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Microgravity - Science and Technology

, Volume 16, Issue 1–4, pp 236–241 | Cite as

Simulation of particle agglomeration and fragmentation in a low gravity environment

  • C. Keith Scott
  • Wen Chao Chen
  • Yves B. Trudeau
  • Kenneth Oxorn
Article
  • 67 Downloads

Abstract

We are developing simulation tools to design aerosol experiments in a space environment. The simulations will be used to assess trade-offs among the level of gravity, active experimental volume, particle density and primary particle size. In our previous work [1] we simulated the formation of particle clusters in a low gravity environment using a modified version of the CONTAIN code [2]. The model did not include the effect of cluster fragmentation on the particle size distribution and deposition on the cell walls. Before implementing complex modifications to the CONTAIN code we have investigated the effects of fragmentation using the Monte Carlo (MC) method to simulate aerosol dynamics. The constant-N Monte Carlo method developed by the Matsoukas group [3–5] was used. In this method the number of particles in the system is kept constant and the mean cluster volume is increased or decreased depending on the event (fragmentation, agglomeration,…). We are particularly interested in measuring the average volume of clusters and probability, Pk, of finding a cluster containing k primary particles. Both quantities are measurable in a low microgravity experiment. Results are presented for different levels of gravity, particle density and fragmentation kernel. The results demonstrate the potential benefits of a full simulation of the planned experiments.

Keywords

Agglomeration Monte Carlo Monte Carlo Simulation Fragmentation Model Particle Agglomeration 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    Scott, K., Chen,W.C., Trudeau, Y., Oxorn, K.: Simulation of Aerosol Dynamics to Design Experimental Cells, Spacebound 2000, Vancouver, Canada, May 14–17 (2000).Google Scholar
  2. [2]
    Murata, K.K., Williams, D.C., Tills, J., Griffith, R.O., Gido, R.G., Tadios, E.L., Davis, F.J., Martinez, G.M., Washington, K.E.: Code Manual for CONTAIN 2.0: A Computer Code for Nuclear Reactor Containment Analysis, Sandia National Laboratory, NUREG/CR-6533 (SAND97-1735), December 1997.Google Scholar
  3. [3]
    Smith, M., Matsoukas, T.: Constant-number Monte Carlo Simulation of Population Balances, Chemical Engineering Science, vol. 53, p. 1777 (1998).CrossRefGoogle Scholar
  4. [4]
    Lee, K., Matsoukas, T.: Simultaneous Coagulation and Break-up Using Constant-N Monte Carlo, Power Technology, vol. 110, p. 82 (2000).CrossRefGoogle Scholar
  5. [5]
    Lin, Y., Lee, K., Matsoukas, T.: Solution of the Population Balance Equation Using Constant-number Monte Carlo, Chemical Engineering Science, vol. 57, p. 2241 (2002).CrossRefGoogle Scholar
  6. [6]
    Efendiev, Y. andZachariah, M.R.: Hybrid Monte Carlo Method for Simulation of Two-Component Aerosol Cogulation and Phase Segregation, Journal of Colloid and Interface Science, vol. 249, p. 30 (2002).CrossRefGoogle Scholar
  7. [7]
    Liffman, K.: A Direct Simulation Monte Carlo Method for Cluster Coagulation, Journal of Computational Physics, vol. 100, p. 116 (1992).CrossRefGoogle Scholar
  8. [8]
    Williams, M.M.R.: A Unified Theory of Aerosol Coagulation, Journal of Physics, vol. D21, p. 875 (1988).Google Scholar
  9. [9]
    Family, F., Meakin, P., Deutch, J.M.: Kinetics of Coagulation with Fragmentation: Scaling Behavior and Fluctuations, Physical Review Letters, vol. 57, p. 727 (1986).CrossRefGoogle Scholar
  10. [10]
    Sintes, T., Toral, R., Chakrabarti, A.: Reversible Aggregation in Self-associating Polymer Systems, Physical Review E, vol. 50, p. 2967 (1994).CrossRefGoogle Scholar
  11. [11]
    Serra, T., Casamitjana, X.: Modelling the Aggregation and Break-up of Fractal Aggregates in a Shear Flow, Applied Science Research, vol. 59, p. 255 (1998).zbMATHCrossRefGoogle Scholar
  12. [12]
    Abdelbaky, M., Scott, C.K.: Final Report on: Particle Aggregation and the Structure of Clusters, Atlantic Nuclear Services Ltd. (1998), unpublished.Google Scholar
  13. [13]
    Fallon, T., Rogers, C.B.: Turbulence-induced Preferential Concentration of Solid Particles in Microgravity Conditions, Experiments in Fluids, vol. 33, p. 233 (2002).CrossRefGoogle Scholar
  14. [14]
    Groszmann, D., Rogers, C.: Decoupling of the Roles of Inertia and Gravity on Particle Dispersion, Fifth Microgravity Fluids Physics and Transport Phenomena Conference, NASA Glenn Research Center, Cleveland, OH, CP-2000-210470, August 9, 2000, p. 1298.Google Scholar

Copyright information

© Springer 2005

Authors and Affiliations

  • C. Keith Scott
    • 1
  • Wen Chao Chen
    • 2
  • Yves B. Trudeau
    • 2
  • Kenneth Oxorn
    • 2
  1. 1.Atlantic Nuclear Services Ltd.Fredericton
  2. 2.ANIQ R&D Ltd., Laboratoire René-J.-A.-LévesqueUniversité de MontréalMontréal

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