1 citations · 1 across the 4 of their papers we have counts for
4 papers
Adaptive Quantum Physics-Informed Neural Networks for Differential Equations with Applications to Fluid Dynamics
Fabio Pereira dos Santos, Renato Portugal, Júlio de Castro Vargas Fernandes +1
Physics-informed neural networks (PINNs) have emerged as a versatile approach for solving nonlinear partial differential equations (PDEs), yet achieving high accuracy efficiently u…
Statistical machine learning tools for probabilistic closures of turbulence models
Julia Domingues Lemos, Fabio Pereira dos Santos
Turbulent flow remains a challenging subject, despite extensive efforts to find analytical descriptions. Modeling small scales of motion is crucial for saving time and resources in…
Hydrodynamic characterization of bubble column using Dynamical High Order Decomposition approach
Carlos Mendez, Fabio Santos, Gabriel Gonçalves
Bubble columns are present in several applications, such as chemical and biochemical reactors and petrochemical and environmental engineering industries. This variety of applicatio…
Computational Fluid Dynamics and Machine Learning as tools for Optimization of Micromixers geometry
Daniela de Oliveira Maionchi, Luca Ainstein, Fabio Pereira dos Santos +1
This work explores a new approach for optimization in the field of microfluidics, using the combination of CFD (Computational Fluid Dynamics), and Machine Learning techniques. The…