GPU parallel computation of dendrite growth competition in forced convection using the multi-phase-field-lattice Boltzmann model

A graphics-processing-unit (GPU)-parallel-based computational scheme is developed to realize the competitive growth process of converging bi-crystal in two-dimensional states in the presence of forced convection conditions by coupling a multi-phase field model and a lattice Boltzmann model. The elimination mechanism in the evolution process is analyzed for the three conformational schemes constituting converging bi-crystals under pure diffusion and forced convection conditions, respectively, expanding the research of the competitive growth of columnar dendrites under melt convection conditions. The results show that the elimination mechanism for the competitive growth of converging bi-crystals of all three configurations under pure diffusion conditions follows the conventional Walton–Chalmers model. When there is forced convection with lateral flow in the liquid phase, the anomalous elimination phenomenon of unfavorable dendrites eliminating favorable dendrites occurs in the grain boundaries. In particular, the anomalous elimination phenomenon is relatively strong in conformation 1 and conformation 2 when the orientation angle of unfavorable dendrites is small, and relatively weak in conformation 3. Moreover, the presence of convection increases the tip growth rate of both favorable and unfavorable dendrites in the grain boundary. In addition, the parallelization of the multi-phase-field-lattice Boltzmann model is achieved by designing the parallel computation of the model on the GPU platform concerning the computer-unified-device-architecture parallel technique, and the results show that the parallel computation of this model based on the GPU has absolute advantages, and the parallel acceleration is more obvious as the computation area increases.