514 citations · 1k across the 6 of their papers we have counts for
7 papers
Physically Organized Latent Spaces in Unsupervised Autoencoders: Evidence from Aerodynamic Databases
Renato Tognaccini, Ettore Saetta, Gianluca Iaccarino
Using aerodynamic databases of progressively increasing complexity - from linear analytical theory to nonlinear separated RANS flows - we demonstrate that an autoencoder, trained s…
Learning Aerodynamics for the Control of Flying Humanoid Robots
Antonello Paolino, Gabriele Nava, Fabio Di Natale +8
Robots with multi-modal locomotion are an active research field due to their versatility in diverse environments. In this context, additional actuation can provide humanoid robots…
Effect of span size in Scale Resolving Simulations of airfoil stall and post-stall
Francesco Mario D'Afiero, Renato Tognaccini, Gianluca Iaccarino
In aerodynamic design, the use of Computational Fluid Dynamics (CFD) tools has long relied on Reynolds-Averaged Navier-Stokes (RANS) and Unsteady RANS (URANS) turbulence models. Ho…
Neural network-based closure models for large-eddy simulations with explicit filtering
Mark Benjamin, Gianluca Iaccarino
Data from direct numerical simulations of turbulent flows are commonly used to train neural network-based models as subgrid closures for large-eddy simulations; however, models wit…
A systematic dataset generation technique applied to data-driven automotive aerodynamics
Mark Benjamin, Gianluca Iaccarino
A novel strategy for generating datasets is developed within the context of drag prediction for automotive geometries using neural networks. A primary challenge in this space is co…
Physics-Informed Machine Learning Approach for Augmenting Turbulence Models: A Comprehensive Framework
Jin-Long Wu, Heng Xiao, Eric Paterson
Reynolds-averaged Navier-Stokes (RANS) equations are widely used in engineering turbulent flow simulations. However, RANS predictions may have large discrepancies due to the uncert…
A Comprehensive Physics-Informed Machine Learning Framework for Predictive Turbulence Modeling
Jian-Xun Wang, Jinlong Wu, Julia Ling +2
Although an increased availability of computational resources has enabled high-fidelity simulations of turbulent flows, the RANS models are still the dominant tools for industrial…