Optimisation of the design and operation of mixing processes using computational fluid dynamics and high performance computing

Lead Research Organisation: University of Manchester
Department Name: Mechanical Aerospace and Civil Eng

Abstract

Mixing operations are an everyday routine in process industry and aim to produce manufactured fluids which cover varying needs of households, businesses and industries. The variety and the magnitude of mixing operations are easily perceived if one considers the range of industries (food, home & personal care, pharmaceutical, chemical etc.) where mixing techniques are applied and yield either intermediate or end-products. The possible outcomes of a mixing process can be broadly classified in terms of two factors; the phases involved (combinations of gas-liquid-solid) and the miscibility of the components with each other. If components are miscible the output is a solution. In case of immiscible components the outcome is either a colloid or a suspension. What distinguishes these two is the lengthscale of the dispersed phase [1]. In the former the dispersed phase ranges from a few molecules to several microns, while in the latter it is of micron order or larger [2]. Solutions are homogenous down to the molecular level, hence they are treated as a single phase fluid when the continuum approach is adopted. Colloids and suspensions, on the other hand, are of multiphase nature [3].

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/N509280/1 01/10/2015 30/09/2020
1727169 Studentship EP/N509280/1 01/04/2016 30/09/2019 Ioannis Bagkeris
 
Description The Sonolator (Sonic Corp, USA) is a high-pressure homogeniser widely used in the process industry (including the partner company Unilever) for manufacturing emulsion-based formulated products. It comprises a cylindrical inlet chamber and a cylindrical main chamber housing an elliptic shape orifice and a knife-edge blade. The processed fluid is emulsified via very high hydrodynamic stresses developed at and downstream the orifice. In this work high performance computing facilities at the University of Manchester and the Hartree Centre at STFC Daresbury are utilised to simulate emulsion formulation processes in a Sonolator using computational fluid dynamics (CFD) and population balance methods (PBM). The main findings are the following:
(a) Mean flow and turbulence field CFD results have been validated via comparisons with experimental measurements [1].
(b) Coupled CFD-PBM simulations have been performed using various modelling approaches of droplet break-up in turbulent flow. The Alopaeus et. al [2] model achieved best agreement with experimental data [3].
(c) The majority of droplet break-up is predicted by the simulations to occur at the free shear layers close to the orifice exit (within approximately 2-3 hydraulic diameters downstream the orifice). The influence of the blade on droplet break-up and dispersion is found to be small as most break-up is predicted before the blade is encountered.
(d) Traditional droplet break-up modelling in turbulent flows is based on the assumption of homogeneous isotropic turbulence (HIT) at infinite Reynolds number. While the majority of droplet break-up models in the literature follow the HIT assumption, Alopaeus et al. model has a different derivation as one of its terms, namely the drop break-up time, is based on experimental observation. It is a widely accepted model and has been employed in numerous publications. Driven by good agreement with experimental data and also by its empirical form, in the present work it is shown from a theoretical viewpoint that the drop break-up time in the Alopaeus et al. model corresponds to a strongly anisotropic turbulence condition. Thus, although they appear different, the Alopaeus et al. model and the models based on HIT may be viewed as variations driven by the underlying turbulence structure.

[1] Ryan, D.J., Simmons, M.J.H., Baker, M.R., 2017, Chem. Eng. Sci, 163: 123-136.
[2] V. Alopaeus, J. Koskinen, K. I. Keskinen, J. Majander, Chem. Eng. Sci. 2002, 57: 1815-1825.
[3] Ryan, D.J., Baker, M.R., Kowalski, A.J., Simmons, M.J.H, 2018, Chem. Eng. Sci, 189: 369-379.
Exploitation Route - Findings (a) to (c) may be put in use by process engineers in the industry, to optimise process design and scale-up of Sonolator mixers.
- Finding (d) may be taken forward by developing a model which will account for the effect of anisotropic turbulence on the velocity scaling used in droplet break-up frequency models.
Sectors Agriculture, Food and Drink,Chemicals,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology

 
Description Current practice for process design and scale-up of emulsion-based formulated products in the Fast Moving Consumer Goods industry involves extensive pilot-scale experiments based on which empirical rules between key outputs and operating parameters are developed. Key emulsion properties, such as droplet size, are sensitive to the mixing process and determine the shelf-life and consumer appeal in terms of texture and even mouth-feel of the final product. Unilever is interested in in-silico evaluation and simulation of their manufacturing processes in order to reduce the number of required pilot-scale experiments and accelerate the introduction of new and better products into the market. In this project high performance computing facilities at the University of Manchester and the Hartree Centre at STFC Daresbury are being used to perform multiphysics numerical simulations of mixing processes typically encountered during the manufacture of emulsion-based formulated food and personal-care products. More specifically, emulsion formulation processes in an industrially relevant high-pressure homogeniser (Sonolator) are simulated using computational fluid dynamics and population balance methods. Various modelling approaches of droplet break-up in turbulent flows are assessed via comparisons between computational and experimental results. These simulations allow process engineers to optimise their process designs, better predict final product properties and reduce reliance on pilot-scale experiments. This in turn leads to process intensification, waste reduction and potential cost savings for Unilever.
First Year Of Impact 2019
Sector Agriculture, Food and Drink,Chemicals
Impact Types Economic