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Numerical simulation of the flow in an experimental device for emulsification

Numerical simulation of the flow in an experimental device for emulsification. Mag. Renate Teppner Ass.-Prof. Dr. Helfried Steiner Univ.-Prof. Dr. Günter Brenn. Part of the CONEX project:. „Emulsions with Nanoparticles for New Materials“.

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Numerical simulation of the flow in an experimental device for emulsification

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  1. Numerical simulation of the flow in an experimental device for emulsification Mag. Renate Teppner Ass.-Prof. Dr. Helfried Steiner Univ.-Prof. Dr. Günter Brenn Part of the CONEX project: „Emulsions with Nanoparticles for New Materials“ Conex mid-term meeting, Oct. 28th to 30th 2004, Warsaw

  2. Numerical simulation: flow configuration Cylindrical-gap emulsifier Z DetailZ: Processing element Cross section A-A

  3. Boundary conditions:

  4. Parameters for the numerical simulation: • Volumetric flow rate: Q = 0.13 l/s • Properties of the fluid (emulsion of water and soybean oil): r = 977.6 kg/m3, m =2.5 x 10-3 Pas -> Reynolds number at circular inlet (diameter D = 0.013 m): Re5000 • CFD-Code: FLUENT 6.1.22 • Turbulence models:-standard k-e • - realizable k-e • - RNG • near wall treatment using low Reynolds number model • Grid: 780.000 cells, structured & unstructured subdomains

  5. Results of the numerical simulation gap #1 Contours of axial velocity component in [m/s] upstream from gap#1

  6. Results of the numerical simulation Velocity vector field near gap#1

  7. Results of the numerical simulation Contours of turbulent kinetic energy kin [m2/s2]

  8. Results of the numerical simulation A,B,C,D A C B B D Contours of turbulent dissipation rate ein [m2/s3] Contours of dissipation rate ein [m2/s3] Contours of axial velocity component in [m/s]

  9. Results of the numerical simulation inside gap #1: A

  10. Results of the numerical simulation inside gap #1: A

  11. Turbulent kinetic energy k in [m2/s2] inside gaps: & A C after gaps: & B D gap

  12. Turbulence intensity : inside gaps: & A C => v-prof gap

  13. Dissipation rate e in [m2/s3] inside gaps: & A C after gaps: & B D gap : maximum of e condition inside 2nd gap relevant for final dropsize distribution C

  14. Estimation of maximum drop size dmax based on numerical results Kolmogorov-Hinze (1955): Turbulent kinetic energy spectrum inertial forces surface tension forces maximum drop size

  15. Estimation of maximum drop size dmax based on numerical results (Karabelas, 1978) with dmax according to Kolmogorov-Hinze (1955): Consideration of viscous forces in dispersed phase (Davis,1985):

  16. Estimation of maximum drop size dmaxbased on numerical results Dissipation rate e: volumetric average of numerical solution over annular gap volume

  17. Estimation of maximum drop size dmax based on numerical results Comparison with experimental data Exptl. dropsize data provided by Slavka Tcholakova at the LCPE, Sofia from measurements with cylindrical emulsifyer

  18. Estimation of maximum drop size dmax based on numerical results Experimental drop size pdf d95 Case 1 : Case 1: d95 = 9.05 mm

  19. Estimation of maximum drop size dmax based on numerical results Experimental dropsize pdf d95 Case 2 : Case 2: d95 = 6.33 mm

  20. Estimation of maximum drop size dmax based on numerical results Experimental dropsize pdf d95 Case 3 : Case 3: d95 = 5.17 mm

  21. Estimation of maximum drop size dmax based on numerical results Comparison with experimental data Exptl. drop size data provided by Slavka Cholakova at LCPE Sofia from measurements with cylindrical emulsifier

  22. Conclusions & further work Conclusions: • strong contraction of the flow in the first gap enforces homogeneity in the circumferential direction • flow around the processing element = axisymmetric (2D) • flow is insensitive to up-stream conditions • strong enhancement of turbulent motion in the wake downstream from every gap • gap-to-gap increase of the mean dissipation rate inside the gap • design criterion for the processing element • strong spatial variation of the dissipation rate e inside each gap • identification of the relevant input value into break-up models ? • how assess the predictive capability of the break-up models ?

  23. Further work Simulation of the flow in the plane emulsifier: flow gap obstacles gap

  24. Further work Simulation of the flow in the plane emulsifier: • Main issues: • Two cylindrical obstacles upstream from the gap: is the gap flow still • practically homogeneous in spanwise direction? • Variation of the geometry of the processing element: 1,2,3 gaps • effect on achievable turbulence intensity and dissipation rate?

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