How to create a digital twin with only data-driven?

I have made a set of simulations in ansys fluent where I parameterize two boundary conditions (entry and exit velocity)
of a 3d case. How can I make it so that with this set of simulations I can train a neural network (only data driven) on Nvidia modulus to be able to generate new solutions from the training data?
My goal is to create a digital twin from only data obtained from simulation and/or experiments.

Hi @matiyanez

Yes, Modulus does allow for physic-driven, hybrid, and data-driven training. An example of a pure data-driven problem is the Darcy problem which has image like data.
For point wise data you can use the PointwiseConstraint.from_numpy() where you can feed in a set of numpy dictionaries to train from. This is used in a couple spots of our examples such as the three fin heat sink which can combined with other physics-based training constraints.

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