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Particle Dispersion and Mass Transfer in Turbulent Shear Flows

  • Sean C. Garrick
  • Michael Bühlmann
Chapter
Part of the SpringerBriefs in Applied Sciences and Technology book series (BRIEFSAPPLSCIENCES)

Abstract

DNS of condensation mass transfer in particle-laden incompressible turbulent mixing layers are performed. The flows are comprised of a particle-free condensable vapor mixing with micron-size porous particles. Simulations are performed at a single Reynolds number while varying the particle Stokes number, the mass transfer and convective time scales, and the vapor concentration at the particle surface. Convection-enhanced mass transfer and the surface concentration at the gas/particle interface are of great importance in accurately predicting gas–particle mass transfer rates. Particle slip velocities are varied by considering different particle Stokes numbers. Simulations utilizing the “perfect sink” assumption are compared with simulations in which the non-zero, steady-state surface concentration is calculated taking into account the sorption properties of porous particles. Results indicate that particle dispersion is greater at lower particle Stokes numbers. However the increased particle slip velocity in the higher particle Stokes number flows result in increased condensation. Furthermore, results show that the perfect sink assumption leads to an overprediction in the condensation mass transfer rate.

References

  1. 3.
    Apte, S.V., Mahesh, K., Moin, P., Oefelein, J.C.: Large-eddy simulation of swirling particle-laden flows in a coaxial-jet combustor. Int. J. Multiphase Flow 29, 1311–1331 (2003)CrossRefMATHGoogle Scholar
  2. 5.
    Ausman, J.M., Watson, C.C.: Mass transfer in a catalyst pellet during regeneration. Chem. Eng. Sci. 17, 323–329 (1962)CrossRefGoogle Scholar
  3. 9.
    Bernal, L.P., Roshko, A.: Streamwise vortex structure in plane mixing layers. J. Fluid Mech. 170, 499–525 (1986)CrossRefGoogle Scholar
  4. 10.
    Boivin, M., Simonin, O., Squires, K.D.: Direct numerical simulation of turbulence modulation by particles in isotropic turbulence. J. Fluid Mech. 375, 235–263 (1998)CrossRefMATHGoogle Scholar
  5. 11.
    Boivin, M., Simonin, O., Squires, K.D.: On the prediction of gas–solid flows with two-way coupling using large eddy simulation. Phys. Fluids 12(8), 2080–2090 (2000)CrossRefMATHGoogle Scholar
  6. 12.
    Brown, G.L., Roshko, A.: On density effects and large structure in turbulent mixing layers. J. Fluid Mech. 64, 775–816 (1974)CrossRefGoogle Scholar
  7. 13.
    Calvert, S., Englund, H.M.: Handbook of Air Pollution Technology. Wiley, New York (1984)Google Scholar
  8. 14.
    Carpenter, M.H.: A high-order compact numerical algorithm for supersonic flows. In: Morton, K.W. (ed.) 12th International Conference on Numerical Methods in Fluid Dynamics. Lecture Notes in Physics, vol. 371, pp. 254–258. Springer, New York (1990)Google Scholar
  9. 16.
    Clack, H.L.: Mass transfer within electrostatic precipitators: trace gas adsorption by sorbent-covered plate electrodes. J. Air Waste Manage. Assoc. 56, 759–766 (2006)CrossRefGoogle Scholar
  10. 17.
    Clack, H.L.: Mass transfer within electrostatic precipitators: in-flight adsorption of mercury by charged suspended particulates. Environ. Sci. Technol. 40, 3617–3622 (2006)CrossRefGoogle Scholar
  11. 18.
    Clack, H.L.: Particle size distribution effects on gas–particle mass transfer within electostatic precipitators. Environ. Sci. Technol. 40, 3929–3933 (2006)CrossRefGoogle Scholar
  12. 19.
    Colucci, P.J., Jaberi, F.A., Givi, P., Pope, S.B.: Filtered density function for large eddy simulation of turbulent reacting flows. Phys. Fluids 10(2), 499–515 (1998)MathSciNetCrossRefMATHGoogle Scholar
  13. 22.
    Damköhler, G.: über die adsorptionsgeschwindigkeit von gasen an porösen adsorbentien. Z. Phys. Chem. 174, 222–238 (1935)Google Scholar
  14. 24.
    Davis, W.T.: Air Pollution Engineering Manual, 2nd edn. Wiley, New York (2000)Google Scholar
  15. 29.
    Flora, J.R.V., Hargis, R.A., O’Dowd, W.J., Pennline, H.W., Vidic, R.D.: Modeling sorbent injection for mercury control in baghouse filters: I—model development and sensitivity analysis. J. Air Waste Manage. Assoc. 53, 478–488 (2003)CrossRefGoogle Scholar
  16. 30.
    Friedlander, S.K.: Smoke, Dust, and Haze: Fundamentals of Aerosol Dynamics, 2nd edn. Oxford University Press, New York (2000)Google Scholar
  17. 32.
    Frössling, N.: über die verdunstung fallender tropfen. Gerlands Beitr. Geophys. 52, 170–215 (1938)Google Scholar
  18. 38.
    Givi, P.: Model free simulations of turbulent reactive flows. Prog. Energy Combust. Sci. 15, 1–107 (1989)CrossRefGoogle Scholar
  19. 39.
    Guan, G., Zhu, J., Xia, S., Feng, Z., Davis, E.J.: Simulation of mass transfer from an oscillating microdroplet. Int. J. Heat Mass Transf. 48, 1705–1715 (2005)CrossRefMATHGoogle Scholar
  20. 41.
    Hinds, W.C.: Aerosol Technology: Properties, Behavior, and Measurement of Airborne Particles, 2nd edn. Wiley, New York (1999)Google Scholar
  21. 42.
    Hwang, W., Eaton, J.K.: Homogeneous and isotropic turbulence modulation by small heavy (\(st \sim 50\)) particles. J. Fluid Mech. 564, 361–393 (2006)CrossRefMATHGoogle Scholar
  22. 43.
    Ishida, M., Wen, C.Y.: Comparison of kinetic and diffusional models for solid–gas reactions. AlChE J. 14(2), 311–317 (1968)CrossRefGoogle Scholar
  23. 44.
    Jaberi, F.A., Colucci, P.J., James, S., Givi, P., Pope, S.B.: Filtered mass density function for large eddy simulation of turbulent reacting flows. J. Fluid Mech. 401, 85–121 (1999)CrossRefMATHGoogle Scholar
  24. 45.
    Karatza, D., Lancia, A., Musmarra, D., Pepe, F., Volpicelli, G.: Kinetics of adsorption of mercuric chloride vapors on sulfur impregnated activated carbon. Combust. Sci. Technol. 112, 163–174 (1996)CrossRefGoogle Scholar
  25. 46.
    Karatza, D., Lancia, A., Musmarra, D., Pepe, F., Volpicelli, G.: Removal of mercuric chloride from flue gas by sulfur impregnated activated carbon. Hazard. Waste Hazard. Mater. 13(1), 95–105 (1996)CrossRefGoogle Scholar
  26. 49.
    Kiger, K.T., Lasheras, J.C.: Dissipation due to particle/turbulence interaction in a two-phase turbulent, shear layer. Phys. Fluids 9(10), 3005–3023 (1997)CrossRefGoogle Scholar
  27. 52.
    Kuan, B.T.: CFD simulation of dilute gas-solid two-phase flows with different solid size distributions in a curved 90  duct bend. ANZIAM J. 46, C744–C763 (2005)Google Scholar
  28. 54.
    Langmuir, I.: The adsorption of gases on plane surfaces of glass, mica and platinum. J. Am. Chem. Soc. 40, 1361–1403 (1918)CrossRefGoogle Scholar
  29. 55.
    Le Clercq, P.C., Bellan, J.: Direct numerical simulation of a transitional temporal mixing layer laden with multicomponent-fuel evaporating drops using continuous thermodynamics. Phys. Fluids 16(6), 1884–1907 (2004)CrossRefMATHGoogle Scholar
  30. 61.
    Ling, W., Chung, J.N., Troutt, T.R., Crowe, C.T.: Direct numerical simulation of a three-dimensional temporal mixing layer with particle dispersion. J. Fluid Mech. 358, 61–85 (1998)CrossRefMATHGoogle Scholar
  31. 67.
    MacCormack, R.W.: The effect of viscosity in hypervelocity impact cratering. AIAA Paper 69–354 (1969)Google Scholar
  32. 68.
    Madsen, J.I., Rogers, W.A., O’Brien, T.J.: Computational modeling of mercury control by sorbent injection. In: Proceedings of ASME Power 2004, 30 March–1 April, Baltimore, MD, USA (2004)Google Scholar
  33. 72.
    Meserole, F.B., Chang, R., Carey, T.R., Machac, J., Richardson, C.F.: Modeling mercury removal by sorbent injection. J. Air Waste Manage. Assoc. 49, 694–704 (1999)CrossRefGoogle Scholar
  34. 73.
    Miller, R.S., Bellan, J.: Direct numerical simulation of a confined three-dimensional gas mixing layer with one evaporating hydrocarbon-droplet-laden stream. J. Fluid Mech. 384, 293–338 (1999)CrossRefMATHGoogle Scholar
  35. 74.
    Miller, R.S., Bellan, J.: Direct numerical simulation and subgrid analysis of a transitional droplet laden mixing layer. Phys. Fluids 12(3), 650–671 (2000)CrossRefMATHGoogle Scholar
  36. 75.
    Moser, R.D., Rogers, M.M.: The three-dimensional evolution of a plane mixing layer: pairing and transition to turbulence. J. Fluid Mech. 247, 275–320 (1993)CrossRefMATHGoogle Scholar
  37. 76.
    Narayanan, C., Lakehal, D.: Particle transport and flow modification in planar temporally evolving laminar mixing layers. I. Particle transport under one-way coupling. Phys. Fluids 18, 093302–1–15 (2006)Google Scholar
  38. 77.
    Narayanan, C., Lakehal, D.: Particle transport and flow modification in planar temporally evolving laminar mixing layers. II. Flow modification due to two-way coupling. Phys. Fluids 18, 093,303–1–13 (2006)Google Scholar
  39. 78.
    Narayanan, C., Lakehal, D., Yadigaroglu, G.: Linear stability analysis of particle-laden mixing layers using lagrangian particle tracking. Powder Technol. 125, 122–130 (2002)CrossRefGoogle Scholar
  40. 80.
    Pope, S.B.: Turbulent Flows. Cambridge University Press, Cambridge (2000)CrossRefMATHGoogle Scholar
  41. 81.
    Ranz, W.E., Marshall, W.R.: Evaporation from drops, part I. Chem. Eng. Prog. 48(3), 141–146 (1952)Google Scholar
  42. 82.
    Ranz, W.E., Marshall, W.R.: Evaporation from drops, part II. Chem. Eng. Prog. 48(4), 173–180 (1952)Google Scholar
  43. 83.
    Rawlings, J.B., Ekerdt, J.G.: Chemical Reactor Analysis and Design Fundamentals. Nob Hill Publishing, Madison (2002)Google Scholar
  44. 85.
    Roshko, A.: Structure of turbulent shear flows: a new look. AIAA J. 14(10), 1349–1357 (1976)CrossRefGoogle Scholar
  45. 87.
    Ruckenstein, E., Vaidyanathan, A.S., Youngquist, G.R.: Sorption by solids with bidisperse pore structures. Chem. Eng. Sci. 26, 1305–1318 (1971)CrossRefGoogle Scholar
  46. 88.
    Ruthven, D.M.: Principles of Adsorption and Adsorption Processes. Wiley, New York (1984)Google Scholar
  47. 89.
    Rütten, F., Meinke, M., Schröder, W.: Large-eddy simulations of 90 pipe bend flows. J. Turbul. 2, 1–14 (2001)CrossRefGoogle Scholar
  48. 92.
    Salazar, J.P.L.C., de Jong, J., Cao, L., Woodward, S., Meng, H., Collins, L.R.: Experimental and numerical investigation of inertial particle clustering in isotropic turbulence. J. Fluid Mech. 600, 245–256 (2008)CrossRefMATHGoogle Scholar
  49. 95.
    Samimy, M., Lele, S.K.: Motion of particles with inertia in a compressible free shear layer. Phys. Fluids 3(8), 1915–1923 (1991)CrossRefGoogle Scholar
  50. 96.
    Sandham, N.D., Reynolds, W.C.: Three-dimensional simulations of large eddies in the compressible mixing layer. J. Fluid Mech. 224, 133–158 (1991)CrossRefMATHGoogle Scholar
  51. 97.
    Scala, F.: Simulation of mercury capture by activated carbon injection in incinerator flue gas. 1. In-duct removal. Environ. Sci. Technol. 35, 4367–4372 (2001)Google Scholar
  52. 99.
    Scala, F.: Modeling mercury capture in coal-fired power plant flue gas. Ind. Eng. Chem. Res. 43, 2575–2589 (2004)CrossRefGoogle Scholar
  53. 107.
    Squires, K.D., Eaton, J.K.: Preferential concentration of particles by turbulence. Phys. Fluids A 3(5), 1169–1178 (1991)CrossRefGoogle Scholar
  54. 110.
    Thiele, E.W.: Relation between catalytic activity and size of particle. Ind. Eng. Chem. 31(7), 916–920 (1939)CrossRefGoogle Scholar
  55. 111.
    Tu, J.Y., Fletcher, C.A.J.: Numerical computation of turbulent gas-solid particle flow in a 90 bend. AlChE J. 41, 2187–2197 (1995)CrossRefGoogle Scholar
  56. 115.
    Wang, Q., Squires, K.D.: Large eddy simulation of particle-laden turbulent channel flow. Phys. Fluids 8(5), 1207–1223 (1996)CrossRefMATHGoogle Scholar
  57. 116.
    White, H.J.: Industrial Electrostatic Precipitation. Addison-Wesley, Reading, MA (1963)Google Scholar
  58. 118.
    Yan, Y., Peng, X.F., Lee, D.J.: Transport and reaction characteristics in flue gas desulfurization. Int. J. Therm. Sci. 42, 943–949 (2003)CrossRefGoogle Scholar
  59. 120.
    Zhu, J., Zheng, F., Laucks, M.L., Davis, E.J.: Mass transfer from an oscillating microsphere. J. Colloid Interface Sci. 249, 351–358 (2002)CrossRefGoogle Scholar

Copyright information

© The Author(s) 2018

Authors and Affiliations

  • Sean C. Garrick
    • 1
  • Michael Bühlmann
    • 2
  1. 1.Department of Mechanical EngineeringUniversity of MinnesotaMinneapolisUSA
  2. 2.University of MinnesotaMinneapolisUSA

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