arXiv subjects

Luca Biferale

Publications and source records attributed to Luca Biferale.

At least 73 records · Page 4Linked to original sources

arXiv2021

Effects of forcing mechanisms on the multiscale properties of magnetohydrodynamics

We performed numerical simulations to study the response of magnetohydrodynamics (MHD) to large-scale stochastic forcing mechanisms parametrized by one parameter, $0 \le a \le1$, going from direct injection on the velocity field ($a = 1$) to stirring acts on the magnetic field only ($a = 0$). We study the multi-scale properties of the energy transfer, by splitting the total flux in channels mediated by (i) the kinetic non-linear advection, (ii) the Lorentz force, (iii) the magnetic advection and (iv) magnetic stretching term. We further decompose the fluxes in two sub-channels given by heterochiral and homochiral components in order to distinguish forward, inverse and flux-loop cascades. We show that there exists a quasi-singular role of the magnetic forcing mechanism for $a \sim 1$: a small injection on the magnetic field $a < 1$ can strongly deplete the mean flux of kinetic energy transfer throughout the kinetic non-linear advection channel. We also show that this negligible mean flux is the result of a flux-loop balance between heterochiral (direct) and homochiral (inverse) transfers. Conversely, both homochiral and heterochiral channels transfer energy forward for the other three channels. Cross exchange between velocity and the magnetic field is reversed around $a = 0.4$ and except when $a \sim 1$ we always observe that heterochiral mixed velocity-magnetic energy triads tend to move energy from magnetic to velocity fields. Our study is an attempt to further characterize the multi-scale nature of MHD dynamics, by disentangling different properties of the total energy transfer mechanisms, which can be useful for improving sub-grid-modelling.

physics.plasm-ph↗

arXiv2021

Validation and application of the lattice Boltzmann algorithm for a turbulent immiscible Rayleigh-Taylor system

We develop a multicomponent lattice Boltzmann (LB) model for the 2D Rayleigh--Taylor turbulence with a Shan-Chen pseudopotential implemented on GPUs. In the immiscible case this method is able to accurately overcome the inherent numerical complexity caused by the complicated structure of the interface that appears in the fully developed turbulent regime. Accuracy of the LB model is tested both for early and late stages of instability. For the developed turbulent motion we analyze the balance between different terms describing variations of the kinetic and potential energies. Then, we analyze the role of interface in the energy balance, and also the effects of the vorticity induced by the interface in the energy dissipation. Statistical properties are compared for miscible and immiscible flows. Our results can also be considered as a first validation step to extend the application of LB model to 3D immiscible Rayleigh-Taylor turbulence.

physics.flu-dyn↗

arXiv2021

A Mesoscale Perspective on the Tolman Length

We demonstrate that the multi-phase Shan-Chen lattice Boltzmann method (LBM) yields a curvature dependent surface tension $σ$ as computed from three-dimensional hydrostatic droplets/bubbles simulations. Such curvature dependence is routinely characterized, at first order, by the so-called {\it Tolman length} $δ$. LBM allows to precisely compute $σ$ at the surface of tension $R_s$ and determine the Tolman length from the coefficient of the first order correction. The corresponding values of $δ$ display universality for different equations of state, following a power-law scaling near the critical temperature. The Tolman length has been studied so far mainly via computationally demanding molecular dynamics (MD) simulations or by means of density functional theory (DFT) approaches playing a pivotal role in extending Classical Nucleation Theory. The present results open a new hydrodynamic-compliant mesoscale arena, in which the fundamental role of the Tolman length, alongside real-world applications to cavitation phenomena, can be effectively tackled. All the results can be independently reproduced through the "idea.deploy" framework.

cond-mat.stat-mech↗

arXiv2021

$λ$-Navier-Stokes turbulence

We investigate numerically the model proposed in Sahoo et al [Phys. Rev. Lett. 118, 164501, (2017)] where a parameter $λ$ is introduced in the Navier-Stokes equations such that the weight of homochiral to heterochiral interactions is varied while preserving all original scaling symmetries and inviscid invariants. Decreasing the value of $λ$ leads to a change in the direction of the energy cascade at a critical value $λ_c \sim 0.3$. In this work, we perform numerical simulations at varying $λ$ in the forward energy cascade range and at changing the Reynolds number $\mathrm{Re}$. We show that for a fixed injection rate, as $λ\to λ_c$, the kinetic energy diverges with a scaling law $\mathcal{E} \propto (λ-λ_c)^{-2/3}$. The energy spectrum is shown to display a larger bottleneck as $λ$ is decreased. The forward heterochiral flux and the inverse homochiral flux both increase in amplitude as $λ_c$ is approached while keeping their difference fixed and equal to the injection rate. As a result, very close to $λ_c$ a stationary state is reached where the two opposite fluxes are of much higher amplitude than the mean flux and large fluctuations are observed. Furthermore, we show that intermittency as $λ_c$ is approached is reduced. The possibility of obtaining a statistical description of regular Navier-Stokes turbulence as an expansion around this newly found critical point is discussed.

physics.flu-dyn↗

arXiv2021

Acceleration of tracer and light particles in compressible homogeneous isotropic turbulence

The accelerations of tracer and light particles in compressible homogeneous isotropic turbulence (CHIT) is investigated by using data from direct numerical simulations (DNS) up to turbulent Mach number $M_t =1$. For tracer particles, the flatness factor of acceleration components, $F_a$, increases gradually for $M_t \in [0.3, 1]$. On the contrary, $F_a$ for light particles develops a maximum around $M_t \sim 0.6$. The PDF of longitudinal acceleration of tracers is increasingly skewed towards the negative value as $M_t$ increases. By contrast, for light particles, the skewness factor of longitudinal acceleration, $S_a$, firstly becomes more negative with the increase of $M_t$, and then goes back to $0$ when $M_t$ is larger than $0.6$. Similarly, differences among tracers and light particles appear also in the zero-crossing time of acceleration correlation. It is argued that all these phenomenons are intimately linked to the flow structures in compression regions, e.g. close to shocklets.

physics.flu-dyn↗

arXiv2021

Structure and Isotropy of Lattice Pressure Tensors for Multi-range Potentials

We systematically analyze the tensorial structure of the lattice pressure tensors for a class of multi-phase lattice Boltzmann models (LBM) with multi-range interactions. Due to lattice discrete effects, we show that the built-in isotropy properties of the lattice interaction forces are not necessarily mirrored in the corresponding lattice pressure tensor. This finding opens a different perspective for constructing forcing schemes, achieving the desired isotropy in the lattice pressure tensors via a suitable choice of multi-range potentials. As an immediate application, the obtained LBM forcing schemes are tested via numerical simulations of non-ideal equilibrium interfaces and are shown to yield weaker and less spatially extended spurious currents with respect to forcing schemes obtained by forcing isotropy requirements only. From a general perspective, the proposed analysis yields an approach for implementing forcing symmetries, never explored so far in the framework of the Shan-Chen method for LBM. We argue this will be beneficial for future studies of non-ideal interfaces.

cond-mat.stat-mech↗

arXiv2021

Oscillations Modulating Power Law Exponents in Isotropic Turbulence: Comparison of Experiments with Simulations

Inertial-range features of turbulence are investigated using data from experimental measurements of grid turbulence and direct numerical simulations of isotropic turbulence simulated in a periodic box, both at the Taylor-scale Reynolds number $R_λ\sim 1000$. In particular, oscillations modulating the power-law scaling in the inertial range are examined for structure functions up to sixth order moments. The oscillations in exponent ratios decrease with increasing sample size in simulations though, in experiments, they survive at a low value of $4$ parts in $1000$ even after massive averaging. The two data sets are consistent in their intermittent character but differ in small but observable respects. Neither the scaling exponents themselves nor all the viscous effects are consistently reproduced by existing models of intermittency.

physics.flu-dyn↗

arXiv2021

Base flow decomposition for complex moving objects in linear hydrodynamics: application to helix-shaped flagellated microswimmers

The motion of microswimmers in complex flows is ruled by the interplay between swimmer propulsion and the dynamics induced by the fluid velocity field. Here we study the motion of a chiral microswimmer whose propulsion is provided by the spinning of a helical tail with respect to its body in a simple shear flow. Thanks to an efficient computational strategy that allowed us to simulate thousands of different trajectories, we show that the tail shape dramatically affects the swimmer's motion. In the shear dominated regime, the swimmers carrying an elliptical helical tail show several different Jeffery-like (tumbling) trajectories depending on their initial configuration. As the propulsion torque increases, a progressive regularization of the motion is observed until, in the propulsion dominated regime, the swimmers converge to the same final trajectory independently on the initial configuration. Overall, our results show that elliptical helix swimmer presents a much richer variety of trajectories with respect to the usually studied circular helix tails.

physics.flu-dyn↗

arXiv2021

Immiscible Rayleigh-Taylor turbulence using mesoscopic lattice Boltzmann algorithms

We studied turbulence induced by the Rayleigh-Taylor (RT) instability for 2D immiscible two-component flows by using a multicomponent lattice Boltzmann method with a Shan-Chen pseudopotential implemented on GPUs. We compare our results with the extension to the 2D case of the phenomenological theory for immiscible 3D RT studied by Chertkov and collaborators ({\it Physical Review E 71, 055301, 2005}). Furthermore, we compared the growth of the mixing layer, typical velocity, average density profiles and enstrophy with the equivalent case but for miscible two-component fluid. Both in the miscible and immiscible cases, the expected quadratic growth of the mixing layer and the linear growth of the typical velocity are observed with close long-time asymptotic prefactors but different initial transients. In the immiscible case, the enstrophy shows a tendency to grow like $\propto t^{3/2}$, with the highest values of vorticity concentrated close to the interface. In addition, we investigate the evolution of the typical drop size and the behavior of the total length of the interface in the emulsion-like state, showing the existence of a power law behavior compatible with our phenomenological predictions. Our results can also be considered as a first validation step to extend the application of lattice Boltzmann tool to study the 3D immiscible case.

physics.flu-dyn↗

arXiv2021

Optimal control of point-to-point navigation in turbulent time-dependent flows using Reinforcement Learning

We present theoretical and numerical results concerning the problem to find the path that minimizes the time to navigate between two given points in a complex fluid under realistic navigation constraints. We contrast deterministic Optimal Navigation (ON) control with stochastic policies obtained by Reinforcement Learning (RL) algorithms. We show that Actor-Critic RL algorithms are able to find quasi-optimal solutions in the presence of either time-independent or chaotically evolving flow configurations. For our application, ON solutions develop unstable behavior within the typical duration of the navigation process, and are therefore not useful in practice. We first explore navigation of turbulent flow using a constant propulsion speed. Based on a discretized phase-space, the propulsion direction is adjusted with the aim to minimize the time spent to reach the target. Further, we explore a case where additional control is obtained by allowing the engine to power off. Exploiting advection of the underlying flow, allows the target to be reached with less energy consumption. In this case, we optimize a linear combination between the total navigation time and the total time the engine is switched off. Our approach can be generalized to other setups, for example, navigation under imperfect environmental forecast or with different models for the moving vessel.

eess.SY↗

arXiv2021

Cascade or not cascade? Energy transfer and elastic effects in active nematics

We numerically study the multi-scale properties of a 2d active gel to address the energy transfer mechanism. We find that activity is able to excite long-ranged distortions of the nematic pattern giving rise to spontaneous laminar flows and to a chaotic regime by further increasing the rate of active energy injection. By means of a scale-to-scale spectral analysis we find that the gel is basically driven by the local balancing between active injection and viscous dissipation, without any signal of non-linear hydrodynamical transfer and turbulent cascades. Furthermore, elasticity may qualitatively play an important role by transferring energy from small to larger scales through nemato-hydrodynamic interactions.

cond-mat.soft↗

arXiv2020

Lattice Boltzmann simulations on the tumbling to tank-treading transition: effects of membrane viscosity

The tumbling to tank-treading (TB-TT) transition for red blood cells (RBCs) has been widely investigated, with a main focus on the effects of the viscosity ratio $λ$ (i.e., the ratio between the viscosities of the fluids inside and outside the membrane) and the shear rate $\dotγ$ applied to the RBC. However, the membrane viscosity $μ_m$ plays a major role in a realistic description of RBC's dynamics, and only a few works have systematically focused on its effects on the TB-TT transition. In this work, we provide a parametric investigation on the effect of membrane viscosity $μ_m$ on the TB-TT transition, for a single RBC. It is found that, at fixed viscosity ratios $λ$, larger values of $μ_m$ lead to an increased range of values of capillary number at which the TB-TT transition occurs. We systematically quantify such an increase by means of mesoscale numerical simulations based on the lattice Boltzmann models.

cond-mat.soft↗

arXiv2020

Controlling Rayleigh-Bénard convection via Reinforcement Learning

Thermal convection is ubiquitous in nature as well as in many industrial applications. The identification of effective control strategies to, e.g., suppress or enhance the convective heat exchange under fixed external thermal gradients is an outstanding fundamental and technological issue. In this work, we explore a novel approach, based on a state-of-the-art Reinforcement Learning (RL) algorithm, which is capable of significantly reducing the heat transport in a two-dimensional Rayleigh-Bénard system by applying small temperature fluctuations to the lower boundary of the system. By using numerical simulations, we show that our RL-based control is able to stabilize the conductive regime and bring the onset of convection up to a Rayleigh number $Ra_c \approx 3 \cdot 10^4$, whereas in the uncontrolled case it holds $Ra_{c}=1708$. Additionally, for $Ra > 3 \cdot 10^4$, our approach outperforms other state-of-the-art control algorithms reducing the heat flux by a factor of about $2.5$. In the last part of the manuscript, we address theoretical limits connected to controlling an unstable and chaotic dynamics as the one considered here. We show that controllability is hindered by observability and/or capabilities of actuating actions, which can be quantified in terms of characteristic time delays. When these delays become comparable with the Lyapunov time of the system, control becomes impossible.

physics.flu-dyn↗

arXiv2020

Lattice Boltzmann simulations of droplet breakup in confined and time-dependent flows

We study droplet dynamics and breakup in generic time-dependent flows via a multicomponent Lattice Boltzmann algorithm, with emphasis on flow start up conditions. We first study droplet breakup in a confined oscillatory shear flow via two different protocols. In one set up, we start from an initially spherical droplet and turn on the flow abruptly ("shock method"); in the other protocol, we start from an initially spherical droplet as well, but we progressively increase the amplitude of the flow, by allowing the droplet to relax to the steady state for each increase in amplitude, before increasing the flow amplitude again ("relaxation method"). The two protocols are shown to produce substantially different breakup scenarios. The mismatch between these two protocols is also studied for variations in the flow topology, the degree of confinement and the inertia of the fluid. All results point to the fact that under extreme conditions of confinement the relaxation protocols can drive the droplets into metastable states, which break only for very intense flow amplitudes, but their stability is prone to external perturbations, such as an oscillatory driving force.

physics.flu-dyn↗

arXiv2019

Collective olfactory search in a turbulent environment

Finding the distant source of an odor dispersed by a turbulent flow is a vital task for many organisms, either for foraging or for mating purposes. At the level of individual search, animals like moths have developed effective strategies to solve this very difficult navigation problem based on the noisy detection of odor concentration and wind velocity alone. When many individuals concurrently perform the same olfactory search task, without any centralized control, sharing information about the decisions made by the members of the group can potentially increase the performance. But how much of this information is actually valuable and exploitable for the collective task ? Here we show that, in a model of a swarm of agents inspired by moth behavior, there is an optimal way to blend the private information about odor and wind detections with the publicly available information about other agents' heading direction. At optimality, the time required for the first agent to reach the source is essentially the shortest flight time from the departure point to the target. Conversely, agents who discard public information are several fold slower and groups that do not put enough weight on private information perform even worse. Our results then suggest an efficient multi-agent olfactory search algorithm that could prove useful in robotics, for instance in the identification of sources of harmful volatile compounds.

physics.bio-ph↗

arXiv2019

Zermelo's problem: Optimal point-to-point navigation in 2D turbulent flows using Reinforcement Learning

To find the path that minimizes the time to navigate between two given points in a fluid flow is known as Zermelo's problem. Here, we investigate it by using a Reinforcement Learning (RL) approach for the case of a vessel which has a slip velocity with fixed intensity, Vs , but variable direction and navigating in a 2D turbulent sea. We show that an Actor-Critic RL algorithm is able to find quasi-optimal solutions for both time-independent and chaotically evolving flow configurations. For the frozen case, we also compared the results with strategies obtained analytically from continuous Optimal Navigation (ON) protocols. We show that for our application, ON solutions are unstable for the typical duration of the navigation process, and are therefore not useful in practice. On the other hand, RL solutions are much more robust with respect to small changes in the initial conditions and to external noise, even when V s is much smaller than the maximum flow velocity. Furthermore, we show how the RL approach is able to take advantage of the flow properties in order to reach the target, especially when the steering speed is small.

nlin.CD↗

arXiv2019

Self-similar Subgrid-scale Models for Inertial Range Turbulence and Accurate Measurements of Intermittency

A class of spectral subgrid models based on a self-similar and reversible closure is studied with the aim to minimize the impact of subgrid scales on the inertial range of fully developed turbulence. In this manner, we improve the scale extension where anomalous exponents are measured by roughly one order of magnitude, when compared to direct numerical simulations or to other popular subgrid closures at the same resolution. We found a first indication that intermittency for high order moments is not captured by many of the popular phenomenological models developed so far.

physics.flu-dyn↗

arXiv2019

Multi-scale control of active emulsion dynamics

We numerically study the energy transfer in a multi-component $2d$ film, made of an active polar gel and a passive isotropic fluid in presence of surfactant favoring emulsification. We show that by confining the active behavior into the localized component, the typical scale where chemical energy is transformed in mechanical energy can be substantially controlled. Quantitative analysis of kinetic energy spectra and fluxes shows the presence of a multi-scale dynamics due to the existence of a flux induced by the active stress only, without the presence of a turbulent cascade. An increase in the intensity of active doping induces drag reduction due to the competition of elastic and dissipative stresses against active forces. Furthermore we show that a non-homogeneous activity pattern induces localized response, including a modulation of the slip length, opening the way toward the control of active flows by external doping.

cond-mat.soft↗