16 citations · 17 across the 5 of their papers we have counts for
5 papers
The balance between compactness and forecast accuracy of data-driven latent-space reduced-order models in controlled wake flows
Alberto Solera-Rico, Patricia García-Caspueñas, Carlos Sanmiguel Vila +1
Model-based active flow control requires predictive models that are accurate, stable, and fast enough for real-time optimisation. In controlled wake flows, this is often achieved t…
Reducing base drag on road vehicles using pulsed jets optimized by hybrid genetic algorithms
Isaac Robledo, Juan Alfaro, Víctor Duro +3
Aerodynamic drag on flat-backed vehicles like vans and trucks is dominated by a low-pressure wake, whose control is critical for reducing fuel consumption. This paper presents an e…
A framework for realisable data-driven active flow control using model predictive control applied to a simplified truck wake
Alberto Solera-Rico, Carlos Sanmiguel Vila, Stefano Discetti
We present a data-driven active flow control framework designed for deployment with few non-intrusive sensors. The method builds upon Artificial Intelligence driven reduced-order p…
Towards aerodynamic surrogate modeling based on -variational autoencoders
Víctor Francés-Belda, Alberto Solera-Rico, Javier Nieto-Centenero +3
Surrogate models that combine dimensionality reduction and regression techniques are essential to reduce the need for costly high-fidelity computational fluid dynamics data. New ap…
-Variational autoencoders and transformers for reduced-order modelling of fluid flows
Alberto Solera-Rico, Carlos Sanmiguel Vila, M. A. Gómez +4
Variational autoencoder (VAE) architectures have the potential to develop reduced-order models (ROMs) for chaotic fluid flows. We propose a method for learning compact and near-ort…