arXiv subjects

Filippo Coletti

Publications and source records attributed to Filippo Coletti.

12 recordsLinked to original sources

arXiv2026

Free-surface curvature and its relation to subsurface turbulence

The free surface atop a turbulent liquid flow is deformed by the underlying fluid motion, with the turbulence imprinting its geometry on the surface. Here we develop a theoretical framework to model such deformations based on the Euler equation with gravity and surface tension, and evaluate it against simultaneous high-resolution measurements of surface topography and subsurface velocity fields in a zero-mean-flow turbulent water tank. We consider a range of Reynolds and Froude numbers, focusing on regimes in which the surface is unbroken. Over a range of spatial and temporal scales, we find close quantitative agreement between the measured surface curvature and that which is modeled based on the velocity field a few millimeters beneath the surface, both from the statistical and the local/instantaneous standpoints. Importantly, we verify a strong correlation between the magnitudes of the surface curvature and the divergence of the near-surface horizontal velocity, which in turn is directly related to gas and heat transfer at the air-water interface. We discuss how the sub-surface motion at increasing depths decorrelates from the surface shape, and does so more rapidly at smaller spatial scales. These findings demonstrate that measurements of surface deformations may be used to sense the state of the flow beneath the surface and provide a foundation to make optically-based inferences of processes controlled by near-surface turbulence.

physics.flu-dyn↗

arXiv2026

First Direct Observations of Internal Flow Structures in a Powder Snow Avalanche: Turbulence, Instability and Particle Distribution

Powder snow avalanches are highly dynamic, multiphase gravity-driven flows typically composed of a dense basal layer overlain by airborne layers in which snow particles are suspended within a turbulent air phase. Despite extensive work on related systems such as pyroclastic density currents and turbidity currents, all gravity current communities face a fundamental limitation: the lack of direct, high-resolution particle-scale field data. Here, we present the first direct optical observations of individual particle motion inside the airborne layers of a natural powder snow avalanche using high-speed imaging. The flow is segmented into three regions: an initial short living surge, a highly dynamic suspension phase, and a final wake. Across these phases, we quantify flow velocity and turbulence characteristics, including integral length scales, and use image intensity as a proxy for particle concentration. We identify fluctuations exceeding the turbulent integral scale and use linear stability analysis to link them to Kelvin-Helmholtz-type shear instabilities. Observed changes in clustering behavior, stratification, and the decoupling of particles from the flow mark the transition from an unstable suspension layer characterized by a high level of turbulent activity to a stable one dominated by passive snow settling. Together, these findings provide the first empirical constraints on turbulence and instability dynamics in airborne avalanche layers, with direct implications for the refinement of numerical avalanche models and closure schemes in multiphase gravity current simulations.

physics.geo-ph↗

arXiv2024

Small-scale dynamics and structure of free-surface turbulence

The dynamics of small-scale structures in free-surface turbulence is crucial to large-scale phenomena in natural and industrial environments. Here we conduct experiments on the quasi-flat free surface of a zero-mean-flow turbulent water tank over the Reynolds number range $Re_{\lambda} = 207\textrm{--}312$. By seeding microscopic floating particles at high concentrations, the fine scales of the flow and the velocity gradient tensor are resolved. A kinematic relation is derived expressing the contribution of surface divergence and vorticity to the dissipation rate. The probability density functions of divergence, vorticity and strain-rate collapse once normalized by the Kolmogorov scales. Their magnitude displays strong intermittency and follows chi-square distributions with power-law tails at small values. The topology of high-intensity events and two-point statistics indicate that the surface divergence is characterized by dissipative spatial and temporal scales, while the high-vorticity and high-strain-rate regions are larger, long-lived, concurrent, and elongated. The second-order velocity structure functions obey the classic Kolmogorov scaling in the inertial range when the dissipation rate on the surface is considered, with a different numerical constant than in 3D turbulence. The cross-correlation among divergence, vorticity and strain-rate indicates that the surface-attached vortices are strengthened during downwellings and diffuse when those dissipate. Sources (sinks) in the surface velocity fields are associated with strong (weak) surface-parallel stretching and compression along perpendicular directions. The floating particles cluster over spatial and temporal scales larger than those of the sinks. These results demonstrate that, compared to 3D turbulence, in free-surface turbulence the energetic scales leave a stronger imprint on the small-scale quantities.

physics.flu-dyn↗

arXiv2024

Restricted Euler dynamics in free-surface turbulence

The small-scale velocity gradient is connected to fundamental properties of turbulence at the large scales. By neglecting the viscous and nonlocal pressure Hessian terms, we derive a restricted Euler model for the turbulent flow along an undeformed free surface and discuss the associated stable/unstable manifolds. The model is compared with the data collected by high-resolution imaging on the free surface of a turbulent water tank with negligible surface waves. The joint probability density function (PDF) of the velocity gradient invariants exhibits a distinct pattern from the one in the bulk. The restricted Euler model captures the enhanced probability along the unstable branch of the manifold and the asymmetry of the joint PDF. Significant deviations between the experiments and the prediction are evident, however, in particular concerning the compressibility of the surface flow. These results highlight the enhanced intermittency of the velocity gradient and the influence of the free surface on the energy cascade.

physics.flu-dyn↗

arXiv2024

Structure and energy transfer in homogeneous turbulence below a free surface

We investigate the turbulence below a quasi-flat free surface, focusing on the energy transport in space and across scales. We leverage a large zero-mean-flow tank where homogeneous turbulence is generated by randomly actuated jets. A wide range of Reynolds number is spanned, reaching sufficient scale separation for the emergence of an inertial sub-range. Unlike previous studies, the forcing extends through the source layer, though the surface deformation remains millimetric. Particle image velocimetry along a surface-normal plane resolves from the dissipative to the integral scales. The contributions to turbulent kinetic energy from both vertical and horizontal components of velocity approach the prediction based on rapid distortion theory as the Reynolds number is increased, indicating that discrepancies among previous studies are likely due to differences in the forcing. At odds with the theory, however, the integral scale of the horizontal fluctuations grows as the surface is approached. This is rooted in the profound influence exerted by the surface on the inter-scale energy transfer: along horizontal separations, the direct cascade of energy in horizontal fluctuations is hindered, while an inverse cascade of that in vertical fluctuations is established. This is connected to the structure of upwellings and downwellings. The former, characterized by somewhat larger spatial extent and stronger intensity, are associated to extensional surface-parallel motions. They thus transfer energy to the larger horizontal scales, prevailing over downwellings which favour the compression (and concurrent vertical stretching) of the eddies. Both types of structures extend to depths between the integral and Taylor microscales.

physics.flu-dyn↗

arXiv2024

Robotics meets Fluid Dynamics: A Characterization of the Induced Airflow below a Quadrotor as a Turbulent Jet

The widespread adoption of quadrotors for diverse applications, from agriculture to public safety, necessitates an understanding of the aerodynamic disturbances they create. This paper introduces a computationally lightweight model for estimating the time-averaged magnitude of the induced flow below quadrotors in hover. Unlike related approaches that rely on expensive computational fluid dynamics (CFD) simulations or drone specific time-consuming empirical measurements, our method leverages classical theory from turbulent flows. By analyzing over 16 hours of flight data from drones of varying sizes within a large motion capture system, we show for the first time that the combined flow from all drone propellers is well-approximated by a turbulent jet after 2.5 drone-diameters below the vehicle. Using a novel normalization and scaling, we experimentally identify model parameters that describe a unified mean velocity field below differently sized quadrotors. The model, which requires only the drone's mass, propeller size, and drone size for calculations, accurately describes the far-field airflow over a long-range in a very large volume which is impractical to simulate using CFD. Our model offers a practical tool for ensuring safer operations near humans, optimizing sensor placements and drone control in multi-agent scenarios. We demonstrate the latter by designing a controller that compensates for the downwash of another drone, leading to a four times lower altitude deviation when passing below.

cs.RO↗

arXiv2024

Data-driven modeling of the regular and chaotic dynamics of an inverted flag from experiments

We use video footage of a water tunnel experiment to construct a two-dimensional reduced-order model of the flapping dynamics of an inverted flag in uniform flow. The model is obtained as the reduced dynamics on an attracting spectral submanifold (SSM) that emanates from the two slowest modes of the unstable fixed point of the flag. Beyond an unstable fixed point and a limit cycle expected from observations, our SSM-reduced model also confirms the existence of two unstable fixed points for the flag, which were found by previous studies. Importantly, the model correctly reconstructs the dynamics from a small number of general trajectories and no further information on the system. In the chaotic flapping regime, we construct a 4D SSM-reduced model that captures the system's chaotic attractor.

physics.flu-dyn↗

arXiv2021

Dynamics of small heavy particles in homogeneous turbulence: a Lagrangian experimental study

We investigate the behavior of microscopic heavy particles settling in homogeneous air turbulence. The regimes are relevant to the airborne transport of dust and droplets: the Taylor-microscale Reynolds number is Re = 289 - 462, the Kolmogorov-scale Stokes number is St = 1.2 - 13, and the Kolmogorov acceleration is comparable to the gravitational acceleration (i.e., the Froude number Fr = O(1)). We use high-speed laser imaging to track the particles and simultaneously characterize the air velocity field, resolving all relevant spatio-temporal scales. The role of the flow sampled by the particles is spotlighted. In the present range of parameters, the particle settling velocity is enhanced proportionally to the velocity scale of the turbulence. Both gravity and inertia reduce the velocity fluctuations of the particles compared to the fluid; while they have competing effect on the particle acceleration, through the crossing trajectories and inertial filtering mechanisms, respectively. The preferential sampling of high-strain/low-vorticity regions is measurable, but its impact on the global statistics is moderate. The inertial particles have large relative velocity at small separations, which increases their pair dispersion; however, gravity offsets this effect by causing them to experience fluid velocities that decorrelate faster in time compared to tracers. Based on the observations, we derive an analytical model to predict the particle velocity and acceleration variances for arbitrary St, Fr, and Re. This agrees well with the present observations and previous simulations and captures the respective effects of inertia and gravity, both of which play crucial roles in the transport.

physics.flu-dyn↗

arXiv2020

Settling and Clustering of Snow Particles in Atmospheric Turbulence

The effect of turbulence on snow precipitation is not incorporated into present weather forecasting models. Here we show evidence that turbulence is in fact a key influence on both fall speed and spatial distribution of settling snow. We consider three snowfall events under vastly different levels of atmospheric turbulence. We characterize the size and morphology of the snow particles, and we simultaneously image their velocity, acceleration, and relative concentration over vertical planes about 30 m2 in area. We find that turbulence-driven settling enhancement explains otherwise contradictory trends between the particle size and velocity. The estimates of the Stokes number and the correlation between vertical velocity and local concentration indicate that the enhanced settling is rooted in the preferential sweeping mechanism. When the snow vertical velocity is large compared to the characteristic turbulence velocity, the crossing trajectories effect results in strong accelerations. When the conditions of preferential sweeping are met, the concentration field is highly non-uniform and clustering appears over a wide range of scales. These clusters, identified for the first time in a naturally occurring flow, display the signature features seen in canonical settings: power-law size distribution, fractal-like shape, vertical elongation, and large fall speed that increases with the cluster size. These findings demonstrate that the fundamental phenomenology of particle-laden turbulence can be leveraged towards a better predictive understanding of snow precipitation and ground snow accumulation. They also demonstrate how environmental flows can be used to investigate dispersed multiphase flows at Reynolds numbers not accessible in laboratory experiments or numerical simulations.

physics.flu-dyn↗

arXiv2019

Inertial particle velocity and distribution in vertical turbulent channel flow: a numerical and experimental comparison

This study is concerned with the statistics of vertical turbulent channel flow laden with inertial particles for two different volume concentrations ($\Phi_{V} = 3 \times 10^{-6}$ and $\Phi_{V} = 5 \times 10^{-5}$) at a Stokes number of $St^{+} = 58.6$ based on viscous units. Two independent direct numerical simulation models utilizing the point-particle approach are compared to recent experimental measurements, where all relevant nondimensional parameters are directly matched. While both numerical models are built on the same general approach, details of the implementations are different, particularly regarding how two-way coupling is represented. At low volume loading, both numerical models are in general agreement with the experimental measurements, with certain exceptions near the walls for the wall-normal particle velocity fluctuations. At high loading, these discrepancies are increased, and it is found that particle clustering is overpredicted in the simulations as compared to the experimental observations. Potential reasons for the discrepancies are discussed. As this study is among the first to perform one-to-one comparisons of particle-laden flow statistics between numerical models and experiments, it suggests that continued efforts are required to reconcile differences between the observed behavior and numerical predictions.

physics.flu-dyn↗

arXiv2019

Velocity and spatial distribution of inertial particles in a turbulent channel flow

We present experimental observations of the velocity and spatial distribution of inertial particles dispersed in the turbulent downward flow through a vertical channel at $Re_{\tau} = 235$ and $335$. The working fluid is air laden with size-selected glass micro-spheres, with Stokes numbers $St = O(10)$ and $O(100)$ based on the Kolmogorov and viscous time scales, respectively. Cases at solid volume fractions ${\phi}_v = 3{\times}10^{-6}$ and $5{\times}10^{-5}$ are considered. In the more dilute regime, the particle concentration profile shows near-wall and centerline maxima compatible with a turbophoretic drift down the gradient of turbulence intensity; the particles travel at similar speed as the unladen flow except in the near-wall region; and their velocity fluctuations generally follow the unladen flow level over the channel core, exceeding it in the near-wall region. The denser regime presents substantial differences in all measured statistics: the near-wall concentration peak is much more pronounced, while the centerline maximum is absent; the mean particle velocity decreases over the logarithmic and buffer layers; and particle velocity fluctuations and deposition velocities are enhanced. Analysis of the spatial distributions of particle positions and velocities reveals dense, elongated clusters forming in the core, which tend to be preferentially aligned with the streamwise direction, and travel faster than the less concentrated particles. In the near-wall region, the particles arrange in highly elongated streaks associated to negative streamwise velocity fluctuations, several channel heights in length and spaced by $O(100)$ wall units, supporting the view that these are coupled to fluid low-speed streaks typical of wall turbulence. The particle velocity fields contain a significant component of random uncorrelated motion, more prominent for higher St and in the near-wall region.

physics.flu-dyn↗

arXiv2018

Experimental study of inertial particles clustering and settling in homogeneous turbulence

We study experimentally the spatial distribution, settling, and interaction of sub-Kolmogorov inertial particles with homogeneous turbulence. Utilizing a zero-mean-flow air turbulence chamber, we drop size-selected solid particles and study their dynamics with particle imaging and tracking velocimetry at multiple resolutions. The carrier flow is simultaneously measured by particle image velocimetry of suspended tracers, allowing the characterization of the interplay between both the dispersed and continuous phases. The turbulence Reynolds number based on the Taylor microscale ranges from $Re_{\lambda}\approx 200$ - $500$, while the particle Stokes number based on the Kolmogorov scale varies between $St_{\eta} = O(1)$ and $O(10)$. Clustering is confirmed to be most intense for $St_{\eta} \approx 1$, but it extends over larger scales for heavier particles. Individual clusters form a hierarchy of self-similar, fractal-like objects, preferentially aligned with gravity and sizes that can reach the integral scale of the turbulence. Remarkably, the settling velocity of $St_{\eta} \approx 1$ particles can be several times larger than the still-air terminal velocity, and the clusters can fall even faster. This is caused by downward fluid fluctuations preferentially sweeping the particles, and we propose that this mechanism is influenced by both large and small scales of the turbulence. The particle-fluid slip velocities show large variance, and both the instantaneous particle Reynolds number and drag coefficient can greatly differ from their nominal values. Finally, for sufficient loadings, the particles generally augment the small-scale fluid velocity fluctuations, which however may account for a limited fraction of the turbulent kinetic energy.

physics.flu-dyn↗