TY - JOUR
T1 - Neural cellular automata for solidification microstructure modelling
AU - Tang, Jian
AU - Kumar, Siddhant
AU - De Lorenzis, Laura
AU - Hosseini, Ehsan
PY - 2023
Y1 - 2023
N2 - We propose Neural Cellular Automata (NCA) to simulate the microstructure development during the solidification process in metals. Based on convolutional neural networks, NCA can learn essential solidification features, such as preferred growth direction and competitive grain growth, and are up to six orders of magnitude faster than the conventional Cellular Automata (CA). Notably, NCA deliver reliable predictions also outside their training range, e.g. for larger domains, longer solidification duration, and different temperature fields and nucleation settings, which indicates that they learn the physics of the solidification process. While in this study we employ data produced by CA for training, NCA can be trained based on any microstructural simulation data, e.g. from phase-field models.
AB - We propose Neural Cellular Automata (NCA) to simulate the microstructure development during the solidification process in metals. Based on convolutional neural networks, NCA can learn essential solidification features, such as preferred growth direction and competitive grain growth, and are up to six orders of magnitude faster than the conventional Cellular Automata (CA). Notably, NCA deliver reliable predictions also outside their training range, e.g. for larger domains, longer solidification duration, and different temperature fields and nucleation settings, which indicates that they learn the physics of the solidification process. While in this study we employ data produced by CA for training, NCA can be trained based on any microstructural simulation data, e.g. from phase-field models.
KW - Cellular automata
KW - Computational speed
KW - Convolutional neural networks
KW - Microstructure modelling
UR - http://www.scopus.com/inward/record.url?scp=85163853039&partnerID=8YFLogxK
U2 - 10.1016/j.cma.2023.116197
DO - 10.1016/j.cma.2023.116197
M3 - Article
AN - SCOPUS:85163853039
SN - 0045-7825
VL - 414
JO - Computer Methods in Applied Mechanics and Engineering
JF - Computer Methods in Applied Mechanics and Engineering
M1 - 116197
ER -