Influence of hydrodynamic conditions on particle size distribution
Advancing the chemical engineering fundamentals
Particulate Systems (T2-3P)
Keywords: CFD, precipitation, mixing, particle size distribution, method of moments
Investigation of crystallization processes under various hydrodynamic conditions is a wide and interesting subject embedded in the wider field of complex multiphase flows. This is due to the fact that the properties, quality and amount of the particulate product depend on the mixing conditions within the reactor. For instance, a good mixing increases the interaction between the ions of a solution during a reactive crystallization (precipitation) process, enhancing the reaction rate. As another example, a reactor providing high residence times may yield larger particles. Publications describing how various particle properties are influenced by the hydrodynamic conditions are numerous, generally relying on experimental studies. As a complement, recent numerical investigations employing complex methods and models for population balance systems, micromixing, reactions rates… are developing at a rapid pace. Nevertheless, further improvements are still necessary in order to obtain a better, quantitative agreement between numerical results and experimental observations.
The particle size distribution (PSD) of a product can be considered as one of the essential criteria indicating the quality of the product. Therefore, the aim of the present work is to numerically determine the influence of the flow conditions on mean particle size and PSD in various reactors corresponding to different hydrodynamic and/or chemical conditions. The considered crystallization process takes place either within an aqueous solutions (similar to the conditions described in [1, 2]) or within a micro-emulsion [3]. Zero-, two- and three-dimensional coupled simulations of the turbulent flow and of the particle population have been performed using the industrial code FLUENT® 6.2 for the Computational Fluid Dynamics (CFD). Equations and source terms of the reaction kinetics, population balance model (PBM) and micromixing model have been defined via external user-defined scalars and functions. Various approaches for the population balance system (standard method of moments, SMM, as well as direct quadrature method of moments, DQMOM) and for micro-scale mixing (multi-environment, ME, as well as direct quadrature method of moments – interaction by exchange with the mean, DQMOM-IEM) have been compared.
The reconstruction of the obtained PSDs has been carried out according to several assumed mathematical function shapes using the first three moments of the PBM. Finally, the reconstructed PSDs and the mean particle size have been compared for the different conditions and compared as far as possible with corresponding experimental findings obtained from literature. A discussion of the obtained results and possible future improvements are proposed at the end of the work.
References:
[1] Öncül, A. A., Sundmacher, K., Seidel-Morgenstern, A., & Thévenin, D. Numerical and analytical investigation of barium sulphate crystallization. Chem. Eng. Sci., 61:652-664, 2006.
[2] Öncül, A. A., Thévenin, D., & Sundmacher, K. Numerical simulation of BaSO4 precipitation in a coaxial pipe mixer with micromixing effects. AIChE Annual Meeting Proceedings, ISBN 0-8169-1012-X, Paper No 70c, San Francisco-USA, November 12-17, 2006.
[3] Öncül, A. A., Niemann, B., Thévenin, D., & Sundmacher, K. CFD model of a semi-batch reactor for the precipitation of nanoparticles in the droplets of a microemulsion. 16th European Symp. on Computer Aided Process Eng. (ESCAPE16) & 9th Int. Symp. on Process Systems Eng. (PSE2006), ISBN 978-0-444-52257-3, Paper No: 1226, Garmisch-Partenkirchen, Germany, July 9-13, 2006.
Presented Monday 17, 13:30 to 15:00, in session Particulate Systems (T2-3P).
