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From the 2 of 6 linked papers with an AI index.

activity
20242026
collaborators

6 papers

physics.flu-dyn2026

Divide and conquer complex flows. Part I: cluster and manifold-based local analysis

Qihong L. Li-Hu, Guy Y. Cornejo Maceda, Andrea Ianiro +1

The paper introduces a data‑driven framework that uses manifold learning and unsupervised clustering to automatically partition complex fluid‑flow domains into subregions with simi…

physics.flu-dyn2026

Feature-based manifold model of actuated wakes

Alicia Rodríguez-Asensio, Guy Y. Cornejo Maceda, Bernd R. Noack +2

The paper presents a feature‑based reduced‑order model that predicts the transient dynamics of bluff‑body wakes under arbitrary time‑varying actuation, using a manifold of dynamic…

physics.flu-dyn2026

On the turbulent wake of the actuated fluidic pinball: dynamics, bifurcations and control authority

Alicia Rodríguez-Asensio, Luigi Marra, Ignacio Andreu-Angulo +6

We present the first comprehensive experimental and numerical study featuring the turbulent wake of the fluidic pinball for a large actuation range. The fluidic pinball is a cluste…

cs.NE2026

Fast and robust parametric and functional learning with Hybrid Genetic Optimisation (HyGO)

Isaac Robledo, Yiqing Li, Guy Y. Cornejo Maceda +1

The Hybrid Genetic Optimisation framework (HYGO) is introduced to meet the pressing need for efficient and unified optimisation frameworks that support both parametric and function…

cs.LG2025

Sensor optimization for urban wind estimation with cluster-based probabilistic framework

Yutong Liang, Chang Hou, Guy Y. Cornejo Maceda +8

We propose a physics-informed machine-learned framework for sensor-based flow estimation for drone trajectories in complex urban terrain. The input is a rich set of flow simulation…

physics.flu-dyn2024

Machine-learned flow estimation with sparse data -- exemplified for the rooftop of a UAV vertiport

Chang Hou, Luigi Marra, Guy Y. Cornejo Maceda +9

We propose a physics-informed data-driven framework for urban wind estimation. This framework validates and incorporates the Reynolds number independence for flows under various wo…