## Abstract

Dissipative particle dynamics (DPD) and its generalization - the fluid particle model (FPM) - represent the 'fluid particle' approach for simulating fluid-like behavior in the mesoscale. Unlike particles from the molecular dynamics (MD) method, the 'fluid particle' can be viewed as a 'droplet' consisting of liquid molecules. In the FPM, 'fluid particles' interact by both central and non-central, short-range forces with conservative, dissipative and Brownian character. In comparison to MD, the FPM method In three dimensions requires two to three times more memory load and a three times greater communication overhead. Computational load per step per particle is comparable to MD due to the shorter interaction range allowed between 'fluid particles' than between MD atoms. The classical linked-Cells technique and decomposing the computational box into strips allow for rapid modifications of the code and for implementing non-cubic computational boxes. We show that the efficiency of the FPM code depends strongly on the number of particles simulated, the geometry of the box and the computer architecture. We give a few examples from long FPM simulations involving up to 8 million fluid particles and 32 processors. Results from FPM simulations in three dimensions of the phase separation in binary fluid and dispersion of the colloidal slab are presented. A scaling law for symmetric quench in phase separation has been properly reconstructed. We also show that the microstructure of dispersed fluid depends strongly on the contrast between the kinematic viscosities of this fluid phase and the bulk phase. This FPM code can be applied for simulating mesoscopic flow dynamics in capillary pipes or critical flow phenomena in narrow blood vessels.

Original language | English (US) |
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Pages (from-to) | 137-161 |

Number of pages | 25 |

Journal | Concurrency Computation |

Volume | 14 |

Issue number | 2 |

DOIs | |

State | Published - Feb 2002 |

## Keywords

- Blood flow simulation
- Checkerboard periodic boundary conditions
- Dispersion
- Fluid particles
- Parallel algorithm
- Phase separation