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Level-set lattice Boltzmann method for interface-resolved simulations of immiscible two-phase flow.

Shaotong Fu1, Zikang Hao1, Weite Su1

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A new lattice Boltzmann (LB) scheme for level-set equations accurately simulates two-phase flows. This method improves interface accuracy and computational efficiency for complex fluid dynamics.

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Area of Science:

  • Computational Fluid Dynamics
  • Multiphase Flow Simulation
  • Numerical Methods

Background:

  • Simulating immiscible two-phase flows is crucial in various engineering applications.
  • Traditional level-set methods often require solving additional partial differential equations for reinitialization.
  • Existing phase-field lattice Boltzmann methods can exhibit errors in capturing interface dynamics.

Purpose of the Study:

  • To develop a novel lattice Boltzmann (LB) scheme for level-set equations to simulate immiscible two-phase flows.
  • To enhance the accuracy and efficiency of interface capturing in fluid simulations.
  • To validate the proposed method against benchmark two-phase flow problems.

Main Methods:

  • A coupled LB model for incompressible fluid and a level-set equation is proposed.
  • Level-set field reinitialization is achieved directly via a source term in the LB equation, avoiding extra PDEs.
  • Graphics Processing Unit (GPU) parallel computation is implemented for the level-set lattice Boltzmann method (LS-LBM).

Main Results:

  • The LS-LBM demonstrates significantly reduced errors in interface motion and deformation compared to classical methods.
  • Simulations of static droplet, layered Poiseuille flow, rising bubble, and Rayleigh-Taylor instability show good stability and accuracy.
  • The method achieves high computational efficiency, particularly with GPU parallelization.

Conclusions:

  • The proposed LS-LBM is a stable, accurate, and efficient method for simulating immiscible two-phase flows.
  • It effectively captures interface dynamics and handles large density ratios and high Reynolds numbers.
  • The direct reinitialization approach simplifies the simulation process and improves performance.