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Using Physics-Informed Neural Networks for Solving Navier-Stokes Equations in Complex Scenarios

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Using Physics-Informed Neural Networks for Solving Navier-Stokes Equations in Complex Scenarios

Additional material videos: from left to right: OpenFoam, our Solution,
the estimated error in the flow field (please note that the error has a different scale)

Multi Layer Perceptron vs Modified Fourier Network (Section 6.2)

Multi Layer Perceptron

>
Modified Fourier Network

Results on different layer widths (Section 6.4)

Layer widths = 256

Layer widths = 512

Results on different piece geometries (Section 6.5)

Single Box

Circular Cylinder

Three Boxes

Results with fine-tuning, 60000 epochs (Section 7.1)

Single Box to Circular Cylinder

Single box to Three Boxes

Results with multi resolution learning (Section 7.2)

Multi resolution (a)

Multi resolution (b)

Results with parametrized learning (Section 7.3)

Big rectangle

Small rectangle

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