Discovering causal relations and equations from data

G Camps-Valls, A Gerhardus, U Ninad, G Varando… - Physics Reports, 2023 - Elsevier
Physics is a field of science that has traditionally used the scientific method to answer
questions about why natural phenomena occur and to make testable models that explain the …

A deep-learning approach for reconstructing 3D turbulent flows from 2D observation data

MZ Yousif, L Yu, S Hoyas, R Vinuesa, HC Lim - Scientific Reports, 2023 - nature.com
Turbulence is a complex phenomenon that has a chaotic nature with multiple spatio-
temporal scales, making predictions of turbulent flows a challenging topic. Nowadays, an …

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

P Díaz-Morales, A Corrochano, M López-Martín… - Expert Systems with …, 2024 - Elsevier
Fluid dynamics problems are characterized by being multidimensional and nonlinear.
Therefore, experiments and numerical simulations are complex and time-consuming …

Extraction and analysis of flow features in planar synthetic jets using different machine learning techniques

E Muñoz, H Dave, G D'Alessio, G Bontempi… - Physics of …, 2023 - pubs.aip.org
Synthetic jets are useful fluid devices with several industrial applications. In this study, we
use the flow fields generated by two synchronously operating synthetic jets and simulated …

Causality analysis of large-scale structures in the flow around a wall-mounted square cylinder

Á Martínez-Sánchez, E López… - Journal of Fluid …, 2023 - cambridge.org
The aim of this work is to analyse the formation mechanisms of large-scale coherent
structures in the flow around a wall-mounted square cylinder, due to their impact on pollutant …

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

A Hetherington, A Corrochano… - Computer Physics …, 2024 - Elsevier
This article presents an innovative open-source software named ModelFLOWs-app, 1
written in Python, which has been created and tested to generate precise and robust hybrid …

[HTML][HTML] Higher order dynamic mode decomposition to model reacting flows

A Corrochano, G D'Alessio, A Parente… - International Journal of …, 2023 - Elsevier
This work presents a new application of higher order dynamic mode decomposition
(HODMD) for the analysis of reactive flows. Due to the high complexity of the data analysed …

[HTML][HTML] Data-driven assessment of arch vortices in simplified urban flows

Á Martínez-Sánchez, E Lazpita, A Corrochano… - International Journal of …, 2023 - Elsevier
Understanding flow structures in urban areas is widely recognized as a challenging concern
due to its effect on urban development, air quality, and pollutant dispersion. In this study …

[HTML][HTML] Perspectives on predicting and controlling turbulent flows through deep learning

R Vinuesa - Physics of Fluids, 2024 - pubs.aip.org
The current revolution in the field of machine learning is leading to many interesting
developments in a wide range of areas, including fluid mechanics. Fluid mechanics, and …

Aspect-ratio effect on the wake of a wall-mounted square cylinder immersed in a turbulent boundary layer

G Zampino, M Atzori, E Zea, E Otero… - International Journal of …, 2025 - Elsevier
The wake topology behind a wall-mounted square cylinder immersed in a turbulent
boundary layer is investigated using high-resolution large-eddy simulations (LES). The …