arXiv subjects

Martín Obligado

Publications and source records attributed to Martín Obligado.

5 recordsLinked to original sources

arXiv2026

Evolution of inertial particle clustering in decaying turbulence

Inertial particle dynamics in turbulence are commonly interpreted in terms of the instantaneous particle Stokes number, as supported by studies in statistically stationary homogeneous isotropic turbulence. But in freely decaying turbulence the Kolmogorov time scale evolves continuously, causing the effective Stokes number, St, to vary even though particle properties remain unchanged. Whether preferential concentration remains uniquely determined by this instantaneous St or depends on the flow's previous evolution has remained largely unexplored. We investigate inertial-particle clustering during the decay of homogeneous isotropic turbulence using direct numerical simulations of heavy point particles in the one-way coupling limit. Clustering is quantified through 3D Voronoï tessellations for populations evolving either from statistically stationary clustered states or initially random distributions. We consider both conventionally forced homogeneous isotropic turbulence and velocity fields reconstructed using physics-informed neural networks. We show that preferential concentration cannot be described solely by the instantaneous St. While particle slip velocity follows the classical steady-state dependence on the instantaneous St, clustering statistics retain a measurable history dependence throughout decay. Existing stationary scaling laws remain applicable to cluster-size evolution, but only through history-dependent prefactors. Particle distributions evolving from different initial conditions rapidly converge towards similar large-scale spatial organisation, indicating that the carrier flow determines the geometry of preferential concentration while finer clustering statistics preserve imprints of the previous evolution. These results demonstrate that preferential concentration in non-stationary turbulence is governed jointly by the instantaneous flow state and its initial state.

physics.flu-dyn↗

arXiv2024

Active grid turbulence anomalies through the lens of physics informed neural networks

Active grids operated with random protocols are a standard way to generate large Reynolds number turbulence in wind and water tunnels. But anomalies in the decay and third-order scaling of active-grid turbulence have been reported. We combine Laser Doppler Velocimetry and hot-wire anemometry measurements in a wind tunnel, with machine learning techniques and numerical simulations, to gain further understanding on the reasons behind these anomalies. Numerical simulations that incorporate the statistical anomalies observed in the experimental velocity field near the active grid can reproduce the experimental anomalies observed later in the decay. The results indicate that anomalies in experiments near the active grid introduce correlations in the flow that can persist for long times.

physics.flu-dyn↗

arXiv2023

Coriolis force deflects wind plant wakes left in the Northern Hemisphere

The physical growth of wind energy over several decades, caused a re-investigation mesoscale effects on wind plant dynamics. At a large scale operation, understanding the interactions between atmospheric phenomena and wind plant wakes is crucial to improving models. Within a wind plant, wakes are generated by individual turbines and the summation of individual wakes is the global plant wake. In both cases, the dynamics are sensitive to atmospheric conditions; one of interest to wind and atmospheric scientists is the Coriolis force. Current research noted spatial and temporal influences on the global plant wakes caused by the Coriolis force. Due to the presence of wind veer in the atmospheric boundary layer, field research is notoriously difficult. As a result, investigations have been lead by numerical simulations. This proved helpful for initial queries, established the significance of the Coriolis force as a non trivial parameter of wind plant dynamics. This works presents a novel experimental study of the impact of the Coriolis force on the dynamics of a scaled wind plant. The experiments show that for a single turbine the wake deflection is insignificant. Additionally, the results show that the global plant wake deflects in the anti-clockwise direction in the Northern hemisphere. The outcomes of this work yield unique experimental methods for research in wind energy, and provide a new basis for the fundamental dynamics of a wind plant under influence of the Coriolis force for future wind plant models causing influence on the global expansion of wind energy.

physics.flu-dyn↗

arXiv2022

Generation of Turbulent States using Physics-Informed Neural Networks

When modelling turbulent flows, it is often the case that information on the forcing terms or the boundary conditions is either not available or overly complicated and expensive to implement. Instead, some flow features, such as the mean velocity profile or its statistical moments, may be accessible through experiments or observations. We present a method based on physics-informed neural networks to generate turbulent states subject to a set of given conditions. The physics-informed method ensures the final state approximates a valid flow. We show examples of different statistical conditions that can be used to prepare states, motivated by experimental and atmospheric problems. Lastly, we show two ways of scaling the resolution of the prepared states. One is through the use of multiple and parallel neural networks. The other uses nudging, a synchronization-based data assimilation technique that leverages the power of specialized numerical solvers.

physics.flu-dyn↗

arXiv2022

An experimental study on the settling velocity of inertial particles in different homogeneous isotropic turbulent flows

We propose an experimental study on the gravitational settling velocity of dense, sub-Kolmogorov inertial particles under different background turbulent flows. We report Phase Doppler Particle Analyzer measurements in a low-speed wind tunnel uniformly seeded with micrometer scale water droplets. Turbulence is generated with three different grids (two consisting on different active-grid protocols while the third is a regular static grid), allowing us to cover a very wide range of turbulence conditions in terms of Taylor-scale based Reynolds numbers ($Re_λ\in [30-520]$), Rouse numbers ($Ro \in [0-5]$) and volume fractions ($ϕ_v \in[0.5\times10^{-5} - 2.0\times10^{-5}]$). We find, in agreement with previous works, that enhancement of the settling velocity occurs at low Rouse number, while hindering of the settling occurs at higher Rouse number for decreasing turbulence energy levels. The wide range of flow parameters explored allowed us to observe that enhancement decreases significantly with the Taylor Reynolds number and is significantly affected by the volume fraction $ϕ_v$. We also studied the effect of large-scale forcing on settling velocity modification. The possibility of changing the inflow conditions by using different grids allowed us to test cases with fixed $Re_λ$ and turbulent intensity but different integral length scale. Finally, we assess the existence of secondary flows in the wind tunnel and their role on particle settling. This is achieved by characterising the settling velocity at two different positions, the centreline and close to the wall, with the same streamwise coordinate.

physics.flu-dyn↗