2 citations · 2 across the 4 of their papers we have counts for
4 papers
Reduced-order modeling of large-scale turbulence using Koopman -variational autoencoders
Rakesh Halder, Benet Eiximeno, Oriol Lehmkuhl
Reduced-order models (ROMs) are very popular for surrogate modeling of full-order computational fluid dynamics (CFD) simulations, allowing for real-time approximation of complex fl…
On Deep-Learning-Based Closures for Algebraic Surrogate Models of Turbulent Flows
Benet Eiximeno, Marcial Sanchís-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…
Turbulent Boundary Layer in a 3-Element High-LiftWing: Coherent Structures Identification
Ricard Montalà, Benet Eiximeno, Arnau Miró +2
A wall-resolved large-eddy simulation (LES) of the fluid flow around a 30P30N airfoil is conducted at a Reynolds number of Rec=750,000 and an angle of attack (AoA) of 9 degrees. Th…
pyLOM: A HPC open source reduced order model suite for fluid dynamics applications
Benet Eiximeno, Arnau Miró, Beka Begiashvili +3
This paper describes the numerical implementation in a high-performance computing environment of an open-source library for model order reduction in fluid dynamics. This library, c…