A three-dimensional (3D) lattice Boltzmann (LB) model is developed to simulate the dendritic growth during solidification of Al-Cu alloys under forced and natural convection. The LB method is used to solve for solute diffusion and fluid flow. It is assumed that the dendritic growth is driven by the difference between the local actual and local equilibrium composition of the liquid in the interface. A cellular automaton (CA) scheme is adopted to capture new interface cells. The LB models for solute transport and fluid flow are first validated against two benchmark problems. The dendrite growth model is also validated with available analytical solutions. The evolution of a 3D dendrite affected by melt convection is investigated. Also, density inversion caused by solute concentration gradient is studied. It is shown that convection can change the kinetics of growth by affecting the solute distribution around the dendrite. In addition, the growth features of two-dimensional (2D) and 3D dendrites are briefly compared. The results show that decreasing undercooling and increasing solute concentration decelerates the growth in all branches of the dendrite. While increasing fluid velocity does not significantly influence upstream and transverse arms, it decreases the growth rate in the downstream direction considerably. The size ratio of the upstream arm to the downstream arm rises by increasing inlet velocity and solute content, and decreasing undercooling. Similarly, in the case of natural convection, redistribution of solute due to buoyancy-induced flow suppresses the growth of the upward arm and accelerates the growth of the downward arm. Considering the advantages offered by the LB method, the present model can be used as a new tool for simulating 3D dendritic solidification under convection.

This paper presents a comparative study between the pseudopotential Shan-Chen model and the phase field multiphase lattice Boltzmann method for simulating bubble dynamics during dendritic solidification of binary alloys. The Shan-Chen method is an efficient lattice Boltzmann multiphase method despite having some limitations, including the generation of large spurious currents. The phase field model solves the Cahn-Hilliard equation in addition to the Navier-Stokes equation to track the interface between phases. The phase field method is more accurate than the Shan-Chen model for simulation of fluids with a high-density ratio since it generates an acceptable small spurious current, though at the expense of higher computational costs. For the simulations in this article, the multiphase lattice Boltzmann model was coupled with the cellular automata and finite difference methods to solve temperature and concentration fields. The simulated results were presented and compared regarding the ability of each model to simulate phenomena at a microscale resolution, such as Marangoni convection, the magnitude of spurious current, and the computational costs. It is shown that although Shan-Chen methods can replicate some qualitative features of bubble-dendrite interaction, the generated spurious current is unacceptably large, particularly for practical values of the density ratio between fluid and gas phases. This occurs even after implementation of several enhancements to the original Shan-Chen method. This serious limitation makes the Shan-Chen models unsuitable to simulate fluid flow phenomena, such as Marangoni convection, because the large spurious currents mask completely the physical flow.

A multi-distribution lattice Boltzmann Bhatnagar–Gross–Krook (BGK) model with a multiple-grid lattice Boltzmann (MGLB) model is proposed to efficiently simulate natural convection over a wide range of Prandtl numbers. In this method, different grid sizes and time steps for heat transfer and fluid flow equations are chosen. The model is validated against natural convection in a square cavity, since extensive benchmark solutions are available for that problem. The proposed method can resolve the computational difficulty in simulating problems with very different time scales, in particular, when using extremely low or high Prandtl numbers. The technique can also enhance computational speed and stability while keeping the simplicity of the BGK method. Compared with the conventional lattice Boltzmann method, the simulation time can be reduced up to one-tenth of the time while maintaining the accuracy in an acceptable range. The proposed model can be extended to other lattice Boltzmann collision models and three-dimensional cases, making it a great candidate for large-scale simulations.