Birds have to flap their wings to generate the needed thrust force, which powers them through the air. But how exactly do flapping wings create such force, and at what amplitude and frequency should they operate? These questions have been asked by many researchers. It turns out that much of the secret is hidden in the wake left behind the flapping wing. Exemplified by the study of Andersen et al. (J. Fluid Mech., vol. 812, 2017, R4), close examination of the flow pattern behind a flapping wing will inform us whether the wing is towed by an external force or able to generate a net thrust force by itself. Such studies are much like looking at the footprints of terrestrial animals as we infer their size and weight, figuring out their walking and running gaits. A map that displays the collection of flow patterns after a flapping wing, using flapping frequency and amplitude as the coordinates, offers a full picture of its flying ‘gaits’.

Stirring olive oil and vinegar to make salad dressing creates an emulsion of vinegar droplets in oil. More vigorous stirring gives smaller droplets, while if left to sit the droplets will begin to coalesce and the two fluids will separate. In this vein, Dodd & Ferrante (J. Fluid Mech., vol. 806, 2016, pp. 356–412) present a new analysis of how homogeneous turbulence in a carrier fluid interacts with a suspension of droplets of an immiscible liquid. Based on a set of direct numerical simulations, the authors provide new insights on how turbulence affects the motion of the droplets, their shape and size; then in turn how the droplets alter the flow including effects of interfacial surface energy on the kinetic energy of the flow.

It was only a matter of time before deep neural networks (DNNs) – deep learning – made their mark in turbulence modelling, or more broadly, in the general area of high-dimensional, complex dynamical systems. In the last decade, DNNs have become a dominant data mining tool for big data applications. Although neural networks have been applied previously to complex fluid flows, the article featured here (Ling et al., J. Fluid Mech., vol. 807, 2016, pp. 155–166) is the first to apply a true DNN architecture, specifically to Reynolds averaged Navier Stokes turbulence models. As one often expects with modern DNNs, performance gains are achieved over competing state-of-the-art methods, suggesting that DNNs may play a critically enabling role in the future of modelling complex flows.

Radko’s recent article (J. Fluid Mech., vol. 805, 2016, pp. 147–170) entitled Thermohaline layering in dynamically and diffusively stable shear flows, is slated to become a seminal reference in the field of fluid dynamics. It proposes an elegant solution to the long-standing question of why thermohaline staircases form in the high-latitude oceans. Equally importantly, it provides a rare and interesting example of how two physical processes that are both strongly stable when considered individually, can trigger a linear instability when they interact.

Recently, Bonnefoy et al. (J. Fluid Mech., vol. 805, 2016, R3) studied the resonant interaction of oblique surface gravity waves in a large $50~\text{m}\times 30~\text{m}\times 5~\text{m}$ wave basin. Their experimental results are in excellent quantitative agreement with predictions of the weakly nonlinear wave theory, and provide additional evidence to the strength of this widely used mathematical formulation. In this article, the reader is introduced to the many facets of the weakly nonlinear theory for surface gravity waves, and to its current and possible future applications, deterministic as well as stochastic.

A pipe conveying fluid is a model problem in fluid–structure interactions and nonlinear dynamics. Several experimental and theoretical studies exist on this problem and very rich nonlinear dynamics have been observed including super- and subcritical instabilities as well as various routes to chaos. Despite all the existing studies, we had not yet seen the fluid inside an oscillating pipe as the pipe undergoes different types of flow-induced instabilities. But the wait is over.

The recent study of Laurence et al. (J. Fluid Mech., vol. 797, 2016, pp. 471–503) develops a new Schlieren-based technique for investigating instabilities and transition in hypersonic boundary layers. This method enables pioneering measurements in a reflected-shock wind tunnel of the characteristics of the second mode of instability on a slender cone, within very short time scales (approximately 1 ms). The visualization technique was shown to resolve the structural evolution of individual wave packets. It was revealed that the disturbance strength concentrates near the wall for high-enthalpy conditions.

In a recent paper, Chu & Prosperetti (J. Fluid Mech., vol. 798, 2016, pp. 787–811) calculate the dissolution of a two-component droplet in an immiscible liquid. Here we discuss in what sense their results go much beyond the Epstein–Plesset solution of a dissolving single-component droplet and hitherto used approximations for dissolving multicomponent droplets. We also highlight the relevance of Chu & Prosperetti’s result for liquid–liquid extraction processes for chemical analysis.

Data-driven low-order modelling has been enjoying rapid advances in fluid mechanics. Arguably, Sirovich (Q. Appl. Maths, vol. XLV, 1987, pp. 561–571) started these developments with snapshot proper orthogonal decomposition, a particularly simple method. The resulting reduced-order models provide valuable insights into flow physics, allow inexpensive explorations of dynamics and operating conditions, and enable model-based control design. A winning argument for proper orthogonal decomposition (POD) is the optimality property, i.e. the guarantee of the least residual for a given number of modes. The price is unpleasant frequency mixing in the modes which complicates their physical interpretation. In contrast, temporal Fourier modes and dynamic mode decomposition (DMD) provide pure frequency dynamics but lose the orthonormality and optimality property of POD. Sieber et al. (J. Fluid Mech., vol. 792, 2016, pp. 798–828) bridge the least residual and pure frequency behaviour with an ingenious interpolation, called spectral proper orthogonal decomposition (SPOD). This article puts the achievement of the TU Berlin authors in perspective, illustrating the potential of SPOD and the challenges ahead.

Few fluid phenomena are as beautiful, fragile and ephemeral as the crown splash that is created by the impact of an object on a liquid. The crown-shaped phenomenon and the physics behind it have mesmerised and intrigued scientists for over a century, and still the scientific world has not yet uncovered all of the secrets of the splash. This is exemplified in a particularly striking manner in Marston et al. (J. Fluid Mech., vol. 794, 2016, pp. 506–529) where a 6 m tall vacuum chamber is employed to study the splash formed upon impact of a sphere onto a deep liquid pool, at both atmospheric and reduced ambient pressures. They shed light into the classical problem of the surface seal and study the buckling of the splash. With an almost magical touch they devise a method to create a splash without the liquid and the sphere ever coming into contact. The images that accompany the paper – taken with state-of-the-art high-speed cameras – are as stunning as the physics that is uncovered in them.

A new paradigm of rheological characterization, oscillatory simple shear with infinite forcing amplitudes, is introduced by Khair (J. Fluid Mech., vol. 791, 2016, R5). This pushes the technique of large-amplitude oscillatory shear (LAOS) to have two extremely large amplitudes (both strain-rate and strain), which we might call XXLAOS. Model-specific analytical predictions are derived for a suspension of nearly spherical rigid particles subject to Brownian rotational diffusion. The work illuminates a new regime of rheological characterization that may serve as a distinct proving ground for constitutive model selection and for probing the flow physics of rheologically complex fluids.

An observed, spectacular and puzzling distinctive feature of wall-bounded flows transitioning to/from turbulence is the large-scale ordered coexistence of laminar and turbulent flow over a wide range of Reynolds numbers. In their article, Chantry et al. (J. Fluid Mech., vol. 791, 2016, R8) circumvent the problem of turbulence modulation in genuine plane Couette flow by replacing no-slip boundary conditions at the walls with effective stress-free conditions constraining the interior part of the flow only. In so doing, they are able to collect relevant information on the laminar–turbulent patterning. The approach is then adapted to plane Poiseuille and pipe flow, giving to it a more universal value. Taking advantage of the stress-free conditions, they derive reduced models efficient at capturing the laminar–turbulent coexistence. Such models would be useful to interpret recent findings in the large-aspect-ratio limit.

Exact coherent structures (ECS), unstable three-dimensional solutions of the Navier–Stokes equations, play a fundamental role in transitional and turbulent wall flows. Dempsey et al. (J. Fluid Mech., vol. 791, 2016, pp. 97–121) demonstrate that at large Reynolds number reduced equations can be derived that simplify the computation and facilitate mechanistic understanding of these solutions. Their analysis shows that ECS in plane Poiseuille flow can be sustained by a novel inner–outer interaction between oblique near-wall Tollmien–Schlichting waves and interior streamwise vortices.

Kahkeshani et al. (J. Fluid Mech., vol. 786, 2016, R3) have studied particle ordering in suspension flow in a rectangular microchannel. Experiments and numerical simulations reveal that inertial focusing and hydrodynamic interactions result in long-lived ‘trains’ of regularly spaced particles. The preferred spacing is frustrated at sufficient particle concentration, an important feature for applications.

Gravity currents are an important buoyancy-driven flow in environmental, geophysical and industrial settings. Turbulence and mixing is commonplace in these flows, but is typically overlooked in theoretical models and predictions. Sher & Woods (J. Fluid Mech., vol. 784, 2015, pp. 130–162) have quantified the velocity and density structure in turbulent gravity currents by combining high-quality experimental data with new theory. Their insights are set to stimulate significant advances in the area.

There have been numerous studies concerning the possibility of self-similar scaling laws in fully developed turbulent shear flows, driven over the past half-century or so by the early seminal work of Townsend (1956, The Structure of Turbulent Shear Flow. Cambridge University Press). His and nearly all subsequent analyses depend crucially on a hypothesis about the nature of the dissipation, ${\it\epsilon}$, of turbulence kinetic energy, $k$. It has usually been assumed (sometimes implicitly) that this is governed by the famous Kolmogorov relation ${\it\epsilon}=C_{{\it\epsilon}}k^{3/2}/L$, where $L$ is a length scale of the energy-containing eddies and $C_{{\it\epsilon}}$ is a constant. The paper by Dairay et al. (J. Fluid Mech. vol. 781, 2015, pp. 166–195) demonstrates, however, that, in the specific context of an axisymmetric wake, there can be regions where ${\it\epsilon}$ has a different behaviour, characterised by a $C_{{\it\epsilon}}$ that is not constant but depends on a varying local Reynolds number (despite the existence of a $-5/3$ region in the spectra). This leads to fundamentally different scaling laws for the wake.

The paper by Dritschel et al. (J. Fluid Mech., vol. 783, 2015, pp. 1–22) describes the long-time behaviour of inviscid two-dimensional fluid dynamics on the surface of a sphere. At issue is whether the flow settles down to an equilibrium or whether, for generic (random) initial conditions, the long-time solution is periodic, quasi-periodic or chaotic. While it might be surprising that this issue is not settled in the literature, it is important to keep in mind that the Euler equations form a dissipationless Hamiltonian system, hence the set of equations only redistributes the initial vorticity, generating smaller and smaller scales, while keeping kinetic energy, angular impulse and an infinite family of vorticity moments (Casimirs) intact. While special solutions that never settle down to an equilibrium state can be constructed using point vortices, vortex patches and other distributions, the fate of random initial conditions is a trickier problem. Previous statistical theories indicate that the long-time state should be a stationary large-scale distribution of vorticity. By carrying out careful numerical simulations using two different methods, the authors make a compelling case that the generic long-time state resembles a large-scale oscillating quadrupolar vorticity field, surrounded by persistent small-scale vortices. While numerical simulations can never conclusively settle this issue, the results might help guide future theories that seek to prove the existence of such an interesting dynamical long-time state.

In a recent study, Lawson & Dawson (J. Fluid Mech., vol. 780, 2015, pp. 60–98) present experimental results on the fine-scale structure of turbulence, which are obtained with a novel variant of particle image velocimetry, to elucidate the relation between the small-scale structure, dynamics and statistics of turbulence. The results are carefully validated against direct numerical simulation data. Their extensive study focuses on the mean structure of the velocity gradient and the pressure Hessian fields for various small-scale flow topologies. It thereby reveals the dynamical impact of turbulent strain and vorticity structures on the velocity gradient statistics through non-local interactions, and points out ways to improve low-dimensional closure models for the dynamics of small-scale turbulence.

Despite studying the same subject – electrically induced flow – the fields of electrokinetics (EK) and electrohydrodynamics (EHD) have developed separately, for different types of fluids and interfaces. In colloids or porous media, EK phenomena derive from the electro-osmotic slip of a liquid electrolyte across the neutral electric double layer on a solid surface. On the other hand, EHD phenomena involve poorly conducting neutral fluids and solids, whose interfaces acquire net charge in response to electric fields. Over the past decade, combined theories of EK and EHD have emerged for fluid/solid interfaces, and now Schnitzer & Yariv (J. Fluid Mech., vol. 773, 2015, pp. 1–33) have taken a major step towards unifying EK and EHD for fluid/fluid interfaces. Following previous work by Baygents and Saville, they derive the classical Taylor–Melcher model of droplet EHD as the large-field thin-double-layer limit of the electrokinetic equations, thus elucidating the ubiquitous ‘leaky dielectric’ approximation. Future work could consider the secondary electro-osmotic flow and electrophoretic motion of the drop (neglected here as small perturbations) and allow for more general EK models.

Bubble interaction with turbulence has a number of applications in engineering processes and nature. The complex interplay between the vortical structures present in a turbulent flow and the bubbles drives their deformation dynamics, which may lead to bubble rupture under the appropriate conditions. Such a process includes nonlinear interaction among the turbulent eddies and between the eddies and the bubbles. Thus, the coupled evolution of a single vortex ring with a bubble represents an idealized scenario that can provide a framework to shed light on understanding such a common and complex mechanism. Jha & Govardhan (J. Fluid Mech., vol. 773, 2015, pp. 460–497) have performed elegant experiments generating controlled vortex rings and injecting bubbles of known volume. They have reported interesting results on the elongation process of the bubble and its impact on vortex dynamics.