194 citations · 362 across the 21 of their papers we have counts for
6 papers · 1 filter
Data-driven modal decomposition methods as feature detection techniques for flow problems: a critical assessment
Beka Begiashvili, Nourelhouda Groun, Jesús Garicano-Mena +2
Modal decomposition techniques are showing a fast growth in popularity for their good properties as data-driven tools. There are several modal decomposition techniques, yet Proper…
Forecasting through deep learning and modal decomposition in two-phase concentric jets
León Mata, Rodrigo Abadía-Heredia, Manuel Lopez-Martin +2
This work aims to improve fuel chamber injectors' performance in turbofan engines, thus implying improved performance and reduction of pollutants. This requires the development of…
Improving aircraft performance using machine learning: a review
Soledad Le Clainche, Esteban Ferrer, Sam Gibson +3
This review covers the new developments in machine learning (ML) that are impacting the multi-disciplinary area of aerospace engineering, including fundamental fluid dynamics (expe…
Causality analysis of large-scale structures in the flow around a wall-mounted square cylinder
Álvaro Martínez-Sánchez, Esteban López, Soledad Le Clainche +3
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 t…
High-resolution large-eddy simulations of simplified urban flows
Marco Atzori, Pablo Torres, Alvaro Vidal +3
High-fidelity large-eddy simulations of the flow around two rectangular obstacles are carried out at a Reynolds number of 10,000 based on the free-stream velocity and the obstacle…
Data-driven assessment of arch vortices in simplified urban flows
Álvaro Martínez-Sánchez, Eneko Lazpita, Adrián Corrochano +3
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 st…