From the 2 of 17 linked papers with an AI index.
15 papers · 1 filter
Divide and conquer complex flows. Part I: cluster and manifold-based local analysis
Qihong L. Li-Hu, Guy Y. Cornejo Maceda, Andrea Ianiro +1
The paper introduces a data‑driven framework that uses manifold learning and unsupervised clustering to automatically partition complex fluid‑flow domains into subregions with simi…
Feature-based manifold model of actuated wakes
Alicia RodrÃguez-Asensio, Guy Y. Cornejo Maceda, Bernd R. Noack +2
The paper presents a feature‑based reduced‑order model that predicts the transient dynamics of bluff‑body wakes under arbitrary time‑varying actuation, using a manifold of dynamic…
Information decomposition for disentangled and interpretable manifold learning of fluid flows via variational autoencoders
Zhiyuan Wang, Iacopo Tirelli, Stefano Discetti +1
We introduce an information-theoretic framework that uses variational autoencoders (VAEs) to extract compact, physically interpretable manifolds from high-dimensional flow-field da…
Drag reduction via separation control using plasma actuators on a truck cabin side
Lucas Schneeberger, Stefano Discetti, Andrea Ianiro
We investigate the drag reduction on a heavy-duty vehicle using dielectric-barrier discharge plasma actuators located on the A-pillars. An experimental campaign is carried out on a…
Meshless Super-Resolution of Scattered Data via constrained RBFs and KNN-Driven Densification
Iacopo Tirelli, Miguel Alfonso Mendez, Andrea Ianiro +1
We propose a novel meshless method to achieve super resolution from scattered data obtained from sparse, randomly positioned sensors such as the particle tracers of particle tracki…
Model-based time super-sampling of turbulent flow field sequences
Qihong Lorena Li-Hu, Patricia GarcÃa-Caspueñas, Andrea Ianiro +1
We propose a novel method for model-based time super-sampling of turbulent flow fields. The key enabler is the identification of an empirical Galerkin model from the projection of…