies to model the full range of possible conditions accurately. The experimental manifold setup is a novel approach for slip characterisation, potentially offering significant reductions in equipment cost, expertise requirements, and testing duration. Furthermore, an innovative method is identified for directly controlling the slip of microgels by modulating surface charge to manipulate the electrostatic interactions between suspended fluid particles and the wall. Negative surface charges produce repulsive Coulomb forces between like-charges, increasing the lubrication layer thickness and decreasing drag. Bubbles produced from electrolysis also increase slip as they remain trapped in the surface profile of the wall and decrease the apparent roughness. These two mechanisms for slip enhancement can be employed to decrease process energy consumption and manipulate the microstructure of materials that depend on the magnitude of slip during extrusion.

Date of Award	1 Aug 2024
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Andrew Masters (Supervisor), Anne Juel (Supervisor) & Claudio Pereira Da Fonte (Supervisor)