Abstract
Smooth dissipative particle dynamics (SDPD) is a Lagrangian formulation of the continuum equations by the adding fluctuations, so it naturally possesses continuity and stochastic property. However, there is no clear rule to quantitatively characterize continuity and randomness. Therefore, it is crucial to propose judgment criteria for different flow regimes, so that efficient algorithms can be chosen to improve computational efficiency. Firstly, the randomness and continuity of SDPD were verified by some numerical examples. Then, three dimensionless numbers characterizing the thermal fluctuations were derived by normalizing the Navier–Stokes equations and their effects were analyzed. For isothermal flows, a dimensionless number, Macro-Mesoscopic Critical Reynolds Number (MMCR), was proposed by integrating the three dimensionless numbers mentioned above, which can determine different flow regimes. SDPD was applied to flows including Poiseuille flow, Couette flow, and flow through a square lattice of cylinders. Statistical information such as the Mathematical expectation, Variance, Kurtosis, and Autocorrelation coefficient was analyzed. Finally, we simulated the wetting using different algorithms in different regions according to the MMCR (multi-region algorithm), and compared the computational results with the SDPD method. The results indicated that MMCR can classify the different flow regimes, which greatly reduces the computational time of SDPD and helps to promote the application of the method.
