135 citations · 541 across the 18 of their papers we have counts for
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physics.flu-dyn2023
PoroTwin: A digital twin for a FluidFlower rig
Eirik Keilegavlen, Eivind Fonn, Kjetil Johannessen +6
We present a framework for integrated experiments and simulations of tracer transport in heterogeneous porous media using digital twin technology. The physical asset in our setup i…
physics.flu-dyn2021
Multi-fidelity information fusion with concatenated neural networks
Suraj Pawar, Omer San, Prakash Vedula +2
Recently, computational modeling has shifted towards the use of deep learning, and other data-driven modeling frameworks. Although this shift in modeling holds promise in many appl…