3 papers
physics.flu-dyn2026
Optimization-Embedded Active Multi-Fidelity Surrogate Learning for Multi-Condition Airfoil Shape Optimization
Isaac Robledo, Alberto Vilariño, Arnau Miró +3
Active multi-fidelity surrogate modeling is developed for multi-condition airfoil shape optimization to reduce high-fidelity CFD cost while retaining RANS-consistent aerodynamic me…
physics.flu-dyn2025
Deep-reinforcement-learning-based separation control in a two-dimensional airfoil
Xavier Garcia, Arnau Miró, Pol Suárez +5
The aim of this study is to discover new active-flow-control (AFC) techniques for separation mitigation in a two-dimensional NACA 0012 airfoil at a Reynolds number of 3000. To find…
physics.flu-dyn2024
On Deep-Learning-Based Closures for Algebraic Surrogate Models of Turbulent Flows
Benet Eiximeno, Marcial SanchÃs-Agudo, Arnau Miró +3
A deep-learning-based closure model to address energy loss in low-dimensional surrogate models based on proper-orthogonal-decomposition (POD) modes is introduced. Using a transform…