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Dissipative-particle-dynamics model for two-phase flows.

Anupam Tiwari1, John Abraham

  • 1School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA. tiwari0@ecn.purdue.edu

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|February 7, 2007
PubMed
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This study introduces a Dissipative Particle Dynamics (DPD) model for simulating liquid-vapor two-phase flows. The model accurately captures phase segregation and surface tension, validated against analytical solutions.

Area of Science:

  • Computational physics and fluid dynamics.
  • Mesoscopic simulations of multiphase systems.

Background:

  • Dissipative Particle Dynamics (DPD) is a mesoscopic simulation technique.
  • Accurate modeling of liquid-vapor interfaces and two-phase flows is crucial in various scientific and engineering fields.

Purpose of the Study:

  • To develop and validate a DPD model for simulating two-phase flows (liquid and vapor).
  • To incorporate mean-field theory and a van der Waals equation of state for phase segregation.
  • To model surface tension using higher-order density gradients and long-range attractive forces.

Main Methods:

  • Utilized Dissipative Particle Dynamics (DPD) as the core mesoscopic simulation method.
  • Employed mean-field theory and a van der Waals equation of state to simulate phase segregation.

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  • Modeled surface tension with a term accounting for density gradients and attractive forces.

    • Main Results:

    • Successfully simulated phase segregation between liquid and vapor phases.
    • Validated the model's ability to reproduce Laplace's law for liquid cylinders of varying sizes.
    • Demonstrated accurate simulation of liquid cylinder oscillations and capillary waves, comparing favorably with analytical solutions.

    Conclusions:

    • The presented DPD model provides a robust framework for simulating liquid-vapor two-phase flows.
    • The model effectively captures key physical phenomena such as phase segregation and surface tension.
    • The validation against analytical solutions confirms the model's accuracy and applicability.