From the 1 of 9 linked papers with an AI index.
9 papers
Gradient-free learning of a closed-loop wall controller for turbulent drag reduction
Giorgio Maria Cavallazzi, Miguel Pérez Cuadrado, Alfredo Pinelli
The paper uses an evolution‑strategy optimisation to train a recurrent closed‑loop wall controller that reduces skin‑friction drag in a turbulent channel flow by about 26%, outperf…
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, Miguel Pérez-Cuadrado +1
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, Miguel Pérez Cuadrado +1
Deep reinforcement learning (DRL) applied to thermal convection control consistently produces degenerate actuation: wall-temperature policies whose outputs are saturated, pseudo-ra…
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…