.png){kind=icon}
Return
Neural cellular automata for solidification microstructure modelling
.png){kind=icon}
OA
AI
DOI：10.1016/j.cma.2023.116197.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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.& COPY; 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Keywords:
Microstructure modelling
Convolutional neural networks
Computational speed
Cellular automata
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7.3
Papers:
1.3W
Citations:
5.6W
Organization
Cited Papers
Grain growth competition during thin-sample directional solidification of dendritic microstructures: A phase-field study.png)
ACTA MATERIALIAOAAI
ACTA MATERIALIAIF9.3
OAAIShareSaveLearning two-phase microstructure evolution using neural operators and autoencoder architectures
OAAI
OAAIShareSaveShareSaveInteractions between adenylate cyclase inhibitors and beta-adrenoceptors in isolated human fat cells
PREAI
ShareSaveShareSaveMachine learning based surrogate modeling approach for mapping crystal deformation in three dimensionsSCRIPTA MATERIALIA
SCRIPTA MATERIALIAIF5.6
PREAI
ShareSave3D Multi-Track and Multi-Layer Epitaxy Grain Growth Simulations of Selective Laser MeltingMATERIALSOAAI
MATERIALSIF3.2
OAAIShareSave
View more