# An artificial neural network approach to bifurcating phenomena in computational fluid dynamics

@article{Pichi2021AnAN, title={An artificial neural network approach to bifurcating phenomena in computational fluid dynamics}, author={Federico Pichi and Francesco Ballarin and Gianluigi Rozza and Jan S. Hesthaven}, journal={ArXiv}, year={2021}, volume={abs/2109.10765} }

This work deals with the investigation of bifurcating fluid phenomena using a reduced order modelling setting aided by artificial neural networks. We discuss the POD-NN approach dealing with non-smooth solutions set of nonlinear parametrized PDEs. Thus, we study the NavierStokes equations describing: (i) the Coanda effect in a channel, and (ii) the lid driven triangular cavity flow, in a physical/geometrical multi-parametrized setting, considering the effects of the domain’s configuration on…

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