Immiscible Rayleigh-Taylor turbulence: Implications for bacterial degradation in oil spills.

An unstable density stratification between two fluids mixes spontaneously under the effect of gravity, a phenomenon known as Rayleigh-Taylor (RT) turbulence. If the two fluids are immiscible, for example, oil and water, surface tension prevents intermixing at the molecular level. However, turbulence fragments one fluid into the other, generating an emulsion in which the typical droplet size decreases over time as a result of the competition between the rising kinetic energy and the surface energy density. Even though the first phenomenological theory describing this emulsification process was derived many years ago, it has remained elusive to experimental verification, hampering our ability to predict the fate of oil in applications such as deep-water spills. Here, we provide the first experimental and numerical verification of the immiscible RT turbulence theory, unveiling a unique turbulent state that originates at the oil-water interface due to the interaction of multiple capillary waves. We show that a single, non-dimensional, and time-independent parameter controls the range of validity of the theory. Our findings have wide-ranging implications for the understanding of the mixing of immiscible fluids. This includes in particular oil spills, where our work enables the prediction of the oil-water interface dynamics that ultimately determine the rate of oil biodegradation by marine bacteria.

Rotor-Stator Emulsification in the Turbulent Inertial Regime: Experiments toward a Robust Correlation for the Droplet Size.

The Sauter mean diameter, d32, is a representative parameter in emulsions that indicates the average size of the oil droplets once the emulsion becomes stable. Several mathematical and physical approaches have been employed in the literature to seek expressions for d32 under different conditions. The present work sheds light on this rich literature and emphasizes that the characterization of emulsions is still a fertile field for investigation. In this paper, a new Π-theorem-based model to predict the normalized Sauter mean diameter for the specific case of rotor-stator emulsification is sought by applying a multiple regression analysis on experimental data of oil-in-water (O-W) emulsions produced using three different oils: paraffin, soybean oil, and isopropyl myristate, at different oil-to-water (O/W) ratios and rotor speeds. The proposed model quantifies the roles of the viscous, inertial, and interfacial tension forces, besides the O/W ratio, in the emulsification process within the turbulent inertial subrange. The developed empirical correlation is then contrasted with relevant literature models for reliability assessment; predictions of the present explicit model are proven to be more accurate for the fluid properties and the experimental conditions under study.

Timing of fungal spore release dictates survival during atmospheric transport.

Fungi disperse spores to move across landscapes and spore liberation takes different patterns. Many species release spores intermittently; others release spores at specific times of day. Despite intriguing evidence of periodicity, why (and if) the timing of spore release would matter to a fungus remains an open question. Here we use state-of-the-art numerical simulations of atmospheric transport and meteorological data to follow the trajectory of many spores in the atmosphere at different times of day, seasons, and locations across North America. While individual spores follow unpredictable trajectories due to turbulence, in the aggregate patterns emerge: Statistically, spores released during the day fly for several days, whereas spores released at night return to ground within a few hours. Differences are caused by intense turbulence during the day and weak turbulence at night. The pattern is widespread but its reliability varies; for example, day/night patterns are stronger in southern regions. Results provide testable hypotheses explaining both intermittent and regular patterns of spore release as strategies to maximize spore survival in the air. Species with short-lived spores reproducing where there is strong turbulence during the day, for example in Mexico, maximize survival by releasing spores at night. Where cycles are weak, for example in Canada during fall, there is no benefit to releasing spores at the same time every day. Our data challenge the perception of fungal dispersal as risky, wasteful, and beyond control of individuals; our data suggest the timing of spore liberation may be finely tuned to maximize fitness during atmospheric transport.

Puff turbulence in the limit of strong buoyancy.

We provide a numerical validation of a recently proposed phenomenological theory to characterize the space-time statistical properties of a turbulent puff, both in terms of bulk properties, such as the mean velocity, temperature and size, and scaling laws for velocity and temperature differences both in the viscous and in the inertial range of scales. In particular, apart from the more classical shear-dominated puff turbulence, our main focus is on the recently discovered new regime where turbulent fluctuations are dominated by buoyancy. The theory is based on an adiabaticity hypothesis which assumes that small-scale turbulent fluctuations rapidly relax to the slower large-scale dynamics, leading to a generalization of the classical Kolmogorov and Kolmogorov-Obukhov-Corrsin theories for a turbulent puff hosting a scalar field. We validate our theory by means of massive direct numerical simulations finding excellent agreement. This article is part of the theme issue 'Scaling the turbulence edifice (part 2)'.

Unraveling the Secrets of Turbulence in a Fluid Puff.

Turbulent puffs are ubiquitous in everyday life phenomena. Understanding their dynamics is important in a variety of situations ranging from industrial processes to pure and applied science. In all these fields, a deep knowledge of the statistical structure of temperature and velocity space-time fluctuations is of paramount importance to construct models of chemical reaction (in chemistry) and of condensation of virus-containing droplets (in virology and/or biophysics) and optimal mixing strategies in industrial applications. As a matter of fact, results of turbulence in a puff are confined to bulk properties (i.e., average puff velocity and typical decay or growth time) and date back to the second half of the 20th century. There is, thus, a huge gap to fill to pass from bulk properties to two-point statistical observables. Here, we fill this gap by exploiting theory and numerics in concert to predict and validate the space-time scaling behaviors of both velocity and temperature structure functions including intermittency corrections. Excellent agreement between theory and simulations is found. Our results are expected to have a profound impact on developing evaporation models for virus-containing droplets carried by a turbulent puff, with benefits to the comprehension of the airborne route of virus contagion.

Dispersed Fibers Change the Classical Energy Budget of Turbulence via Nonlocal Transfer.

The backreaction of dispersed rigid fibers to turbulence is analyzed by means of a state-of-the-art fully coupled immersed boundary method. The following universal scenario is identified: turbulence at large scales looses a consistent part of its kinetic energy (via a Darcy friction term), which partially reappears at small scales where a new range of energy-containing scales does emerge. Large-scale mixing is thus depleted in favor of a new mixing mechanism arising at the smallest scales. Anchored fibers cause the same backreaction to turbulence as moving fibers of large inertia. Our results thus provide a link between two apparently separated realms: the one of porous media and the one of suspension dynamics.

Flexible Fiber Reveals the Two-Point Statistical Properties of Turbulence.

We study the dynamics of a flexible fiber freely moving in a three-dimensional fully developed turbulent field and present a phenomenological theory to describe the interaction between the fiber elasticity and the turbulent flow. This theory leads to the identification of two distinct regimes of flapping, which we validate against direct numerical simulations fully resolving the fiber dynamics. The main result of our analysis is the identification of a flapping regime where the fiber, despite its elasticity, is slaved to the turbulent fluctuations. In this regime the fiber can be used to measure two-point statistical observables of turbulence, including scaling exponents of velocity structure functions, the sign of the energy cascade and the energy flux of turbulence, as well as the characteristic times of the eddies within the inertial range of scales. Our results are expected to have a deep impact on the experimental turbulence research as a new way, accurate and efficient, to measure two-point, and more generally multipoint, statistics of turbulence.

Hybrid AI-enhanced lightning flash prediction in the medium-range forecast horizon.

Traditional fully-deterministic algorithms, which rely on physical equations and mathematical models, are the backbone of many scientific disciplines for decades. These algorithms are based on well-established principles and laws of physics, enabling a systematic and predictable approach to problem-solving. On the other hand, AI-based strategies emerge as a powerful tool for handling vast amounts of data and extracting patterns and relationships that might be challenging to identify through traditional algorithms. Here, we bridge these two realms by using AI to find an optimal mapping of meteorological features predicted two days ahead by the state-of-the-art numerical weather prediction model by the European Centre for Medium-range Weather Forecasts (ECMWF) into lightning flash occurrence. The prediction capability of the resulting AI-enhanced algorithm turns out to be significantly higher than that of the fully-deterministic algorithm employed in the ECMWF model. A remarkable Recall peak of about 95% within the 0-24 h forecast interval is obtained. This performance surpasses the 85% achieved by the ECMWF model at the same Precision of the AI algorithm.

Spontaneous symmetry breaking of a hinged flapping filament generates lift.

Elastic filamentous structures found on swimming and flying organisms are versatile in function, rendering their precise contribution to locomotion difficult to assess. We show in this Letter that a single passive filament hinged on the rear of a bluff body placed in a stream can generate a net lift force without increasing the mean drag force on the body. This is a consequence of spontaneous symmetry breaking in the filament's flapping dynamics. The phenomenon is related to a resonance between the frequency associated with the von Kármán vortex street developing behind the bluff body and the natural frequency of the free bending vibrations of the filament.

Transport and evaporation of virus-containing droplets exhaled by men and women in typical cough events.

The spreading of the virus-containing droplets exhaled during respiratory events, e.g., cough, is an issue of paramount importance for the prevention of many infections such as COVID-19. According to the scientific literature, remarkable differences can be ascribed to several parameters that govern such complex and multiphysical problem. Among these, a particular influence appears associated with the different airflows typical of male and female subjects. Focusing on a typical cough event, we investigate this aspect by means of highly-resolved direct numerical simulations of the turbulent airflow in combination with a comprehensive Lagrangian particle tracking model for the droplet motion and evaporation. We observe and quantify major differences between the case of male and female subjects, both in terms of the droplet final reach and evaporation time. Our results can be associated with the different characteristics in the released airflow and thus confirm the influence of the subject gender (or other physical properties providing different exhalation profiles) on both short-range and long-range airborne transmission.

Biological fluid dynamics of airborne COVID-19 infection.

ABSTRACT: We review the state of knowledge on the bio-fluid dynamic mechanisms involved in the transmission of the infection from SARS-CoV-2. The relevance of the subject stems from the key role of airborne virus transmission by viral particles released by an infected person via coughing, sneezing, speaking or simply breathing. Speech droplets generated by asymptomatic disease carriers are also considered for their viral load and potential for infection. Proper understanding of the mechanics of the complex processes whereby the two-phase flow emitted by an infected individual disperses into the environment would allow us to infer from first principles the practical rules to be imposed on social distancing and on the use of facial and eye protection, which to date have been adopted on a rather empirical basis. These measures need compelling scientific validation. A deeper understanding of the relevant biological fluid dynamics would also allow us to evaluate the contrasting effects of natural or forced ventilation of environments on the transmission of contagion: the risk decreases as the viral load is diluted by mixing effects but contagion is potentially allowed to reach larger distances from the infected source. To that end, our survey supports the view that a formal assessment of a number of open problems is needed. They are outlined in the discussion.

Scaling and statistical geometry in passive scalar turbulence.

We show that the statistics of a turbulent passive scalar at scales larger than the pumping may exhibit multiscaling due to a weaker mechanism than the presence of statistical conservation laws. We develop a general formalism to give explicit predictions for the large scale scaling exponents in the case of the Kraichnan model and discuss their geometric origin at small and large scale.

Route to non-Gaussian statistics in convective turbulence.

Motivated by the work of Li and Meneveau [Phys. Rev. Lett. 95, 164502 (2005)], we propose and solve a model for the Lagrangian evolution of both longitudinal and transverse velocity and temperature increments for Boussinesq convection. From this model, the short-time evolution of an initially imposed Gaussian joint probability density function (PDF) of both velocity and temperature increments is computed analytically and the trend to non-Gaussian statistics shown in a quantitative way. Predictions for moments of the joint PDF are obtained and their behavior analyzed with respect to known experimental and numerical results. The obtained results do not depend on the model free parameters, a fact in favor of their robustness.

Drag reduction in the turbulent Kolmogorov flow.

We investigate the phenomenon of drag reduction in a viscoelastic fluid model of dilute polymer solutions. By means of direct numerical simulations of the three-dimensional turbulent Kolmogorov flow we show that drag reduction takes place above a critical Reynolds number Re(c). An explicit expression for the dependence of Re(c) on polymer elasticity and diffusivity is derived. The values of the drag coefficient obtained for different fluid parameters collapse onto a universal curve when plotted as a function of the rescaled Reynolds number Re/ Re(c). The analysis of the momentum budget allows us to gain some insight on the physics of drag reduction, and suggests the existence of a Re-independent value of the drag cofficient--lower than the Newtonian one--for large Reynolds numbers.

Dynamics of light particles in oscillating cellular flows.

The dynamics of light particles in chaotic oscillating cellular flows is investigated both analytically and numerically by means of Monte Carlo simulations. At level of linear analysis (in the oscillation amplitude) we determined how the known fixed points relative to the stationary cellular flow deform into closed stable trajectories. Once the latter have been analytically determined, we numerically show that they possess the dynamical role of attracting all asymptotic trajectories for a wide range of parameters values. The robustness of the attracting trajectories is tested by adding a white-noise contribution to the particle equation of motion. As a result, attracting trajectories persist up to a critical Péclet number above which an average rising velocity sets in. Possible implications of our results on the long-standing problem related to the explanation of the observed oceanic plankton patchiness will be also discussed.

Scaling properties of the two-dimensional randomly stirred Navier-Stokes equation.

We inquire into the scaling properties of the 2D Navier-Stokes equation sustained by a force field with Gaussian statistics, white noise in time, and with a power-law correlation in momentum space of degree 2 - 2 epsilon. This is at variance with the setting usually assumed to derive Kraichnan's classical theory. We contrast accurate numerical experiments with the different predictions provided for the small epsilon regime by Kraichnan's double cascade theory and by renormalization group analysis. We give clear evidence that for all epsilon, Kraichnan's theory is consistent with the observed phenomenology. Our results call for a revision in the renormalization group analysis of (2D) fully developed turbulence.

Rayleigh-Taylor turbulence in two dimensions.

The first consistent phenomenological theory for two- and three-dimensional Rayleigh-Taylor (RT) turbulence has recently been presented by Chertkov [Phys. Rev. Lett. 91, 115001 (2003)]. By means of direct numerical simulations, we confirm the spatiotemporal prediction of the theory in two dimensions and explore the breakdown of the phenomenological description due to intermittency effects. We show that small-scale statistics of velocity and temperature follow Bolgiano-Obukhov scaling. At the level of global observables, we show that the time-dependent Nusselt and Reynolds numbers scale as the square root of the Rayleigh number. These results point to the conclusion that RT turbulence in two and three dimensions, thanks to the absence of boundaries, provides a natural physical realization of the Kraichnan scaling regime hitherto associated with the elusive "ultimate state of thermal convection."

Scaling and universality in turbulent convection.

Anomalous correlation functions of the temperature field in two-dimensional turbulent convection are shown to be universal with respect to the choice of external sources. Moreover, they are equal to the anomalous correlations of the concentration field of a passive tracer advected by the convective flow itself. The statistics of velocity differences is found to be universal, self-similar, and close to Gaussian. These results point to the conclusion that temperature intermittency in two-dimensional turbulent convection may be traced back to the existence of statistically preserved structures, as it is in passive scalar turbulence.

Active versus passive scalar turbulence.

Active and passive scalars transported by an incompressible two-dimensional conductive fluid are investigated. It is shown that a passive scalar displays a direct cascade towards the small scales while the active magnetic potential builds up large-scale structures in an inverse cascade process. Correlations between scalar input and particle trajectories are found to be responsible for those dramatic differences as well as for the behavior of dissipative anomalies.