# Graph neural networks for laminar flow prediction around random 2D shapes

@inproceedings{Chen2021GraphNN, title={Graph neural networks for laminar flow prediction around random 2D shapes}, author={Junfeng Chen and Elie Hachem and Jonathan Viquerat}, year={2021} }

In the recent years, the domain of fast flow field prediction has been vastly dominated by pixel-based convolutional neural networks. Yet, the recent advent of graph convolutional neural networks (GCNNs) have attracted a considerable attention in the computational fluid dynamics (CFD) community. In this contribution, we proposed a GCNN structure as a surrogate model for laminar flow prediction around 2D obstacles. Unlike traditional convolution on image pixels, the graph convolution can be… Expand

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