Generation of design allowables on the open hole tensile strength of composite laminates using sensitivity analysis and uncertainty quantification framework

Aeronautical industries are concerned about the cost effective generation of design allowables for composite laminates. Design allowables take into account the variabilities arising from different sources (material, manufacturing, defects etc.,) which are determined using expensive and time consuming experimental campaigns....

Nonlinear State-Space Generalizations of Graph Convolutional Neural Networks

Graph convolutional neural networks (GCNNs) learn compositional representations from network data by nesting linear graph convolutions into nonlinearities. In this work, we approach GCNNs from a state-space perspective revealing that the graph convolutional module is a minimalistic linear state-space model, in which the state update matrix is...

Mapping business models for social service design in healthcare