Abstract:
The development of lattice gas model to discrete Boltzmann method is briefly introduced for modeling multiphase complex fluid systems. Based on the basic principles of statistical physics, the Boltzmann equation is given through the idea of coarse-grained modeling. The physical images of progressively refined measurements contained in the Chapman-Enskog multi-scale expansion method are analyzed, and the basic principles and main steps of Discrete Boltzmann Modeling (DBM) are given. The applications of discrete Boltzmann in phase separation, combustion and hydrodynamic instability systems are briefly reviewed. For the kinetic modeling of multiphase complex fluid systems, the key techniques are the introduction of intermolecular forces and the contribution of chemical reactions. The introduction of tracer particles of different colors makes it possible to determine the source of material particles in the mixing process under the framework of single-fluid theory. The structure formed by the distribution of tracer particles in their velocity space contains rich flow field information, which opens a new perspective for the study of complex flow field. In the case of multi-media, the correspondence between discrete Boltzmann modeling and Kinetic Macro Modeling (KMM) is one-to-several, where KMM means that to derive the macroscopic model equations from kinetic theory. As the degree of non-equilibrium of the system deepens, the complexity of discrete Boltzmann modeling and simulation increases more slowly than that of KMM and simulation. As a coarse-grained physical modeling method, discrete Boltzmann selects a perspective to study a set of kinetic properties of the system according to research requirements, so it is required that the kinetic moments describing this set of properties maintain their values in the process of model simplification. It provides a convenient and effective way to investigate the mesoscale situations where continuum modeling fails or physical functions are insufficient and molecular dynamics method is unable to do so due to the limited applicable scale.