194 citations · 362 across the 21 of their papers we have counts for
4 papers · 1 filter
AeroJEPA: Learning Semantic Latent Representations for Scalable 3D Aerodynamic Field Modeling
Francisco Giral, Abhijeet Vishwasrao, Andrea Arroyo Ramo +8
High-fidelity CFD is essential for aerodynamic design, but repeated simulations are computationally expensive, motivating surrogate models for rapid evaluation across geometries an…
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…
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…