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Pattern formation in reverse filtration combustion.

Chuan Lu1, Yannis C Yortsos

  • 1Department of Chemical Engineering, University of Southern California, Los Angeles, California 90089-1211, USA.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|October 26, 2005
PubMed
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This study uses a pore-network simulator to investigate pattern formation in reverse filtration combustion. Results reveal unstable, fingered patterns of burned fuel, influenced by parameters like Peclet number.

Area of Science:

  • Combustion science
  • Porous media physics
  • Computational fluid dynamics

Background:

  • Reverse filtration combustion is a complex process occurring in porous media.
  • Understanding pattern formation is crucial for controlling combustion efficiency and safety.
  • Previous studies in Hele-Shaw cells showed similar unstable patterns.

Purpose of the Study:

  • To simulate and analyze pattern formation in reverse filtration combustion using a pore-network model.
  • To investigate the influence of pore-level mechanisms on combustion patterns.
  • To study the effect of parameters like Peclet number on pattern characteristics.

Main Methods:

  • Development of a two-dimensional pore-network simulator.
  • Inclusion of pore-level mechanisms: heat and mass transfer, reaction kinetics.

Related Experiment Videos

  • Simulation of both adiabatic and non-adiabatic combustion scenarios with heat loss.
  • Sensitivity analysis on parameters such as Peclet number.

    • Main Results:

    • Observed development of unstable, fingered patterns of burned fuel.
    • Patterns are analogous to those seen in Hele-Shaw cell reverse combustion.
    • Sensitivity analysis revealed the impact of parameters on pattern morphology.
    • Finger spacing and width were analyzed using a selection principle.

    Conclusions:

    • Pore-network simulation effectively captures pattern formation in reverse filtration combustion.
    • The study provides insights into the fundamental mechanisms driving unstable combustion patterns.
    • Findings contribute to the understanding of combustion dynamics in porous media and offer a basis for predictive modeling.