activity
20222026
most citedImproving aircraft performance using machine learning: a review

194 citations · 362 across the 21 of their papers we have counts for

collaborators
Showing 2023Show all

7 papers · 1 filter

cs.CE2023★ 5 cited

Low-cost singular value decomposition with optimal sensor placement

Ashton Hetherington, Soledad Le Clainche

This paper presents a new method capable of reconstructing datasets with great precision and very low computational cost using a novel variant of the singular value decomposition (…

physics.flu-dyn2023★ 17 cited

A unified view of elastic and elasto-inertial turbulence in channel flows at low and moderate Reynolds numbers

Giulio Foggi Rota, Christian Amor, Soledad Le Clainche +1

The chaotic flow of elastic fluids at low Reynolds number (Re) is typically distinguished into elasto-inertial and elastic turbulence (EIT/ET). However, the clear separation among…

cs.CE2023★ 4 cited

ModelFLOWs-app: data-driven post-processing and reduced order modelling tools

A. Hetherington, A. Corrochano, R. Abadía-Heredia +6

This article presents an innovative open-source software named ModelFLOWs-app, written in Python, which has been created and tested to generate precise and robust hybrid reduced or…

physics.flu-dyn2023★ 3 cited

Deep Learning combined with singular value decomposition to reconstruct databases in fluid dynamics

Paula Díaz, Adrián Corrochano, Manuel López-Martín +1

Fluid Dynamics problems are characterized by being multidimensional and nonlinear. Therefore, experiments and numerical simulations are complex and time-consuming. Motivated by thi…

physics.flu-dyn2023★ 2 cited

Hierarchical Higher-Order Dynamic Mode Decomposition for Clustering and Feature Selection

Adrián Corrochano, Giuseppe D'Alessio, Alessandro Parente +1

In this work, a new algorithm based on the application of higher-order dynamic mode decomposition (HODMD) is proposed for feature selection and variables clustering in reacting flo…

cs.LG2023★ 2 cited

A predictive physics-aware hybrid reduced order model for reacting flows

Adrián Corrochano, Rodolfo S. M. Freitas, Alessandro Parente +1

In this work, a new hybrid predictive Reduced Order Model (ROM) is proposed to solve reacting flow problems. This algorithm is based on a dimensionality reduction using Proper Orth…

physics.flu-dyn2023

Mode selection in concentric jets. The steady-steady 1:2 resonant mode interaction with O(2) symmetry

Adrián Corrochano, Javier Sierra-Ausín, Juan Ángel Martin +2

In this article, a thorough characterization of the configuration composed by two concentric jets at a low Reynolds number is presented. The analysis comprises a layout with a wide…