Classification of Computer Aided Engineering (CAE) Parts Using Graph Convolutional Networks. (arXiv:2202.11289v1 [cs.LG])

CAE engineers work with hundreds of parts spread across multiple body models.
A Graph Convolutional Network (GCN) was used to develop a CAE parts classifier.
As many as 866 distinct parts from a representative body model were used as
training data. The parts were represented as a three-dimensional (3-D) Finite
Element Analysis (FEA) mesh with values of each node in the x, y, z coordinate
system. The GCN based classifier was compared to fully connected neural network
and PointNet based …

arxiv cae classification computer aided engineering engineering graph networks