2 citations · 3 across the 4 of their papers we have counts for
4 papers
Hybrid DeepONet Surrogates for Multiphase Flow in Porous Media
Ezequiel S. Santos, Gabriel F. Barros, Amanda C. N. Oliveira +6
The solution of partial differential equations (PDEs) plays a central role in numerous applications in science and engineering, particularly those involving multiphase flow in poro…
A predictive physics-aware hybrid reduced order model for reacting flows
Adrián Corrochano, Rodolfo S. M. Freitas, Alessandro Parente +1
In this work, a new hybrid predictive Reduced Order Model (ROM) is proposed to solve reacting flow problems. This algorithm is based on a dimensionality reduction using Proper Orth…
Prediction of liquid fuel properties using machine learning models with Gaussian processes and probabilistic conditional generative learning
Rodolfo S. M. Freitas, Ágatha P. F. Lima, Cheng Chen +3
Accurate determination of fuel properties of complex mixtures over a wide range of pressure and temperature conditions is essential to utilizing alternative fuels. The present work…
An encoder-decoder deep surrogate for reverse time migration in seismic imaging under uncertainty
Rodolfo S. M. Freitas, Carlos H. S. Barbosa, Gabriel M. Guerra +2
Seismic imaging faces challenges due to the presence of several uncertainty sources. Uncertainties exist in data measurements, source positioning, and subsurface geophysical proper…