4 papers
Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting
Gabriele Immordino, Andrea Vaiuso, Andrea Da Ronch +1
This study presents a framework for predicting unsteady transonic wing pressure distributions, integrating an autoencoder architecture with graph convolutional networks and graph-b…
Parametric Nonlinear Volterra Series via Machine Learning: Transonic Aerodynamics
Gabriele Immordino, Andrea Da Ronch, Marcello Righi
This study introduces an approach for modeling unsteady transonic aerodynamics within a parametric space, using Volterra series to capture aerodynamic responses and machine learnin…
Predicting Transonic Flowfields in Non-Homogeneous Unstructured Grids Using Autoencoder Graph Convolutional Networks
Gabriele Immordino, Andrea Vaiuso, Andrea Da Ronch +1
This paper focuses on addressing challenges posed by non-homogeneous unstructured grids, commonly used in Computational Fluid Dynamics (CFD). Their prevalence in CFD scenarios has…
-based sparsification of energy interactions in two-dimensional turbulent flows
Riccardo Rubini, Davide Lasagna, Andrea Da Ronch
In this paper, sparsity-promoting regression techniques are employed to automatically identify from data relevant triadic interactions between modal structures in large Galerkin-ba…