arXiv subjects

Paolo Olivucci

Publications and source records attributed to Paolo Olivucci.

4 recordsLinked to original sources

arXiv2026

Exemplar-based objective classification of gust-induced loads across multiple flight conditions

Is it possible to find an objective classification criterion that organizes the complexity of gust-induced loads across many flight conditions? And one that remains as interpretable as a labelling based on coarse parameters, such as the flight attitude? Our approach encodes a large number of experimental observations through a machine-learned representation and applies a summarization procedure to select a minimal subset of highly significant exemplars. The exemplars provide a similarity-based objective classification criterion of all the observations, they can be more conveniently inspected by experts and can become subject of more refined experiments. We demonstrate the approach on a database of 3480 pressure-load measurements induced by random gusts on a flying-wing model across six flight attitudes. We find nine fundamental response types that recur across multiple attitudes; analysis of a type's transient response enables physical intuition into the underlying fluid mechanics.

cs.LG↗

arXiv2026

Control-oriented cluster-based reduced-order modelling

This work addresses the challenge of learning reduced-order models (ROMs) capable of generalizing to unobserved dynamical regimes across unseen control parameters. We introduce the Control-oriented Cluster-based Network Model (CNMc), a framework for synthesizing reduced-order dynamics at held-out operating conditions without requiring simulation data at those conditions. While the traditional Cluster Network Model (CNM) is limited to observed regimes, CNMc enables generalization by fitting supervised regression models to the transition probabilities and transition times of the CNM as functions of the control parameter. A key enabler is a Procrustes transformation that maps each operating condition's state space to a common coordinate system in which trajectories across all conditions are standardised and shape-aligned, permitting a shared cluster partition to be learned. We evaluate CNMc on two fluid dynamics benchmarks, the Lorenz-63 system and a controlled turbulent boundary layer, demonstrating that the predicted statistics at the withheld condition closely match those of a CNM trained directly on test data. CNMc also outperforms the competing interpolation-based CNM approaches under identical conditions. These results represent a step toward parameter-aware ROMs suitable for real-time flow control and the acceleration of parametric design studies.

physics.flu-dyn↗

arXiv2026

The search for the gust-wing interaction "textbook"

We address whether complex physical relations can be investigated through the synergy of automated high-volume experiments and the reduction of large datasets to a concise, representative subset of canonical examples -- a "textbook". To this end, we consider the unsteady aerodynamics of wing-gust interactions, which is characterized by its rich, high-dimensional physics. We take advantage of a purpose-built gust generator to systematically produce over 1,000 distinct random gust events and to measure the unsteady loads induced on a delta wing. We then employ a data summarization procedure to identify representative subsets of increasing size from the large-scale database, which then serve as training data for a machine-learning model of the aerodynamic loads from sparse pressure measurements. An appropriately selected "textbook" of a few events can achieve predictive accuracy comparable to random training sets up to two orders of magnitude larger, capturing the intrinsic diversity of the full-scale data and enhancing modeling efficiency and interpretability. Our methodology evidences the potential of distilling the essential information contained in large amounts of experimental observations.

physics.flu-dyn↗

arXiv2021

Reduction of turbulent skin-friction drag by passively rotating discs

A turbulent channel flow modified by the motion of discs that are free to rotate under the action of wall turbulence is studied numerically. The Navier-Stokes equations are coupled nonlinearly with the dynamical equation of the disc motion, which synthesizes the fluid-flow boundary conditions and is driven by the torque exerted by the wall-shear stress. We consider discs that are fully exposed to the fluid and discs for which only half of the surface interfaces the fluid. The disc motion is thwarted by the fluid torque in the housing cavity and by the torque of the ball bearing that supports the disc. For the full discs, no drag reduction occurs because of the small angular velocities. The most energetic disc response occurs for disc diameters that are comparable with the spanwise spacing of the low-speed streaks. A perturbation analysis for small disc-tip velocities reveals that the two-way nonlinear coupling has an intense attenuating effect on the disc response. The reduced-order results show excellent agreement with the nonlinear results for large diameters. The half discs rotate with a finite angular velocity, leading to large reduction of the turbulence activity and of the skin-friction drag over the spinning portion of the discs, while the maximum drag reduction over the entire walls is 5.6%. The dependence of the drag reduction on the wall-slip velocity and the spatial distribution of the wall-shear stress qualitatively match results based on the only available experimental data.

physics.flu-dyn↗