PhD Studentship: EPSRC Supported EngD: Prediction of Flow and Mixing of Rheologically Complex Fluids

An almost exponential increase in the computational speed, miniaturization and the resulting decrease in the cost of computing in the recent past has led to huge interest towards In-Silico first approaches for solving engineering problems. This is especially true for CFD, where the use of finer meshes and more complex models leads to more accurate results. However, although handling many fluid flow applications is possible computationally, understanding the flow behaviour of many complex fluids and creating realistic flow/mixing models remains a challenge. A variety of complex fluids are encountered in industry in diverse fields of formulation engineering (e.g. foods, home and personal care, pharmaceuticals, paints, lubricants, etc.). During the processing of various formulations at lab/industry scale, phase changes often occur, driven by changes in temperature (T), pH, and composition (xi). This can result in complex fluids comprising mixtures of meso-phases, solids, isotropic liquids, etc., which can completely alter the rheology of the fluid, potentially leading to undesired inhomogeneities in terms of pH, T, and xi and loss of structure/performance. Additionally, the complex rheology can also become a huge scale-up challenge. There is, therefore, a clear need for models to capture this behaviour accurately so In-Silico first tools can be further developed to help understand and scale-up processing of many complex formulations. The main Objective of this work is to study experimentally, the flow and mixing behaviour of complex fluids comprising of solids, mesophases and isotropic liquids. The knowledge can subsequently be converted to rheology and CFD models.

This problem has 3 main sub-challenges.

1. Study the flow/mixing behaviour of complex fluids of varying rheology using Positron Emission Particle Tracking (PEPT) methodology. Flow behaviour will be studied on a range of batch and continuous pilot/lab scale processing equipment, such as ploughshare mixer, sigma mixer, screw extruder, etc.
2. Adapt and develop methods to measure and characterize the rheology of complex formulations, and fit rheological models that capture the effect of xi, T, etc as well as time and deformation rate.
3. Develop numerical methods to capture the flow behaviour and produce realistic predictions of the flow/mixing during processing.

The work planned is directed towards identifying the abilities and gaps of rheometers and CFD in understanding the rheologically complex flows in industrial equipment and developing PEPT based experimental techniques to help validate results. These efforts, eventually, will help towards creating scale-up rules for different processing equipment of interest that are commonly used to handle highly viscous and complex fluids. This output will be relevant to a range of processes and formulations in a wide range of industries beyond that of the industrial partner. To enable better understanding of the systems, the student may visit state of the art R&D facilities available with the industry partner (in India and USA). The student will also have access to CFD/DEM platforms/code available with the industry partner. The work will build on the success of just-completing project in which the CFD model has been developed and validated for a steady state system.

The project will be supervised by Drs Andrew Ingram and Christopher Windows-Yule.

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