Recent work has demonstrated that Lagrangian chaos can arise at the Darcy scale in even simple poroelastic media, relevant across geophysical, biophysical, and industrial domains. Key factors controlling the onset of chaotic advection in poroelastic media flow include medium heterogeneity, compressibility, and transient forcing. Here we focus on how the range of Lagrangian coherent structures (LCSs) present in poroelastic flows influences the transport of diffusive solutes. We use a minimal two-dimensional sinusoidally forced poroelastic computational model to show that LCS interactions impact the dispersion of solute plumes via the establishment of minimum flux manifolds, leading to strongly anomalous plume moments and solute residence time distributions. We interpret these results with fluid element stretching distributions and local Lyapunov exponents. Anomalous features persist even at low Péclet number. Our data show that solute dispersion in poroelastic systems subject to transient forcing can only be understood by resolving the LCSs of these complex flows.

To tackle the challenging near-wall turbulence modeling while preserving low computational cost, the near-wall nonoverlapping domain decomposition (NDD) method is proposed, incorporating the machine-learning technique. Using recently proposed implicit NDD (INDD), the solution can be calculated with a Robin-type (slip) wall boundary condition on a relatively coarse mesh and then corrected in the near-wall region at every iteration through an estimated turbulent viscosity profile obtained from a neural network. To maintain a reasonable complexity with acceptable accuracy, only the near-wall field properties, i.e., wall-normal distance, near-wall velocities, streamwise pressure gradients, and one near-wall scale parameter, are employed as the input features for the neural network. The benefit of incorporating machine learning is twofold. First, the near-wall turbulent viscosity is predicted more accurately than by the traditional algebraic functions used in the approximate approach. Second, similarly to the conventional NDD, the present simulations save one order of computational cost over the fully resolved one-block simulations. The accuracy and efficiency of the method are demonstrated on test cases with the $k\text{−}\varepsilon$ model, including turbulent flows in a channel and an asymmetric diffuser at different Reynolds numbers. Results compare favorably with the one-block benchmark solutions and show a better agreement when compared with approximate NDD predictions. In the latter case, a variation of diffuser geometry is also considered to test the model performance on engineering design tasks with another turbulent model (i.e., Spalart-Allmaras), showing good generalization capability on different turbulence closures.

Three-dimensional direct numerical simulations are used to revisit the experiments on multibubble cavitation performed by Bremond et al., Phys. Fluids 18, 121505 (2006); Phys. Rev. Lett. 96, 224501 (2006). In particular, we aim at understanding the asymmetry observed therein during the expansion and collapse of bubble clusters subjected to a pressure pulse. Our numerical simulations suggest that the asymmetry is due to the force applied by the imposed pressure pulse and it is a consequence of the finite effective speed of sound in the liquid. By comparing our numerical results to the experiments, we found that the effective speed of sound under the experimental conditions was smaller than that of degassed water due to microbubbles in the system which resulted from prior cavitation experiments in the same setup. The estimated values of the effective speed of sound are consistent with those derived from the classical theory of wave propagation in liquids with small amounts of gas. To support this theory, we also present evidence of tiny bubbles remaining in the liquid bulk as a result of the fragmentation of large bubbles during the prior cavitation experiments. Furthermore, we find that this asymmetry also alters the direction of the liquid jet generated during the last stages of bubble collapse.

In convective fluids, small vortices develop between neighboring convective cells. Familiar in the atmosphere in the form of dust devils and water spouts, these convective vortices have been seen in simulations of oceanic convection where the vortices exhibit an unexplained bias towards cyclonic rotation despite having a large Rossby number. Here we use large eddy simulations (LES) of an idealized oceanic convective mixed layer and vary independently the Coriolis acceleration and the surface buoyancy flux to investigate the development of the cyclonic bias of convective vortices. While large convective vortices are biased for sufficiently large values of the Coriolis parameter, small convective vortices do not exhibit a clear bias. Using Lagrangian particles, we find that the large convective vortices develop through the merger of many small convective vortices. We propose a statistical theory to predict the cyclonic bias of large convective vortices composed of many small unbiased convective vortices and test the theory using LES results. We apply the theory to typical convective conditions and find that convective vortices in upper ocean mixed layers are expected to exhibit a bias, while convective vortices in the terrestrial and Martian atmospheres are expected to be largely unbiased.

We present a physically motivated low-dimensional model for the dynamics of two interacting large-scale circulations (LSC) in two-layer turbulent convection. Inspired by our experimental results of the flow dynamics and coupling in two-layer turbulent convection [J. Fluid Mech. 728, R1 (2013)], the model extends previous studies of single-LSC dynamics to incorporate four stochastic ordinary differential equations describing the strength $\delta$ and azimuthal orientations $\theta$ of two vertically aligned LSCs. The interaction terms of the two LSCs, i.e., thermal and viscous coupling terms, are predicted based on the influence of the fluid temperature by the other LSC through heat advection and thermal diffusion, and the enhanced (reduced) viscous damping across the interface between the two LSCs. Our model produces two stable LSC rolls and predicts their preferred flow states for the thermal and viscous couplings. The model describes properly the diffusive motion of both $\delta$ and $\theta$ of the two LSCs, and the Poissonian distribution of time interval between LSC cessations. More importantly, our study reveals that flow reversals and cessations in two-layer convection can be achieved when turbulent fluctuations drive the azimuthal diffusion of the two LSCs into a flow state that the two LSC planes are orthogonal to each other, the strength of the LSC in the fluid layer with a relatively larger Rayleigh number reduces to zero deterministically, owing to the unbalanced buoyancy forcing. Our model provides accurate predictions for the enhanced occurrence frequency of flow reversals observed in the experiment, and it suggests a new dynamical process of flow reversals in multilayer turbulent convection.

Previous results of discrete simulations of steady, unidirectional particle flows, here collected and critically reanalyzed, permit to make the case that the kinetic theory of granular gases, extended to include the correlations in the velocity fluctuations and the role of friction in collisions, provides the long-sought universal framework to predict the flow of realistic particles over the entire range of solid volume fraction from dilute to very dense—the upper limit being the critical value at which rate-independent components of the stresses arise. The case is made even stronger by the explicit derivation of the popular inertial rheology and its nonlocal extension to deal with heterogeneities based on the granular fluidity concept as special limits of the kinetic theory. In the process, common statements about the frictional-collisional duality in the granular stresses and the importance of long-lasting contacts creating a percolating network are shown to be greatly exaggerated for granular flows in practical applications.

The stresslet in a dilute suspension of rigid spheres in an Oldroyd-B fluid under imposed shear and uniaxial exentional flow is studied using a combination of analytical and numerical techniques. Previous work has focused on the stresslet contribution to the per-particle viscosity of a suspension. This contribution has been shown to decrease with increasing suspending fluid elasticity in shear and decrease with increasing strain in transient uniaxial extension. By considering the surface tractions in the Newtonian limit, we propose analytical scalings for the three components of the stresslet—pressure, viscous stress, and polymer stress—as functions of the appropriate Weissenberg or Deborah number. We conduct direct numerical simulations of a dilute sphere in viscoelastic fluid flow to compare against analytical scalings and see good agreement for weak elasticity, with increasing deviations as the fluid becomes increasingly elastic. Finally, we discuss the consequences of these trends on the tractions and stresses experienced by the suspended particles.

We conducted experiments using a typical centimeter swimmer, A. salina, and an electromagnetically driven quasi-two-dimensional flow to study the interaction between active matter and flow. The flow spanned from time-independent cellular flow to weakly time-dependent regimes. We focused on the impact of swarming active matter on hyperbolic Lagrangian coherent structures (LCSs) that mark the most straining regions in the flow. There is one decade of scale separation between active matter agents and the length scale of LCSs. We illustrated that the impact of active matter on LCSs was much more significant compared to localized random noise with similar energy input. In addition, we revealed that the perturbation generated by active matter could couple with the background flow and further deform the LCSs. In addition to the impact on the most straining hyperbolic regions of flow, we also revealed that the rotational elliptical region of the flow was much more susceptible to active matter perturbation in a Lagrangian perspective. We further described how the influence of active matter changed with their number densities and background flow intensities. We revealed that the LCSs could be decently altered even at a small number density of active matter. Through this work, we aim to provide valuable insights and draw attention to the problem regarding the interaction between active matter and external flow structures.

The reconstruction of incomplete information in flow fields is a pervasive challenge in numerous turbulence-related applications. This paper proposes a framework for the high-fidelity reconstruction of large-area damaged turbulent fields with high resolution based on a physically constrained generative adversarial network. The network incorporates some special designs, such as leveraging complete or sparse fields of velocity components as physical constraints, employing a ResNet-like network with a fast Fourier convolution module, and adopting a PatchGAN discriminator network. To train the network, we employ a combination of loss functions, which comprise mean absolute error, network-level loss, and feature matching loss. We validate our method on a dataset of compressible isotropic turbulent flow and investigate three distinct damaged distributions with gap ratios of $39.06\%$ and $56.25\%$. The proposed reconstruction framework has been shown to achieve excellent reconstruction performance. The reconstructed flow fields are consistent with the raw flow fields in terms of magnitude, power spectrum, and two-point correlation function. We also provide extensive ablation studies to validate our approach. The results indicate that the utilization of physical constraints significantly improves the reconstruction performance in damaged regions, particularly in cases that involve a large damaged area. Furthermore, in the proposed reconstruction framework, the size of patch in the PatchGAN discriminator network can be flexibly adjusted according to the scale of turbulence structures, and the perceptual loss function plays a crucial role in evaluating differences between feature maps of flow fields at network levels based on a pretrained network. These special designs ensure consistency across diverse scales of turbulence structures and improve the accuracy and efficiency of network training.

A theoretical analysis is presented for the flow of a Herschel-Bulkley fluid around the inside surface of a rotating cylinder, at rotation speeds for which the fluid largely collects in a prominent pool in the lower part of the cylinder. The analysis, based on lubrication theory, predicts the steady states typically reached after a small number of rotations. The analysis is also modified to consider the drainage of the film around a stationary cylinder, which allows an exploration of the dynamics when a rotating drum is suddenly stopped. The predictions of the theory are compared with experiments in which a Carbopol suspension is rotated inside an acrylic drum.

In the present work, a numerical framework is developed for simulating gas-solid flows associated with interaction of a rocket plume on a planetary surface. For this investigation, a unique, two-way coupled, dusty-gas flow model has been developed in the coupled direct simulation Monte Carlo (DSMC)-discrete element method (DEM) framework, which has been applied for dust dispersion on lunar surface. In this model, the gas-gas collisions are modeled probabilistically, whereas grain-grain interactions are computed deterministically. Most importantly, a multiphase fluid-solid two-way coupling model is proposed where the fluid-particle interaction is modeled macroscopically by considering the momentum and energy exchange between the two phases. The use of the DEM approach allows us to model dense granular phase near a planetary regolith. Additionally, the framework allows us to calculate not only the particle trajectories, but also their temperatures. To make the framework efficient for dynamic calculation of drag and heat transfer from gas to grain phase, the same coefficients are precalculated (and used later as a look-up table) for gas flow over an isolated granular particle over a range of speed ratios for free molecular flow conditions. Using the developed framework, a comprehensive numerical study is performed to model dust dispersion associated with lunar landing. The influence of particle diameter on gas and grain phases and dust transportation has been analyzed in the coupled framework. Additionally, the impact of the two-way coupled gas-grain interaction model is analyzed and compared with one-way coupled model.

Turbulence in wall-bounded flows is characterized by stable statistics for the mean flow and the fluctuations both for the case of the ensemble and the time mean. Although in a substantial set of turbulent systems, this stable statistical state corresponds to a stable fixed point of an associated statistical state dynamics (SSD) closed at second order, referred to as S3T, this is not the case for wall turbulence. In wall turbulence the trajectory of the statistical state evolves on a transient chaotic attractor in the S3T statistical state phase space and the time-mean statistical state is neither a stable fixed point of this SSD nor, if the time-mean statistical state is maintained as an equilibrium state, is it stable. Nevertheless, sufficiently small perturbations from the ensemble or time-mean state of wall turbulence are expected to relax back to the mean statistical state following an effective linear dynamics. In this work the dynamics of spanwise uniform perturbations to the time-mean flow are studied using a linear inverse model to identify the linear operator governing the ensemble stability of the ensemble or time-mean state by obtaining the time mean stability properties over the transient attractor of the turbulence identified by the S3T SSD. The ensemble or time-mean stability of an unstable equilibrium can be understood by noting that, even when every member of an ensemble is unstable, the ensemble mean may be stable with perturbations following an identifiable stable dynamics. While simplifying insight into turbulent flows has commonly been obtained by identifying and studying ensemble mean statistical states, less attention has been accorded to identifying and studying the ensemble mean dynamics. We show that, in the case of wall turbulence, even though stable fixed-point SSD equilibria are not available to allow application of traditional perturbation analysis methods to identify the perturbation stability of the mean state, an effective linear stability analysis can be obtained to identify the perturbation dynamics of the ensemble or time-mean statistical state.

Using fluid displacement in a Hele-Shaw cell, we experimentally demonstrate the arresting effect of an imposed flow on a phase separation occurring in a growing liquid-liquid interfacial region, unlike in an initially homogeneous single-phase mixture quenched within the miscibility gap. Increasing the imposed flow rate reduces the exponent α in the form $\mathrm{\Delta }A\propto t^{\alpha }$, where $\mathrm{\Delta }A$ is the increase in the area occupied by the displacing fluid owing to phase separation. We show that α can be expressed as a function of the ratio of the phase separation rate to the flow rate on a single curve, indicating that the competition between the imposed flow and phase separation rates determines the degree of the interfacial phase separation. The arresting effect and the mechanism are verified by a numerical simulation.

Liquid nanofilms are ubiquitous in nature and technology, and their equilibrium and out-of-equilibrium dynamics are key to a multitude of phenomena and processes. We numerically study the evolution and rupture of viscous nanometric films, incorporating the effects of surface tension, van der Waals forces, thermal fluctuations, and viscous shear. We show that thermal fluctuations create perturbations that can trigger film rupture, but they do not significantly affect the growth rate of the perturbations. The film rupture time can be predicted from a linear stability analysis of the governing thin film equation, by considering the most unstable wavelength and the thermal roughness. Furthermore, applying a sufficiently large unidirectional shear can stabilize large perturbations, creating a finite-amplitude traveling wave instead of film rupture. In three dimensions, unidirectional shear does not inhibit rupture, as perturbations are not suppressed in the direction perpendicular to the applied shear. However, if the direction of shear varies in time, then the growth of large perturbations is prevented in all directions, and rupture can be impeded.

When a drop of a volatile liquid is deposited on a uniformly heated wettable, thermally conducting substrate, one expects to see it spread into a thin film and evaporate. Contrary to this intuition, due to thermal Marangoni contraction, the deposited drop contracts into a spherical-cap-shaped puddle, with a finite apparent contact angle. Strikingly, this contracted droplet, above a threshold temperature, well below the boiling point of the liquid, starts to spontaneously move on the substrate in an apparently erratic way. We describe and quantify this self-propulsion of the volatile drop. It arises due to spontaneous symmetry breaking of thermal Marangoni convection, which is induced by the nonuniform evaporation of the droplet. Using infrared imaging, we reveal the characteristic interfacial flow patterns associated with Marangoni convection in the evaporating drop. A scaling relation describes the correlation between the moving velocity of the drop and the apparent contact angle, both of which increase with the substrate temperature.

Active flow control can achieve substantial performance gains and meet the challenges of next-generation air vehicles and energy-harvesting devices. The use of active flow control techniques with the moving flap or morphing surfaces has been shown to be a viable path to regulating the flow-induced vibration of the foil. However, due to the complex nature of flow over morphing surfaces, all physical phenomena are intertwined, which prevents a clear understanding of the underlying flow physics and, therefore, a successful design of a controlling action to optimally modify them. In this research an active flow control framework with the model predictive control theory is proposed to modulate the flow-induced flutter of a foil using the morphing flap surface. The geometrically weighted dynamic-relevant modes are used to build surrogate models to achieve rapid model-based active control of complex systems. It is shown that the flap is capable of both facilitating and eliminating fluid-induced vibrations by regulating the lift forces exerted on the foil. Furthermore, the control framework provides full knowledge of how the structure modifies the flow and has the potential to identify the ambient environmental change simultaneously.

Fluid-structure interactions between active and passive components are important for many biological systems to function. A particular example is chromatin in the cell nucleus, where ATP-powered processes drive coherent motions of the chromatin fiber over micron lengths. Motivated by this system, we develop a multiscale model of a long flexible polymer immersed in a suspension of active force dipoles as an analog to a chromatin fiber in an active fluid—the nucleoplasm. Linear analysis identifies an orientational instability driven by hydrodynamic and alignment interactions between the fiber and the suspension, and numerical simulations show activity can drive coherent motions and structured conformations. These results demonstrate how active and passive components, connected through fluid-structure interactions, can generate coherent structures and self-organize on large scales.

Molecular tagging is used to study the dispersion and deformation of patterns written in turbulent air. The writing is done by fusing ${\mathrm{O}}_2$ and ${\mathrm{N}}_2$ molecules into NO in the focus of a strong ultraviolet laser beam. By crossing several of these laser beams, patterns that have both small and large scales can be painted. The patterns are visualized a while later by inducing fluorescence of the NO molecules with a second UV laser and registering the image. The width of the lines that make the pattern is approximately $50\mu \mathrm{m}$, a few times the Kolmogorov length $\eta$, the smallest length scale in turbulence, while the largest size of the patterns ($\approx 4\mathrm{mm}$) is inside the inertial range of the used turbulent jet flow. At small scales molecular clouds disperse under the joint action of molecular diffusion and turbulence. The experiments reveal this highly nontrivial interaction. At inertial-range scales ($\approx 200\eta$) we verify the Batchelor dispersion of objects whose size is inside the inertial range. Patterns are compressible objects and spontaneously develop concentration fluctuations. We show for the first time the nontrivial statistical properties of these fluctuations. Finally, we use the information in written and deformed lines to quantify turbulent intermittency, obtaining results that agree with the established scaling anomaly of velocity structure functions.

We present the observation of an expanding vortex ring below a fast-spreading ethanol-water film over a deep substrate of water. The radius of the vortex ring ($r_v$) is shown to scale with time as $t^{1/2}$. The outer radius of the disturbed region ($r_o$), which comprises the expanding film of length $r_f$ and the plume of length $l_p$ at its periphery, scales in the same way as $r_v$. Based on this observation, contrary to the earlier proposal of the origin of such vortex rings to be due to evaporative cooling, we hypothesize that such vortex rings occur due to the separation of the shear layer below the plumes. Based on this hypothesis, we obtain scaling laws for the radius of the vortex ring ($r_v$) and its radial expansion velocity ($U_v$). These scaling laws are shown to match our measurements, thereby validating the phenomenology of such vortex rings.

We experimentally investigate the amplitude of the common sound heard when we pour water, tea, or coffee on a filled receptacle. Using water jets from circular nozzles, we find that pouring is audible when the nozzle distance from the free surface is above one-third of the jet breakup length. The sound amplitude increases with the steepness of the jet corrugation, informing that thin jets are louder than thick ones for a given pouring height. Since the jet corrugation is related to the air entrainment rate, the sound of pouring can serve as a practical noninvasive probe in aeration processes. After the jet breaks up into drops impacting on the free surface, the pouring sound amplitude increases with the nozzle diameter, unlike before breakup.