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Eyal Fattal

Publications and source records attributed to Eyal Fattal.

6 recordsLinked to original sources

Second-order stochastic modeling of particle resuspension: macroscopic degeneracy and anomalous pre-detachment transport

Particle resuspension models are commonly evaluated using the macroscopic resuspended fraction, although this integrated observable may conceal the temporal dynamics leading to detachment. Here, a second-order Markovian Lagrangian stochastic model is developed by augmenting the angular-velocity state with a finite-correlated tangential acceleration. The model is examined over turbulent channel flows with ($Re_τ\in [60, 430]$) and compared with an established first-order formulation. The two models produce nearly overlapping resuspended fractions, revealing a macroscopic degeneracy between distinct stochastic descriptions. Multiscale trajectory statistics break this degeneracy. The acceleration-augmented formulation changes the short-time regularity from $S_2(τ) \propto τ$ to $S_2(τ) \propto τ^2$, sustains angular-velocity correlation, and produces stronger directional asymmetry and heavier increment tails. The survivor-conditioned mean square displacement exposes a Reynolds-number-dependent anomalous-transport window, in which the attached-particle ensemble grows more rapidly than the diffusive reference and locally approaches ballistic and super-ballistic scaling before crossing toward diffusion-like transport. This finite-time pathway records how particles approach detachment and is compressed out of the macroscopic resuspended fraction. At $Re_τ\approx 60$, the trajectories enter a distinct low-Reynolds-number statistical state characterized by converging velocity and acceleration decorrelation and near-Gaussian increments. These results establish multiscale trajectory statistics as essential discriminants between stochastic resuspension models and identify finite acceleration correlation as a source of dynamical information beyond macroscopic detachment kinetics.

physics.flu-dyn

On the Markovian assumption in near-wall turbulence: The case of particle resuspension

We investigate the validity of the Markovian assumption in modeling near-wall turbulence by analyzing the detachment of micron-sized particles from the viscous sublayer. By coupling direct numerical simulations with a fractional Ornstein-Uhlenbeck process, we demonstrate that while wall shear stress events follow Poissonian occurrence statistics, their internal dynamics exhibit strong temporal persistence (Hurst exponent $H \approx 0.84$), indicating non-Markovian memory. We reveal that the successful predictions of Markovian resuspension models stems from their free parameter acting as a phenomenological surrogate for flow memory. We further identify a critical regime transition governed by a wall shear stress events decay rate, $λ$. We identify a strong intermittency regime ($λ< 0.2$), where coherent structures exhibit extended temporal correlations that cannot be mimicked by white noise. Conversely, rapid decays ($λ> 0.2$) generate quasi-random fluctuations that justify the Markovian approximation. These findings offer a new perspective on the physical validity of classical stochastic modeling in wall-bounded flows.

physics.flu-dyn

Adaptive degenerate space method for source term estimation using a backward Lagrangian stochastic model

The general problem of characterizing gas source parameters based on concentration measurements is known to be a difficult task. As many inverse problems, one of the main obstacles for accurate estimation is the non-uniqueness of solution, induced by the lack of sufficient information. As the number of detectors is lowered, which is more than a plausible scenario for many practical situations, the number of possible solutions that can characterize the source increases dramatically, leading to severe errors. In this paper, a Lagrangian stochastic based method for identifying these suspected points, which will be referred to as 'degenerate space', is formulated and analysed. Then, a new procedure for quantitative prediction of the effect of deploying a new detector in space is used to design an adaptive scheme for source term estimation. This scheme has been tested for several scenarios, differing by the location of the initial detectors, and is shown to reduce dramatically the degeneracy formed by insufficient information. The combined formulation of degenerate space with the new adaptive scheme is shown to give improved accuracy, and in particular for a relatively small number of detectors.

physics.comp-ph

On local isotropy and scale dependence of pair dispersion in turbulent canopy flows

Canopy flows in the atmospheric surface layer play important economic and ecological roles, governing the dispersion of passive scalars in the environment. The interaction of high-velocity fluid and large-scale surface-mounted obstacles in canopy flows produces drag and causes intense, inhomogeneous, and anisotropic turbulence. In this work, we focus on the turbulent dispersion of passive scalars by studying the ``pair dispersion'' - a statistical measure of relative motion between particles. We analyze the results of a 3D-PTV experiment in a wind tunnel canopy flow, focusing on small scales. We confirm the existence of local isotropy of pair dispersion at scales smaller than a characteristic shear length scale $L_Γ=(ε/Γ^3)^{1/2}$, where $ε$ and $Γ$ are the mean dissipation rate and shear rate, respectively. Furthermore, we show that pair dispersion in this locally isotropic regime is a scale-dependent super-diffusive process, similar to what occurs in homogeneous isotropic turbulent flows. In addition, we measure the pair relative velocity correlation function, showing that its de-correlation occurs in the locally isotropic regime, and discuss the implications of this observation for modeling pair dispersion. Thus, our study extends the fundamental understanding of turbulent pair dispersion to the anisotropic, inhomogeneous, turbulent canopy flow, bringing valuable information for modeling scalar dispersion in the atmospheric surface layer.

physics.flu-dyn

Turbulence -- Obstacle Interactions in the Lagrangian Framework: Applications for Stochastic Modeling in Canopy Flows

Lagrangian stochastic models are widely used to predict and analyze turbulent dispersion in complex environments, such as in various terrestrial and marine canopy flows. However, due to a lack of empirical data, it is still not understood how particular features of highly inhomogeneous canopy flows affect the Lagrangian statistics. In this work, we study Lagrangian short time statistics by analyzing empirical Lagrangian trajectories in sub-volumes of space that are small in comparison with the canopy height. For the analysis we used 3D Lagrangian trajectories measured in a dense canopy flow model in a wind-tunnel, using an extended version of real-time 3D particle tracking velocimetry (3D-PTV). One of our key results is that the random turbulent fluctuations due to the intense dissipation were more dominant than the flow's inhomogeneity in affecting the short-time Lagrangian statistics. This amounts to a so-called quasi-homogeneous regime of Lagrangian statistics at small scales. Using the Lagrangian dataset we calculate the Lagrangian autocorrelation function and the second-order Lagrangian structure-function, and extract associated parameters, namely a Lagrangian velocity decorrelation timescale, $T_i$, and the Kolmogorov constant, $C_0$. We demonstrate that in the quasi-homogeneous regime, both these functions are well represented using a second-order Lagrangian stochastic model that was designed for homogeneous flows. Furthermore, we show that the spatial variations of the Lagrangian separation of scales, $T_i/τ_η$, and the Kolmogorov constant, $C_0$, cannot be explained by the variation of the Reynolds number, $Re_λ$, in space, and that $T_i/τ_η$ was small as compared with homogeneous turbulence predictions at similar $Re_λ$. We thus hypothesize that this occurred due to the so-called "wake production", and show empirical results supporting our hypothesis.

physics.flu-dyn

Extended 3D-PTV for direct measurements of Lagrangian statistics of canopy turbulence in a wind tunnel

Direct estimation of Lagrangian turbulence statistics is essential for the proper modeling of dispersion and transport in highly obstructed canopy flows. However, Lagrangian flow measurements demand very high rates of data acquisition, resulting in bottlenecks that prevented the estimation of Lagrangian statistics in canopy flows hitherto. We report on a new extension to the 3D Particle Tracking Velocimetry (3D-PTV) method, featuring real-time particle segmentation that outputs centroids and sizes of tracer particles and performed on dedicated hardware during high-speed digital video acquisition from multiple cameras. The proposed extension results in four orders of magnitude reduction in data transfer rate that enables to perform substantially longer experimental runs, facilitating measurements of convergent statistics. The extended method is demonstrated through an experimental wind tunnel investigation of the Lagrangian statistics in a heterogeneous canopy flow. We observe that acceleration statistics are affected by the mean shear at the top of the canopy layer and that Lagrangian particle dispersion at small scales is dominated by turbulence in the wake of the roughness elements. This approach enables to overcome major shortcomings from Eulerian-based measurements which rely on assumptions such as the Taylor's frozen turbulence hypothesis, which is known to fail in highly turbulent flows.

physics.flu-dyn