Computational fluid dynamics multiphase flow

Pareek, V., M.P. Brungs, and A.A. Adesina, Photocausticization of Spent Bayer liquor A Pilot-Scale Study. Advances in Environmental Research, 2003. 7(2) p. 411-420. Bertola, F., M. Vanni, and G. Baldi, Application of Computational Fluid Dynamics to Multiphase Flow in Bubble Columns. International journal of Chemical Reactor Engineering, 2003. 1 p. A3. 

Computational fluid dynamics (CFD) is rapidly becoming a standard tool for the analysis of chemically reacting flows. For single-phase reactors, such as stirred tanks and empty tubes, it is already well-established. For multiphase reactors such as fixed beds, bubble columns, trickle beds and fluidized beds, its use is relatively new, and methods are still under development. The aim of this chapter is to present the application of CFD to the simulation of three-dimensional interstitial flow in packed tubes, with and without catalytic reaction. Although the use of... 

Scheuerer G. Solution algorithms and implementations strategies for Eulerian-Eulerian multiphase-flow models. Proceedings of ACFD 2000 International Conference on Applied Computational Fluid Dynamics, Beijing, 2000. 

Care is needed when modeling compressible gas flows, flows of vapor-liquid mixtures, slurry flows, and flows of non-Newtonian liquids. Some simulators use different pipe models for compressible flow. The prediction of pressure drop in multiphase flow is inexact at best and can be subject to very large errors if the extent of vaporization is unknown. In most of these cases, the simulation model should be replaced by a computational fluid dynamics (CFD) model of the important parts of the plant. 

In solid-liquid mixing design problems, the main features to be determined are the flow patterns in the vessel, the impeller power draw, and the solid concentration profile versus the solid concentration. In principle, they could be readily obtained by resorting to the CFD (computational fluid dynamics) resolution of the appropriate multiphase fluid mechanics equations. Historically, simplified methods have first been proposed in the literature, which do not use numerical intensive computation. The most common approach is the dispersion-sedimentation phenomenological model. It postulates equilibrium between the particle flux due to sedimentation and the particle flux resuspended by the turbulent diffusion created by the rotating impeller. 

Kolev NI (2002) Multiphase Flow Dynamics 1 Fundamentals. Springer, Berlin Kuipers JAM, van Swaaij WPM (1997) Application of Computational Fluid Dynamics to Chemical Reaction Engineering. Reviews in Chemical Engineering 13 (3) 1-118. 

Caia C, Minev P (2004) A finite element method for an averaged multiphase flow model. Int J Computational Fluid Dynamics 18(2) 111-123... 

The answer to this question is mainly driven by the computational cost of solving the kinetic equation due to the large number of independent variables. In the simplest example of a 3D velocity-distribution function n t, x, v) the number of independent variables is 1 + 3 + 3 = 1. However, for polydisperse multiphase flows the number of mesoscale variables can be much larger than three. In comparison, the moment-transport equations involve four independent variables (physical space and time). Furthermore, the form of the moment-transport equations is such that they can be easily integrated into standard computational-fluid-dynamics (CFD) codes. Direct solvers for the kinetic equation are much more difficult to construct and require specialized numerical methods if accurate results are to be obtained (Filbet Russo, 2003). For example, with a direct solver it is necessary to discretize all of phase space since a priori the location of nonzero values of n is unknown, which can be very costly when phase space is not bounded. 

This partial differential equation is deterministic by nature. In practice, however, many hydrodynamic phenomena (e.g., transition from laminar to turbulent flow) have chaotic features (deterministic chaos [Stewart 1993]). The reason for this is that the Navier-Stokes equation assumes a homogeneous ideal fluid, whereas a real fluid consists of atoms and molecules. Today highly developed numerical flow simulators (computational fluid dynamics, CFD) are available for solving the Navier-Stokes equation under certain boundary conditions (e.g.. Fluent Deutschland GmbH). These even allow complex flow conditions, including particle, droplet, bubble, plug, and free surface flow, as well as multiphase flow such as that foundin fluidized-bed reactors and bubble columns, to be treated numerically [Fluent 1998]. 

Ranganathan P, Savithri S. (2010) Computational flow modeling of multiphase mechanically agitated reactors. In Ho HW, editor. Computational Fluid Dynamics. ISBN 978-953-7619-59-6, InTech. Available at http //www.mtechopen.com/books/computational-fluid-dynamics/computational-flow-modeling-of-multiphase-mechanically-agitated-reactors. p 307-334. Accessed Aug. 2013. 

Physics mathematics engineering chemistry suspension mechanics hydrodynamics computational fluid dynamics microfluidic systems coating flows multiphase flows viscous flows. 

Computational fluid dynamics (CFD) approach has become a standard tool for analyzing various situations where fluid flow has an effect on the studied processes. Numerous studies using CFD for chemical process industry have also been reported. Mostly, they have been simple cases as the system is non-reacting, contains only one phase (liquid or gas), or physical properties are assumed constant. When we are dealing with multiphase systems like gas-liquid or liquid-liquid systems we must take into account some phenomena which are not of importance for one-phase systems. The vapor-liquid or liquid-liquid equilibrium is one of these that are needed in order to model the system. In addition to that, mass and heat transfer between the phases must generally be taken into account. Also, the two-phase characteristics of fluid flow need to be taken into consideration in the CFD models. 

Gas-liquid mixed tanks are used for various operations in industrial practise. The design of gas-liquid mixing units and reactors is still done by empirical correlations, which are usually valid for specific components, mixing conditions and geometries. Computational Fluid Dynamic (CFD) techniques have been used successfully for single-phase flow, but gas-liquid flow calculations are still tedious for computers. Therefore, simpler and more accurate multiphase models are needed. In order to verify multiphase CFD calculations and to fit unknown parameters in the multiphase models, experimental local bubble size distributions and flow patterns are needed. 

Computational fluid dynamics (CFD) is now quite well established as a tool for modeling mixing processes with single-phase systems, but its success in predicting multiphase coalescing or dispersing flows has hitherto been limited. A brief overview in the context of the modeling of gas-liquid systems has been included in Section 11-3.1. 

Ronnie Andersson is an Assistant professor in Chemical Engineering at Chalmers University of Technology. He obtained his PhD at Chalmers in 2005, and from 2005 until 2010 he worked as consultant at Epsilon HighTech as a speciahst in computational fluid dynamic simulations of combustion and multiphase flows. His research projects involve physical modeling, fluid dynamic simulations, and experimental methods. 

Our understanding of the hydrodynamics of multiphase flows has progressed substantially in the recent three decades, thanks to the development of advanced experimental techniques, particularly laser Doppler anemometry (LDA), particle image velocimetry (PIV), computer-automated radioactive particle tracking (CARPT), and optical bubble probes. In addition, computational fluid dynamics (CFD) simulations allow for inner views in two-phase process equipment. 

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