GPU-Accelerated Cellular Automaton Model for Grain Growth during Directional Solidification of Nickel-Based Superalloy

Abstract

To accelerate the large-scale cellular automaton (CA) simulation for grain growth, a parallel CA model for grain growth was developed. The model was implemented based on the compute unified device architecture (CUDA) parallel computing platform. The model was verified by the grain growth of a single crystal and the columnar-to-equiaxed transition (CET) of an Al-7wt% Si specimen of uniform undercooling with a constant cooling rate. The grid independence of the model was verified. The grain growth of a plate-like casting of nickel-based superalloy during directional solidification process was simulated and the obtained results of grain density at each section with different heights were compared with the experimental data. The CET transition of directional solidified Al-7wt% Si cylindrical ingot was simulated. The grain texture and cooling curves were in good agreement with experimental results from the literature. Finally, high parallel performance of the CA model was obtained and evaluated.

Moving Multiscale Modelling to the Edge: Benchmarking and Load Optimization for Cellular Automata on Low Power Microcomputers

“…The last mode used in this work is GPU-mode. In this case, the possibilities of GPU acceleration were used: CA evolution parallelizes well on GPUs [23,24]. For GPU computations, WS with NVidia RTX 2080ti and Jetson Nano with 128 CUDA cores were used.…”

“…In this work, particular attention is paid to grain growth process using Cellular Automata (CA). According to the current approaches to CA, it parallelizes very well on GPU streaming processors [23,24]. Using this approach the execution time can be improved by several times.…”

Study of Grain Growth in a Ni-Based Superalloy by Experiments and Cellular Automaton Model

“…Cellular automaton (CA) has an intrinsic advantage over the description and visualization of microstructural evolution in metals and alloys [19,20]. It has been successfully applied to describe the evolution of the grain structure in alloy steels [21,22], titanium alloys [23][24][25], and Ni-based superalloys [26][27][28].…”