arXiv subjects

Alessio Innocenti

Publications and source records attributed to Alessio Innocenti.

6 recordsLinked to original sources

arXiv2026

Analysis and simulations of droplet generation regimes in a coaxial microfluidic device

The generation of microdroplets via segmentation in microfluidic devices is of interest in many applications, from biochemical to pharmaceutical. This technique permits indeed much higher control on the droplet size, uniformity and generation rate than in standard batch generation processes. In this work we have evaluated the suitability of the open-source software Basilisk to accurately predict microdroplet generation by segmentation. We have validated the numerical tool with analytical solutions for the dynamics of droplets in confined flows, namely with Bretherton theory, and by comparison with literature experimental results. We have then performed several campaigns of numerical simulations for a coaxial device, analyzing the different regimes of droplet generation, and evaluating how the physical and flow parameters affect the production mechanisms and {the diameters of the generated droplets}. Finally we have proposed new scaling laws for the prediction of droplet diameters in the dripping and jetting regimes, refining existing ones by taking into account additional physical effects, like the viscosity ratio.

physics.flu-dyn↗

arXiv2020

Direct Numerical Simulation of bubble-induced turbulence at high Reynolds numbers

We report on a investigation of turbulent bubbly flows. Bubbles of a size larger than the dissipative scale, cannot be treated as point-wise inclusions, and generate important hydrodynamic fields in the carrier fluid when in motion. Furthermore, when the volume fraction of bubbles is large enough, the bubble motion may induce a collective agitation due to hydrodynamic interactions which display some turbulent-like features. We tackle this complex phenomenon numerically, performing direct numerical simulations (DNS) with a Volume-of-fluid (VOF) method. In the first part of the work, we perform both 2D and 3D tests in order to determine appropriate numerical and physical parameters. We then carry out a highly-resolved simulation of a 3D bubble column, with a configuration and physical parameters similar to those used in laboratory experiments. This is the largest simulation attempted for such a configuration and is possible only thanks to adaptive grid refinement. Results are compared both with experiments and previous coarse-mesh numerical simulations. In particular, the one-point Probability Density Function (PDF) of the liquid velocity fluctuations is in good quantitative agreement with experiments, notably in the vertical direction, although more extreme events are sampled in the present configuration. The spectra of the liquid kinetic energy show a clear $k^{-3}$ scaling. The mechanisms underlying the energy transfer and notably the possible presence of a cascade are unveiled by a local scale-by-scale analysis in the physical space. The comparison with previous simulations indicate to what extent simulations not fully resolved may yet give correct results, from a statistical point of view.

physics.flu-dyn↗

arXiv2019

Lagrangian stochastic modeling of acceleration in turbulent wall-bounded flows

The Lagrangian approach is natural to study issues of turbulent dispersion and mixing. We propose in this work a general Lagrangian stochastic model including velocity and acceleration as dynamical variables for inhomogeneous turbulent flows. The model takes the form of a diffusion process and the coefficients of the model are determined via Kolmogorov theory and the requirement of consistency with the velocity-based models. It is shown that the present model generalises both the acceleration-based models for homogeneous flows and the generalised Langevin models for the velocity. The resulting closed model is applied to a channel flow at high Reynolds number and compared to experiments as well as direct numerical simulations. A hybrid approach coupling the stochastic model with a Reynolds-Averaged-Navier-Stokes (RANS) is used to obtain a self-consistent model, as commonly used in probability density function methods. Results highlight that most of the acceleration features are well represented, notably the anisotropy and the strong intermittency. These results are valuable, since the model allows to improve the modelling of boundary layers yet remaining relatively simple. It sheds also some light on the statistical mechanisms at play in the near-wall region.

physics.flu-dyn↗

arXiv2018

A Lagrangian probability-density-function model for collisional turbulent fluid-particle flows. II. Application to homogeneous flows

The Lagrangian probability-density-function model, proposed in Part I for dense particle-laden turbulent flows, is validated here against Eulerian-Lagrangian direct numerical simulation (EL) data for different homogeneous flows, namely statistically steady and decaying homogeneous isotropic turbulence, homogeneous-shear flow and cluster-induced turbulence (CIT). We consider the general model developed in Part I adapted to the homogeneous case together with a simplified version in which the decomposition of the phase-averaged (PA) particle-phase fluctuating energy into the spatially correlated and uncorrelated components is not used, and only total exchange of kinetic energy between phases is allowed. The simplified model employs the standard two-way coupling approach. The comparison between EL simulations and the two stochastic models in homogeneous and isotropic turbulence and in homogeneous-shear flow shows that in all cases both models are capable to reproduce rather well the flow behaviour, notably for dilute flows. The analysis of the CIT gives more insights on the physical nature of such systems and about the quality of the models. Results elucidate the fact that simple two-way coupling is sufficient to induce turbulence, even though the granular energy is not considered. Furthermore, first-order moments including velocity of the fluid seen by particles can be fairly well represented with such a simplified stochastic model. However, the decomposition into spatially correlated and uncorrelated components is found to be necessary to account for anisotropic energy exchanges. When these factors are properly accounted for as in the complete model, the agreement with the EL statistics is satisfactory up to second order.

physics.flu-dyn↗

arXiv2018

A Lagrangian probability-density-function model for collisional turbulent fluid-particle flows. I. Model derivation

Inertial particles in turbulent flows are characterised by preferential concentration and segregation and, at sufficient mass loading, dense particle clusters may spontaneously arise due to momentum coupling between the phases. These clusters, in turn, can generate and sustain turbulence in the fluid phase, which we refer to as cluster-induced turbulence. In the present theoretical work, we tackle the problem of developing a framework for the stochastic modelling of moderately dense particle-laden flows, based on a Lagrangian formalism, which naturally includes the Eulerian one. A rigorous formalism and a general model have been put forward focusing, in particular, on the two ingredients that are key in moderately dense flows, namely, two-way coupling in the carrier phase, and the decomposition of the particle-phase velocity into its spatially correlated and uncorrelated components. Specifically, this last contribution allows to identify in the stochastic model the contributions due to the correlated fluctuating energy and to the granular temperature of the particle phase, which determines the time scale for particle-particle collisions. Applications of the Lagrangian probability-density-function model developed in this work to moderately dense particle-laden flows are discussed in a companion paper.

physics.flu-dyn↗

arXiv2016

Lagrangian filtered density function for LES-based stochastic modelling of turbulent dispersed flows

The Eulerian-Lagrangian approach based on Large-Eddy Simulation (LES) is one of the most promising and viable numerical tools to study turbulent dispersed flows when the computational cost of Direct Numerical Simulation (DNS) becomes too expensive. The applicability of this approach is however limited if the effects of the Sub-Grid Scales (SGS) of the flow on particle dynamics are neglected. In this paper, we propose to take these effects into account by means of a Lagrangian stochastic SGS model for the equations of particle motion. The model extends to particle-laden flows the velocity-filtered density function method originally developed for reactive flows. The underlying filtered density function is simulated through a Lagrangian Monte Carlo procedure that solves for a set of Stochastic Differential Equations (SDEs) along individual particle trajectories. The resulting model is tested for the reference case of turbulent channel flow, using a hybrid algorithm in which the fluid velocity field is provided by LES and then used to advance the SDEs in time. The model consistency is assessed in the limit of particles with zero inertia, when "duplicate fields" are available from both the Eulerian LES and the Lagrangian tracking. Tests with inertial particles were performed to examine the capability of the model to capture particle preferential concentration and near-wall segregation. Upon comparison with DNS-based statistics, our results show improved accuracy and considerably reduced errors with respect to the case in which no SGS model is used in the equations of particle motion.

physics.flu-dyn↗