7 citations · 7 across the 9 of their papers we have counts for
9 papers
Gradient-free learning of a closed-loop wall controller for turbulent drag reduction
Giorgio Maria Cavallazzi, Miguel Pérez Cuadrado, Alfredo Pinelli
Closed-loop wall controllers learnt by multi-agent reinforcement learning are usually trained on periodic boxes far smaller than the flows they are meant to drive, and a large part…
Manifold-adapted radial basis functions for reduced-order modelling of chaotic flows
Miguel Pérez Cuadrado, Giorgio Maria Cavallazzi, Alfredo Pinelli
Chaotic systems often evolve on a low-dimensional attractor whose geometry varies from one region to another. We propose a non-intrusive reduced-order model that reads this local g…
Offline accuracy is not enough: closed-loop instability and stabilisation of a wall-sensor neural estimator in opposition control
Giorgio Maria Cavallazzi, Miguel Pérez-Cuadrado, Alfredo Pinelli
Opposition control reduces skin-friction drag by opposing the wall-normal velocity on a near-wall detection plane, but the detection-plane velocity it requires is not available fro…
Reward hacking in physical reinforcement learning revealed by turbulent drag reduction
Giorgio Maria Cavallazzi, Miguel Pérez-Cuadrado, Alfredo Pinelli
Reinforcement-learning controllers optimise specified rewards, but in physical systems those rewards often capture only part of the true control objective. Three mechanisms through…
Deep reinforcement learning with spatial and temporal awareness for active boundary control of buoyancy-driven convection
Giorgio Maria Cavallazzi, Miguel Pérez Cuadrado, Alfredo Pinelli
Deep reinforcement learning (DRL) applied to thermal convection control consistently produces degenerate actuation: wall-temperature policies whose outputs are saturated, pseudo-ra…
Restoring Convergence Order in Explicit Runge-Kutta Integration of Hyperbolic PDE with Time-Dependent Boundary Conditions
Giorgio Maria Cavallazzi, Miguel Pérez Cuadrado, Alfredo Pinelli
Explicit Runge-Kutta (RK) integration of hyperbolic initial-boundary value problems with time-dependent Dirichlet data often displays order reduction: the observed convergence orde…
Manifold-Adapted Sparse RBF-SINDy: Unbiased Library Construction and Unsupervised Discovery of Dynamical States in Turbulent Wall Flows
Miguel Perez-Cuadrado, Giorgio Maria Cavallazzi, Alfredo Pinelli
The turbulent attractor of wall bounded flows is not a structureless strange set but contains a skeleton of dynamically distinct states connected by rare directed transitions whose…
Walsh-Hadamard Neural Operators for Solving PDEs with Discontinuous Coefficients
Giorgio M. Cavallazzi, Miguel Pérez Cuadrado, Alfredo Pinelli
Neural operators have emerged as powerful tools for learning solution operators of partial differential equations (PDEs). However, standard spectral methods based on Fourier transf…
Deep reinforcement learning for the management of the wall regeneration cycle in wall-bounded turbulent flows
Giorgio Maria Cavallazzi, Luca Guastoni, Ricardo Vinuesa +1
The wall cycle in wall-bounded turbulent flows is a complex turbulence regeneration mechanism that remains not fully understood. This study explores the potential of deep reinforce…