Computational Fluid Dynamics for Value-Added Scale-Up

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Scaling up a mixing operation involves a number of process parameters that can drastically alter both the quality and yield of a desired product. Factors such as shear rate, vorticity, and bulk movement are all critical design considerations for large-scale mixing  (Paul, Obeng, & Kresta, 2004). These factors are commonly characterized by empirical methods which can lead to difficulty in comparing scales of production due to the non-linear effects of scale-up. Computational Fluid Dynamics (CFD) modelling is a tool that may be used in conjunction with conventional methods to develop a stronger understanding of mixing processes. Engineering design practices are only as good as the information upon which they are based and CFD is a tool to allow a greater generation of information to form the basis of scale-up design calculations and decisions.

CFD Methodology

A CFD mixing study consists of three primary phases: pre-processing, solving, and post-processing (Chung, 2002). During pre-processing a mesh is generated for the physical system, often using a 3D CAD model or drawing. Pre-processing is also when the boundary and initial conditions are determined. These factors greatly affect the quality of a CFD study; great care is taken to ensure that these constraints are set appropriately. Furthermore, the thermophysical properties of the materials are identified during this phase. These include viscosity, density, heat capacity, and surface tension. Next, the solver is set up by the CFD engineer to best accomplish the goals of the study. This is carried out with the use of proprietary packages (ANSYS Fluent, SolidWorks) or in-house solutions. Lastly, during post-processing the CFD engineer works closely with the client or design engineer to guarantee that the relevant data is obtained in a presentable and functional manner.

Application to Scale-up Design

CFD studies yield the most value when used alongside conventional methods for process scale-up. CFD can be used to execute many iterative conditions forming a complex experimental design with the key findings verified by real experimentation. CFD analysis can also be crucial when performing scale-up design for high-value materials where material costs prohibit iterative experimentation. The outputs of CFD in mixing design can be broken down as follows:

Process design: Reactor temperature, pressure, RPM, etc.

Equipment design: Impeller geometry, reactor geometry, sparger/dip-tube placement, etc.

CFD studies can be used to validate operating conditions (RPM – bulk mixing), troubleshoot unknown effects (temperature profile – degree of reaction), and identify proper equipment selection (impeller type – shear). When used appropriately, CFD studies can be applied to optimize mixing conditions and equipment, leading to improved process safety and decreasing capital and operating costs. XRCC utilizes two main software packages for CFD simulations, SolidWorks Flow Simulation and OpenFOAM. The decision of which package to use depends on the simulation complexity and the degree of post-processing required. The Xerox Research Centre of Canada uses CFD studies to add value to scale-up design processes by both reducing iterative workloads as well as increasing the amount of information that engineers are able to leverage for better process design decisions.


[1] Paul, E. L., Obeng, V. A., & Kresta, S. M. (2004). Handbook of Industrial Mixing. John Wilely & Sons Inc.

[2] Chung, T. J. (2002). Computational Fluid Dynamics. Cambridge University Press.

Author: Benjamin Knapik, Process Engineering Specialist, Xerox Research Centre of Canada

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