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Found 5 papers, 0 papers with code
Engineering software 2.0 by interpolating neural networks: unifying training, solving, and calibration
The evolution of artificial intelligence (AI) and neural network theories has revolutionized the way software is programmed, shifting from a hard-coded series of codes to a vast neural network.
Simulation-Free Determination of Microstructure Representative Volume Element Size via Fisher Scores
We propose a simulation-free alternative that determines RVE size based only on a micrograph.
Statistical Parameterized Physics-Based Machine Learning Digital Twin Models for Laser Powder Bed Fusion Process
In the context of laser powder bed fusion (LPBF) additive manufacturing, a digital twin of the manufacturing process can offer predictions for the produced parts, diagnostics for manufacturing defects, as well as control capabilities.
An Introduction to Kernel and Operator Learning Methods for Homogenization by Self-consistent Clustering Analysis
However, for large-scale engineering problems such as concurrent multiscale simulation for mechanical properties, the training cost for the current operator learning methods is very high.
HiDeNN-PGD: reduced-order hierarchical deep learning neural networks
This paper presents a proper generalized decomposition (PGD) based reduced-order model of hierarchical deep-learning neural networks (HiDeNN).
