We numerically investigate the swimming mechanism of a dolphin by focusing on the hierarchy of vortices in its turbulent wake. Using direct numerical simulations of a self-propelled dolphin and scale decomposition of the flow, we show that the caudal fin generates large vortex rings that contribute most of propulsion, whereas smaller vortices are created through the energy cascade but contribute little to propulsion. We also show that this mechanism remains robust regardless of the Reynolds number.

The purpose of the work is to understand the coupled influence of fluid and arterial wall viscoelasticity on wave dynamics, flow impedance, and energy dissipation in a compliant artery. Most theoretical models simplify this coupling by assuming Newtonian flow or purely elastic vessel walls. This study presents a comprehensive model for detailed profiling of vascular mechanics that utilizes physiological arterial parameters to assess the frequency-dependent impedance and energy dissipation behavior within the fluid-structure model.

Blood flow in microcirculation exhibits complex, non-Newtonian behavior arising from red blood cell (RBC) migration and the formation of a near-wall cell-free layer (CFL), which remain challenging to capture with continuum models. Here, we introduce a modified suspension-balance model with a lift-force closure that bridges cell-level microrheology to continuum transport. The model quantitatively predicts CFL formation, hematocrit redistribution, and velocity blunting, while recovering key physiological signatures. This work provides an efficient continuum framework for capturing heterogeneous transport in concentrated deformable particle suspensions under confinement.

Building on prior studies of obstacle–detonation interactions, this work uses two-dimensional detailed-chemistry simulations to examine how obstacle configurations affect detonation attenuation and flame acceleration. Increased dispersion enhances attenuation by fragmenting the front and leads to distinct reinitiation modes compared to concentrated obstacles. With extended obstacle sections, propagation transitions from quasi-detonation to choking, governed by a critical blockage ratio that decreases with increasing cell width. A scaling is proposed to predict regime transitions and capture the balance between shock attenuation and flame acceleration.

Oblique detonation waves are pivotal for hypersonic propulsion, but their stationary characteristics are rarely studied under controlled reaction rate distributions. Two-dimensional Euler simulations coupled with a two-step kinetic model are employed, and the effects of activation energy and reaction rate constant are isolated while induction and exothermic zone lengths are fixed. It is demonstrated that higher activation energy delays initiation and stabilizes oblique detonation, while unsteady upstream motion via thermal choking is triggered when a critical reaction rate is exceeded. A new stability criterion for oblique detonation is provided by these results.

Turbulence in viscoelastic media is typically associated with polymeric fluids, where elasticity drives chaotic flows even at low Reynolds numbers. Here, we demonstrate that strongly coupled plasmas, despite lacking molecular chains, exhibit intermittent viscoelastic turbulence arising from long-range inter-particle interactions. Using large-scale three-dimensional molecular dynamics simulations, we uncover a cascade of kinetic and elastic energy with steeper power-law scaling than Kolmogorov $k^{-5/3}$ and intermittency. These results establish dusty plasmas as a microscopic platform for exploring viscoelastic turbulence beyond conventional fluid systems.

Traditional heat transfer models for shear-thinning fluids often lack the physical depth to fully capture their complex turbulent transport mechanisms. This study introduces a robust phenomenological model for power-law fluids in pipe flow, integrating Kolmogorov’s theory into an extended Prandtl-Taylor analogy. Furthermore, the introduction of a flow-independent Power-Law Prandtl number decouples the fluid’s intrinsic thermal properties from flow kinematics. The resulting correlation offers superior predictive accuracy and deeper physical insight.

Viscoelastic flows through narrow, nonuniform geometries are common in engineering and biological systems, yet the pressure drop behavior of such fluids remains poorly understood. We develop a theoretical model for the flow of an Oldroyd-B fluid in slowly varying constrictions, deriving closed-form expressions for the elastic stresses and pressure drop valid for all Deborah numbers in the ultra-dilute limit. Our theory is in excellent agreement with numerical simulations and reveals key differences between constrictions and contractions, including a plateau in the pressure drop at high Deborah numbers and a significantly shorter relaxation length in the exit channel of the constriction.

Viscoelastic natural convection differs from its purely Newtonian analogue due to polymer-induced elastic stresses and shear-dependent viscosity. When coupled to buoyancy-driven flow, these viscoelastic effects modify velocity and thermal boundary layers. We examine the role of cavity aspect ratio in governing the spatial distribution of elastic stresses. Coupled effects of cavity aspect ratio and viscoelasticity determine whether polymer forces enhance or suppress convection, thus affecting local and overall heat transfer performance. These insights offer guidance for controlling heat transfer under low-inertia, with implications for thermal management and process design in polymeric flows.

When bubbles burst at the surface, they eject droplets through the formation of a fast upwards jet. We study how this jet is modified when bubbles are grouped together in rafts at the surface, and find that the presence of these neighbors strongly reduces the size of the ejected droplets and increases their upwards velocity. This effect significantly broadens the drop size distribution of the whole raft and shifts the peak towards smaller sizes.

Electric fields strongly elongate ionic liquid droplets in flight, but have little effect on their impact dynamics. Experiments show that despite pronounced deformation induced by Maxwell stresses, the splashing threshold and maximum spreading factor remain nearly unchanged, revealing that high viscosity suppresses electrohydrodynamic coupling during impact.

Antibubbles are the structural inverse of soap bubbles: they consist of a liquid core enclosed by a thin quasi-spherical gas shell, immersed in a liquid medium. Producing multilayer antibubbles, i.e. antibubbles enclosed by multiple soap/air films, has been a challenge in the past years, as it requires a delicate balance between surface tension and inertia. In this paper, we investigate a method that uses one or more soap films and a soapy liquid droplet to generate multilayer antibubbles. We also identify the optimal parameters for forming single-layer and multilayer antibubbles across three different viscosities.

Outward-diffusing vorticity fields form around particles and droplets in time-periodic fluid motions. As a result, the time-dependent shear gradients in the fluid and at the particle surface are typically greater than those of the classical steady-state Stokes velocity profile. This leads to an additional viscous force, the Basset–Boussinesq history force (BBH), which depends on the past motion of the particle that created the vortices. An experiment with particles in a shaken fluid is proposed to measure the parameter dependence of the BBH, and parameter ranges are also predicted in which the BBH becomes comparable to or stronger than classical Stokes friction.

While the coalescence of similarly-sized air bubbles in water is known to eject satellite bubbles, a complete model has remained elusive. Suspending unconstrained air bubbles using magnetic levitation, this study combines experiments and simulations to reveal how initial size ratios dictate the outcome, including twin satellites for equal-sized precursors. A timing model shows satellite production is governed by the coincidence of converging capillary waves and the retraction of the coalescing bubbles’ poles. Analysis of the capillary waves offers insight into why similarly-sized drops do not eject satellites in the same manner as bubbles.

We investigate the breakup dynamics of an inviscid liquid bridge under slow drainage. The transition from symmetric to asymmetric breakup occurs at a length-to-radius ratio of 4.1, corresponding to a shift from even-mode to odd-mode dominance. Contrary to previous experimental conclusions, we show that satellite droplet momentum originates from capillary impulses beginning at the flattening moment before the first pinch-off. A new scaling law is proposed and validated.

A droplet adopts a complex shape in a spring and can create significant spring compression, potentially functioning as a capillary weight-lifting system. By tuning the ratio between the pitch of the soft spring and the droplet size reveals a range of distinct droplet flow regimes, in which the vertical velocity is directly linked to the droplet’s rotational motion. Active control of the spring’s extension and compression demonstrates how both the static and dynamic states of the droplet can be controlled.

The total energy spectrum exhibits a Kolmogorov-like scaling, consistent with the conservation of total energy in the system. However, the kinetic and magnetic energy spectra often diverge from the −5/3 scaling. In this paper, we show that this divergence arises from energy transfer between the velocity and magnetic fields, either from velocity to magnetic field or vice versa. Our extensive numerical simulations therefore demonstrate Kolmogorov-like phenomenology for isotropic MHD turbulence.

For isotropic magnetohydrodynamic (MHD) turbulence, we employ high-resolution numerical simulations and compute the energy spectra and fluxes, as well as the structure functions, of Elsässer variables. While the competing spectral indices 5/3 and 3/2 are too close, the 5/3 index still provides a better fit to the energy spectra. More importantly, the structure functions strongly support the Kolmogorov-like phenomenology. Additionally, the energy fluxes in imbalanced MHD are consistent with the predictions of the Kolmogorov-like model. The figure shows normalized cross helicity of 0.65.

We investigate the dynamics of a leaky dielectric droplet subjected to a superposed alternating and constant electric field using analytical small deformation theory and phase-field simulations. The mean and amplitude of droplet deformation depend on the mixing ratio (MR) and frequency of the superposed electric field. Results show that deformation amplitude under a superposed field is larger than in a purely alternating electric field. When the root-mean-square value of the superposed field exceeds that of the pure AC field, the mean deformation increases with increasing MR. The variation of the nondimensional oscillating interfacial kinetic energy with MR is also explored.

Spatially localized flow perturbations that maximize perturbation-energy amplification can reveal underlying drivers of flow instability. In this paper, we show that such spatially localized perturbations can be found by solving a particular sparse optimization problem and propose an efficient iterative method for doing so. Our approach is demonstrated on a subcritical plane Poiseuille flow, wherein we find that a subset of the perturbations identified by our method yield a comparable degree of energy amplification as their global counterparts.

We revisit Squire’s theorem, a fundamental concept in hydrodynamic stability theory, but only valid for temporal modes, and extend it to spatiotemporal modes. This extension reveals a new class of subcritical oblique modes in which three-dimensional disturbances can become unstable at lower Reynolds numbers than their two-dimensional equivalents. While individual modes are unphysical, their superposition within a framework such as Briggs’ theory yields finite-energy perturbations. The theory provides a framework to describe spatially growing oblique structures, such as those observed in transitional shear flows.

Deep reinforcement learning (DRL) for active flow control in turbulent regimes has been challenging due to prohibitive computational costs. This study overcomes this barrier by integrating a GPU-accelerated lattice Boltzmann solver with a two-stage exploration strategy, making DRL feasible for turbulent flow applications. For the canonical case of flow past a circular cylinder, the DRL-guided controller reduces drag by 55% and lift fluctuation by 26%, through significantly modifying the wake dynamics and turbulent features. Follow-up tests demonstrate that online-smoothed actuation performs as effectively as high-frequency inputs, offering practical advantages for real-world implementation.

Under transient conditions, the evolution of flow in the rotor-stator cavity of an aero-engine differs markedly from the steady state. Using theory together with three-dimensional direct numerical simulations, we capture the nonlinearity and unsteady behavior in the transient evolution of rotating cavity flows. For a laminar enclosed rotor-stator cavity, the transient process primarily generates and dissipates circular waves whereas a turbulent one features small-scale fragmented vortical structures. This study elucidates three-dimensional transient evolution and flow structures in rotating cavities, providing a foundation for further investigations of transient rotating cavity flows.

We investigate the bypass transition of a flat-plate boundary layer over a three-dimensional irregular rough surface characterized by isotropic protrusions and a favorable-adverse pressure gradient. By positioning the roughness upstream of or adjacent to the separation point and introducing inlet free-stream turbulence of varying intensities and fundamental frequencies, the combined effects of pressure gradients, three-dimensional roughness, and free-stream turbulence on bypass transition and disturbance amplification are examined. Notably, when the rough surface is upstream of the separation point, intense low-frequency free-stream turbulence can excite novel elongated resonant modes.

Experiments and numerical simulations of flow near a moving contact line are presented for dynamic contact angles exceeding 90°. High-resolution PIV and interface tracking deliver simultaneous measurements of velocity fields, interface shapes, and interfacial speeds across low to moderate Reynolds numbers. A central finding is the pronounced slowing down of fluid particles along the interface as they approach the contact line, providing direct experimental evidence toward resolving the classical singularity. Complementary VOF simulations with a variable-slip model reproduce the observations and demonstrate that such simulations can resolve detailed flow fields with experimental fidelity.

Chemical reactions in liquid solutions can generate self-sustained Marangoni flows driven by concentration gradients of reacting species. A nonequilibrium regime emerges involving the interplay of hydrodynamics and chemistry. Here, we show how differential diffusion shapes complex spatiotemporal dynamics by driving more extrema (2 or more) in the surface tension profiles and more convection rolls/vortices in the bulk. A striking example is the occurrence of spatial oscillations of surface tension in the strongly coupled regime. As a response to the formation of an extremum, we compute the delay time required for a roll to emerge from the continuity and tangential stress balance equations.

Metallic coatings play a vital role in protecting metal surfaces from corrosion, but achieving uniform, defect-free layers remain a major challenge due to undulation instabilities. This work investigates a novel control strategy for liquid films on moving substrates using coordinated gas jets and electromagnetic actuators. By extending integral film models and embedding them in a reinforcement-learning framework, a proximal policy optimization (PPO) algorithm learns to actively suppress instabilities. The resulting control exploits a new physical mechanism: gas jets damp wave crests while electromagnetic forces lift troughs, leading to smoother coatings.

An instability may arise when a hot viscous fluid enters a thin gap and cools through heat transfer to a colder surrounding environment. In this paper, we investigate this mechanism in the small Biot number regime, where cooling through the plates is weak but acts over sufficiently long times that the temperature becomes nearly uniform across the gap. From numerical simulations we show that fingering instabilities emerge in response to small inlet perturbations within a range of Péclet numbers and viscosity contrasts. From linear stability analysis we find the dispersion relation and quantify how the fastest growth rate and corresponding wavenumber depend on the global parameters.

We propose a transformer-based reinforcement learning framework to learn an effective control strategy for regulating aerodynamic lift in arbitrary gust sequences via pitch control, showing that this approach can be successfully applied to disturbed flows. By using two machine learning techniques, pretraining and transfer learning, we also show that the approach can extend control policies to regimes far from the training regimes, such as arbitrarily long gust sequences. We also investigate the impact of pivot point location and show that quarter-chord pitching control can achieve superior lift regulation with substantially less control effort compared to mid-chord pitching control.

We perform a comprehensive numerical study of standard, inverted, and wall-mounted flag models to reveal how flag-induced dynamics and vortex organization control thermal transport. The results identify distinct vortex-generation mechanisms for each configuration and map their high-efficiency regimes in the parameter space of bending stiffness and Reynolds number. These findings clarify the thermo-hydraulic performance limits of flexible flags and provide guidance for designing efficient passive heat transfer enhancers.

This study investigates shear-driven flow over a microstructured surface of zero-thickness ridges separating rectangular grooves infused with a relatively low-viscosity lubricant. Asymptotic analysis in that limit reveals that viscous resistance is dominated by a boundary layer about the ridge tips that is exponentially small in the viscosity ratio $\mu \ll 1$, resulting in a surprising ${\mu }^{-1/2}$ scaling for the effective slip length.

When a cylindrical droplet containing a solid particle rod interacts with a planar shock wave, a complex evolution of its internal wave structure ensues. We simulate the interaction numerically, and the ray analysis method is specifically adopted to analyze the evolution of the wave structure in detail. The results show that the particle rod separates negative pressure regions more distinctly, raises the droplet’s minimum pressure, leads to cavitation at high shock wave intensity, and that particle eccentricity influences wave structure and cavitation. These findings are expected to contribute to advancements in fuel atomization and biomedical applications.

From previous studies on rigid isotropic particles, one might expect that heavy particles would be centrifuged out of vortices. However, during experimental runs, we observed thin, heavy, flexible discs trapped in stable orbits near a vortex core. By reconstructing their three-dimensional shape and motion, we show how deformability and anisotropy alter the classical force balance. The results raise new questions about how form and flexibility impact transport in vortical flows.

Unlike-doublet impinging jets are widely used in hypergolic liquid rocket engines, but the role of inertia disparity in shaping atomization and mixing has remained unclear. Using high-fidelity Volume of Fluid simulations with intra-liquid species transport, we show that increasing inertia disparity narrows the spray, shortens liquid-sheet breakup, and reduces mixing efficiency. At high disparity, the jets exhibit central-axis collapse and mutual penetration, producing a distinctive flow-rate distribution. Flow topology analysis links these behaviors to Kelvin–Helmholtz type shear instabilities that generate vortices and drive liquid sheet collapse.

We show that the incompressible Large eddy simulations of the condensation fronts (also referred to as bubbly shocks or condensation shocks) in partial cavitation within a three-dimensional Venturi agree well with the experiments. The condensation front is fundamentally different from traditional shock waves. The density variations due to evaporation and condensation of cavitation, rather than fluid compressibility, govern its formation and propagation. Hence, a compressible solver is unnecessary for simulating condensation fronts. These findings offer a new understanding of the shedding mechanism of partial cavitation.

The relaxation of a buckled elastic sheet in a fluid involves a balance between bending, inertia, and hydrodynamic forces. We show that a minimal inviscid model predicts both the oscillation frequency about the stable mode and the growth rate of unstable modes, in agreement with more general viscous simulations. The framework also captures the temporal transition from unstable to stable configurations.

Microswimmers under weak confinement exhibit flow fields that are highly dependent on the spatial arrangement of their propulsion and drag forces, as well as their geometry. These flow fields can be approximated by placing Stokeslets and source dipoles at proper positions of the swimmer. We observe versatile swimming trajectories, such as centerline sliding and amplified oscillations, depending on the relative strengths of the Stokeslets and source dipoles.

We revisit a largely overlooked theoretical model from Belen’kii and Fradkin (1965) and show that it captures many key features of non-Boussinesq Rayleigh-Taylor mixing observed in modern studies. By extending the analysis of this pioneering study, we uncover new physical insight and develop a practical, analytically tractable representation. Calibrated with DNS data, this work bridges classical theory and modern turbulence modeling, offering a compact tool for understanding and predicting variable-density turbulent flows.

The transfer of energy and other conserved quantities across scales is a central aspect of out-of-equilibrium systems such as turbulent hydrodynamic flows. Despite its role in the few predictive theories that exist, a dynamical understanding of what determines said transfer (and its direction in scale) has yet to be established. In this study, we investigate how the dynamics of complex Fourier velocity phases influence the flux of conserved quantities in simplified (“shell”) models of hydrodynamic turbulence. We develop an analytically tractable model for the statistics of the phases, validate the model using simulations, and use the model to predict properties of the energy cascade.

We model turbulence using coherent vortices distributed within a multiscale statistical framework, termed woven turbulence, which naturally captures key turbulence features. Based on explicitly controllable vortices, we find that the scale-independent hierarchical vortex density corresponds to the −5/3 law of the energy spectrum, while the Reynolds-number-independent total vortex density corresponds to the intermittent scaling of the structure function. Woven turbulence also serves as a fast turbulence synthesis method, requiring only the Taylor-Reynolds number as input and exhibiting extremely low computational cost comparable to the random Fourier modes method.

Transition to turbulence in wall-bounded shear flows is often explained through the self-sustaining process proposed by Waleffe, where streaks, streamwise vortices, and streak waviness interact nonlinearly. Using direct numerical simulations of plane Couette–Poiseuille flow near transition, we examine how streak waviness relates to the underlying roll structures. The results show that, once the rolls reach sufficient amplitude, the waviness of the streaks scales quadratically with the rolls, clarifying a key nonlinear step of the self-sustaining process in this asymmetric shear flow.

Wall-bounded turbulence exhibits coherent vortical structures whose geometry and multiscale organization remain difficult to capture in physics-based models. We construct turbulence fields as ensembles of hierarchically organized hairpin vortex packets with height-dependent core size. The model quantitatively reproduces statistical and structural features of high-Reynolds-number turbulence, including both attached and detached motions. It further elucidates how vortex geometry and packet organization govern these features, while enabling rapid initialization of fully developed turbulence at substantially reduced cost.

A new method is proposed to detect rare events in a shear flow. Using Live Optical Flow Velocimetry (L-OFV), it becomes possible to monitor a flow over extended periods (hours or even days) based on quantitative measurements and predefined criteria. Once these criteria are met (typically large standard-deviation excursions in velocity probes), the time history of the 2D velocity field is recorded before and after the event. After 1.5 hours of live monitoring of a backward-facing-step flow, a single extreme event, deep in the velocity-distribution tails, was found. Analysis of the time-resolved 2D velocity fields revealed a strong upstream-directed jet burst piercing the recirculation region.

Rectangular exhaust nozzles are an attractive option in the design of high-speed propulsion systems. This study investigates the effects of V- shaped trailing edges (VTEs), a feature that improves stealth performance, on the flow and noise radiation of a hot over-expanded rectangular jet. Results show that the VTEs can effectively suppress the screech tone and overall sound pressure levels in the upstream and downstream directions. This study also demonstrates that the energy redistribution during wave interactions is modulated by the VTEs, providing an inherent explanation for the screech reduction.

The second-order Lagrangian velocity structure function in turbulence is a fundamental quantity for which clear inertial range scaling has been much more elusive than corresponding Eulerian measures. In this work direct numerical simulation at high Reynolds number is used to better understand the question of asymptotic constancy of the supposed scaling constant through effects of the acceleration autocorrelation function. A spatial-temporal decomposition of the Lagrangian velocity increment exposes strong but incomplete cancellation between convective and local contributions, with rapid approach of particle displacements towards inertial range values having an important role.

We introduce a momentum decomposition framework to analyze the pressure field. It establishes a generic relationship between the mean pressure and flow statistics for turbulent flow, manifesting as fundamental mechanisms of pressure-gradient contributions in Cartesian coordinates involving mean flow accelerations, Reynolds stresses, and viscous stresses. With a focus on bluff body flows, this framework is validated in both laminar and turbulent regimes, providing a physical basis for flow analysis and control.

Counter-gradient transport in stably stratified shear turbulence remains poorly understood, particularly from a structural perspective. Using direct numerical simulations combined with the clustering method, this study identifies and characterizes coherent structures responsible for counter-gradient transport of heat and momentum. We find that such transport is dominated by structures larger than the Corrsin scale and primarily organized as paired Q1–Q3 events. Distinct physical mechanisms are revealed, with heat transport arising from both vortex-induced rotation and fluid parcel interactions, while momentum transport is governed solely by vortex-induced rotation.

Vegetation canopies in open-channel flows often experience time-dependent drag that reshapes turbulence near the canopy top. Using large-eddy simulation with a variable-drag model, we show that oscillatory drag reorganizes coherent vortices and shifts turbulent kinetic energy activity from the canopy-top shear layer into the canopy interior. The framework provides an efficient way to isolate how prescribed canopy drag affects turbulence structure and energy transport in large-domain simulations.

Laser-sustained plasma (LSP) is a novel light source for bright-field wafer defect inspection in chip manufacturing, but the inherent spatiotemporal instabilities severely limit performance. Through experiments and multiphysics modeling, this work reveals that these periodic fluctuations originate from buoyancy-driven vortex ring dynamics. A generalized scaling law incorporating the gas density ratio is established for accurate frequency prediction, demonstrating that the Prandtl and Péclet numbers govern the oscillation threshold and patterns. These findings provide a mechanistic framework for the development of stable LSP light sources.

Horizontally driven shallow electrolyte flows are widely employed laboratory analogs of oceanic and two-dimensional flows. Although previous studies investigated the presence of three-dimensional circulations within the bulk of turbulent shallow flows, relatively little attention was paid to whether the fluid layer thickness itself remains spatiotemporally uniform. In this study, we report experimental measurements of free-surface deformations in shallow flows. For certain Reynolds number and fluid layer height combinations that characterize the flow, we show that the free surface undergoes significant deformation, thereby rendering an otherwise shallow flow geometrically three-dimensional.

What bridges convection and stratified turbulence? Using direct numerical simulations, we reveal that in highly turbulent stratified inclined duct (SID) flow, these two phenomena can coexist within a single canonical system. At sufficiently large Reynolds number, SID undergoes a transition to the ultimate regime of turbulent convection, marked by the enhanced transport scaling Nu~Ra${}^{1/2}$. The transition coincides with the onset of turbulent boundary layers and is subcritical and hysteretic, as expected for the non-normal-nonlinear route to turbulence in shear flows.

We examine an ensemble of numerically simulated breaking surface gravity waves and show that the inception of breaking can be characterized by the maximum local interface angle. In our simulations that include surface tension effects, we find that breaking inception occurs when the local interface angle exceeds 60°; a value twice that reported in previous studies without surface tension. We explore this result in the context of the commonly utilized kinematic inception parameter and show that these two indicators of breaking inception are related through the relative flux of energy into the wave crest.

The Fully Dispersive Internal Wave (FDIW) equations, related on the two interface fluctuations in three-layer fluid, is derived from the stratified Euler equations using multiscale asymptotic expansion valid up to second-order nonlinearity. It can accommodate both mode-1 and mode-2 nonlinear internal waves and their transformations without further assumptions like the comparable phase speed of two modes needed in the well-known coupled Korteweg-de Vries (KdV) system, due to capturing all wavelengths without long-wave assumptions. The results indicate that coupled KdV equations should be used in the ocean with great caution as the difference between the KdV and FDIW equations is shown.

Surface-swimming organisms generate a rich variety of wave patterns. By studying the wakes produced by two juvenile snakes, we show that their surface waves strongly deviate from classical predictions for uniform straight-line motion. A simple slaloming-source model reproduces these patterns and shows they emerge from the superposition of translating, pulsating wave sources. Overall, our results provide a new framework for understanding capillary-gravity waves generated by non-uniform motion and enable the construction of a phase diagram describing these regimes.

Numerical simulations of sheared particle suspensions often require large domains to avoid wall effects. We implement Lees–Edwards boundary conditions in particle-resolved Lattice Boltzmann Method–Discrete Element Method (LBM–DEM) simulations to model homogeneous shear flows without physical boundaries. The method enables computationally efficient simulations while resolving particle-scale hydrodynamic interactions. It provides a practical tool for studying suspension rheology quantitatively by capturing how particles interact with the surrounding fluid and with each other across a range of concentrations.

Sparse-sensing reconstruction of turbulent flows remains challenging due to high sensor requirements and poor fidelity near solid interfaces. VIVALDy, a machine learning framework, addresses these limitations through a hybrid β-Variational Autoencoder-Generative Adversarial Network (β-VAE-GAN) and a bidirectional transformer to compress flow fields into a compact latent space and predict temporal evolution from minimal inputs. Masked convolutions are used to enhance fidelity at solid boundaries. Validated against experimental data for a moving cylinder, the framework reconstructs diverse fluid-structure interaction regimes using only cylinder displacement.

Rayleigh–Bénard convection is a canonical system for studying turbulent heat transport, yet controlling it at high Rayleigh numbers remains computationally prohibitive. Here, we combine data-driven manifold dynamics with reinforcement learning to construct a reduced-order environment that enables efficient training of control policies. When deployed in direct numerical simulations, the learned strategies achieve up to 23% reduction in heat transfer by stabilizing near-wall dynamics and suppressing plume emission. This work establishes a scalable and physically interpretable route to controlling high-dimensional turbulent flows.

The Lattice Boltzmann Method (LBM) exploits its nearly incompressible nature to relate local density to pressure, avoiding iterative Poisson solvers. However, this pressure–density coupling makes robust extension of LBM to the Two-Fluid equations particularly challenging. In this work, we propose two complementary approaches to address this problem: a mixture model for dilute suspensions prioritizing computational efficiency, and a well-balanced formulation employing a pressure-free LBM with an explicit Poisson solver for maximum accuracy. Both methods are validated on standard benchmarks and isotropic turbulent flows, demonstrating accuracy and robustness across challenging flow regimes.

Advective flows are often characterized by wavepackets. Hilbert proper orthogonal decomposition (HPOD) extracts these coherent structures from flow field data by exploiting their representation as modulated traveling waves. HPOD is a complex valued extension of proper orthogonal decomposition, where the analytic signal is obtained via a Hilbert transform applied either in time (conventional HPOD) or along the advection direction (space-only HPOD). Both HPOD formulations yield equivalent decompositions for advecting wavepackets. The resulting modes exhibit amplitude and frequency modulation in space and time, enabling instantaneous, local flow analysis.

The decay of turbulent kinetic energy is strongly influenced by large-scale coherent structures. Using a synthetic-jet-driven turbulence facility and the Proper Orthogonal Decomposition (POD) method, we show that slowly decaying modes persistent across repeated experiments bias the observed decay rates. Removing these modes reveals a stochastic turbulence field with decay consistent with classical theory. This framework helps resolve discrepancies in reported decay rates and distinguishes whether variations arise from specific coherent modes or changes in the underlying stochastic turbulence.

Accurate reconstruction of near-wall turbulence from limited wallmeasurements remains a central challenge in non-intrusive flow sensing, especially because conventional learning approaches often sacrifice small-scale fidelity. Building on recent data-driven advances, this study shows that a spectrally informed composite loss can markedly outperform standard mean-squared-error training for reconstructing velocity fluctuations from wall-shear and pressure signals. The method improves statistical and spectral accuracy, preserves fine-scale energy, and remains robust under noisy and coarse inputs, strengthening the case for practical turbulence sensing with neural networks.

Optical images of transparent objects depend in a complicated way on their three-dimensional properties, which made it difficult to simulate such images accurately. Using ray tracing with calibrated illumination, we simulated with high fidelity images of drops with complex shapes, and images of pressure waves inside drops. The simulated images can be used to visualize, validate, and refine fluid dynamics models. They can also be used to determine multiple three-dimensional properties from experimental images.