UCNN: A Convolutional Strategy on Unstructured Mesh

Understand

In machine learning for fluid mechanics, fully-connected neural network (FNN) only uses the local features for modelling, while the convolutional neural network (CNN) cannot be applied to data on structured/unstructured mesh.

• In order to overcome the limitations of FNN and CNN, the unstructured convolutional neural network (UCNN) is proposed, which aggregates and effectively exploits the features of neighbour nodes through the weight function.
• Adjoint vector modelling is taken as the task to study the performance of UCNN.
• The mapping function from flow-field features to adjoint vector is constructed through efficient parallel implementation on GPU.