Choosing the mounting position of an aortic prosthesis—intra- or supra-annular—remains debated, as clinical comparisons rarely isolate hemodynamic effects of valve replacement procedures. We perform fluid-structure interaction simulations of a patient-specific left heart, testing the same bioprosthetic valve in both configurations on the same patient, rationalizing mounting and valve size effects. Supra-annular implantation consistently lowers transvalvular pressure gradients, increases orifice area, and reduces shear and hemolysis risk (see figure). These results provide controlled evidence to guide implantation strategy and device selection in cases of patient-prosthesis mismatch risk.

Cells and other soft particles are often forced to flow in confined geometries in both laboratory and natural environments, where the elastic deformation induces an additional drag and pressure drop across the particle. We start by measuring the pressure drop across a single spherical hydrogel particle as it flows in a microfluidic comparator. This pressure is found to depend on the amount of confinement, elastic modulus, fluid viscosity and velocity. A model for the force balance on the particle is then proposed, by incorporating the above ingredients and relying on simulations of bead geometry and lubrication flow considerations.

Extreme Lagrangian acceleration in turbulence is often attributed to particle trapping in coherent vortex structures. Here, we show that shell models, despite lacking vortex filaments, reproduce the extreme intermittent fluctuations of Lagrangian acceleration seen in real flows. Within the multifractal framework, we accurately predict acceleration moments and full probability distribution functions (PDFs) across a wide range of Reynolds numbers. This shows extreme Lagrangian fluctuations can arise from inertial-range dynamics alone, supporting the universality of multifractal statistics and highlighting shell models as effective tools to capture key features of turbulence.

Macroscopic pilot-wave systems, such as bouncing droplets, have long provided analogies to quantum-like wave–particle duality. We introduce a new platform: a particle oscillating in a density-stratified fluid, which couples to its self-generated internal gravity waves. Using theory and simulations, we show that a Doppler force drives spontaneous horizontal motion, while wave reflections from boundaries create a Casimir-like potential that constrains long-term dynamics. These results establish the ludion as a three-dimensional hydrodynamic pilot-wave system, opening new avenues for exploring macroscopic wave–particle phenomena.

Flow visualization using reflective flakes presents a puzzle: Why do experimental patterns appear steady and reproducible when orientations of individual flakes follow chaotic paths on the unit sphere, even in steady flows? We introduce a probabilistic framework that treats flake orientation as a probability density field rather than tracking individual particle trajectories. The key insight reveals that small random motions, typically ignored in deterministic approaches, are requisite for eliminating initial condition dependence and achieving the steady patterns observed in experiments. The theory successfully predicted asymmetric flow patterns that deterministic approaches couldn’t explain.

Shrimp thrive in a wide range of climates, from the tropics to polar waters and inland freshwater. Our research shows how their swimming style has evolved to be highly resilient to environmentally driven changes in water properties. Our findings highlight the ability of the large biomass of shrimp-like crustaceans to adapt to vastly different water temperatures and viscosities. It also shows the potential for crustacean-inspired underwater vehicles; such drones could navigate environments with variable viscosity, such as phytoplankton blooms or oil spills, without requiring modifications to their control algorithms.

Active fluids can influence the behavior of passive particles, with sedimentation being an important such process. We investigate how the velocity of a sphere varies when settling in a square tube filled with active nematic fluids. While the direct active forces exerted on the sphere are weak in our study, activity can still significantly modify settling velocity by altering the flow structure and nematic field. The results manifest mechanisms of activity-induced shear thinning and thickening for various anchoring conditions and activity. As activity increases, transitions between flow patterns further influence settling, with different effects observed in extensile and contractile fluids.

Oscillatory flows in porous environments arise in both biological and technological systems, yet their time-averaged steady streaming has been largely overlooked. Here we analyze steady streaming in slender channels with porous interiors using a homogenized model with Darcy resistance. We find that porous media not only attenuate streaming compared to unobstructed channels but also alter its structure. These results provide new insight into fluid transport in oscillatory flows through porous environments.

Sessile ciliates feed by generating ciliary currents rather than by locomotion. While the optimal ciliary stroke in uniform nutrient fields is known, natural habitats are patchy and gradient-rich. We show that, for a stationary cell, a linear nutrient gradient leaves the purely diffusive uptake unchanged; however, when cells generate ciliary flows that align with the gradient, intake is enhanced, following a square-root scaling law with time and Péclet number. Thus, cells using simple flow-generation strategies can exploit environmental asymmetry to optimize resource acquisition.

In the microcirculation, highly deformable red blood cells flow through vessels of comparable size. Many of these vessels are compliant, but the impact of their deformation on the cell dynamics remains largely unexplored. Motivated by this, a computational study using a three-dimensional fully coupled fluid-structure interaction model is presented on the flow of deformable capsules in a compliant, inflating tube. The tube’s inflation is found to significantly alter the capsules’ transient deformation and velocity. Additionally, interactions between the capsule and tube create flow rate oscillations that are absent in a rigid tube under similar flow conditions.

In this study, a comprehensive Darcy-type law for viscoplastic fluids is proposed. The two extreme limits of a yield-stress fluid flow in a porous medium are addressed individually and then are combined to propose a Darcy-type law which is valid across the entire range of the Bingham numbers (i.e. the ratio of the fluid’s yield stress to the characteristic viscous stress). These two extreme limits are namely the viscous limit (infinitely large pressure gradient compared to the yield stress of the fluid – ultra low Bingham number) and the plastic/yield limit (infinitely large Bingham number).

Elastic instabilities and turbulence driven by elastic hoop stresses are likely to develop on top of shear-banding flows in giant micelles. We show the existence of a generic flow diagram in an operating space built on the curvature ratio Λ of the Taylor-Couette flow and the Weissenberg number Wi, which compares elastic and viscous stresses. Two different pathways to purely elastic turbulence are identified depending on Λ, with clear signatures in the stress response. The geometric scaling of the onset of elastic turbulence is found to be reminiscent of the Pakdel-McKinley criterion that recasts the different mechanisms and most unstable instability modes of flows with curved streamlines.

Most simulations of polymeric turbulence treat the solution as a suspension of elastic dumbbells. Though the feedback-force exerted by the beads of the dumbbell are taken into account while calculating the large-scale flow, the local disturbance flow at the scale of the dumbbell is typically neglected, i.e., inter-bead hydrodynamic interactions (HI) are disregarded. Here, we quantify the effect of these interactions on the dumbbell’s extension. We derive exact analytical results for a Batchelor-Kraichnan random flow, while also performing simulations in homogeneous isotropic turbulence. We find that the effects of HI are mild but extend beyond simply increasing the elastic relaxation time.

Migration and retention of particles in flow systems is a long-standing and ever-relevant topic. We identify a new mode of particle accumulation driven by geometry variations in confined spaces and nonhydrodynamic viscosity effects of complex particle systems, which is triggered in the absence of clogging effects and distinct from shear-induced migration in dense suspensions. A new dimensionless number is derived and validated by numerical simulations in typical pore-throat geometries. Investigations in heterogeneous porous structures reveal variable yet predictable accumulation patterns, offering new opportunities for preferential flow control in porous media.

The impact of gas rarefaction on the two-dimensional aerodynamic ground effect over a flat plate is analyzed. The free-molecular problem was studied analytically based on the collisionless Boltzmann equation and Maxwell boundary conditions, and compared with direct simulation Monte Carlo at finite Knudsen numbers (Kn). The results indicate that the ground invariably increases aerodynamic loading on the plate and shifts the maximum lift to lower angles of attack compared with the non-confined configuration (NC). While the ground may contribute negatively to the lift in the ideal-flow limit, its relative difference compared with NC is found to be significantly larger and positive at high Kn.

We examine the statistics of the deformation of sub-Kolmogorov droplets in homogeneous isotropic turbulence (HIT). Data obtained with various phenomenological ellipsoidal models (EMs) – assuming that the droplet preserves the ellipsoidal shape at all times – are compared with ground-truth data obtained with three-dimensional fully resolved simulations (FRSs), without any ad-hoc assumption on the droplet shape. We find that some EM models show close agreement with FRS data across the range of capillary numbers explored. Given the computational expense of FRS the possibility to generate ensembles of data with quantitatively validated EMs in shorter times could be useful for some purposes.

The inertial collapse of a cavitation bubble concentrates potential energy within the bubble. This process redistributes energy between the bubble and the surrounding liquid, while also emitting a shock wave. In the incompressible limit, bubble dynamics are governed by the driving pressure, but at high collapse speeds, compressibility effects become critical. We present a theoretical framework that corrects radiated energy estimates, derives closed-form expressions for bubble energy and volume at collapse, and relates shock pressure directly to governing parameters. Our results provide a foundation for describing more complex systems, such as bubble clouds and bubbles near boundaries.

Analytical solutions for the deformation, translational velocity, and rotational velocity of a linear poroelastic particle in an unbounded Stokes flow are provided. The solutions are specialized to the cases of shear and Poiseuille flows. Surprisingly, the rotation of the particle is not influenced by its poroelastic nature.

Conventional wisdom holds that suppressing droplet penetration through meshes needs to decrease pore sizes. Alternatively, this work demonstrates that a macro-ridge on a superhydrophobic mesh can increase the dynamic pressure threshold for liquid penetration. Using high-speed visualization and force measurements, we show that the ridge breaks the symmetry of droplet retraction, inducing multiple flow-focusing events at different sites in place of one flow-focusing event at the droplet center on a flat mesh. This work provides a new strategy for designing water-repellent surfaces without compromising the breathability.

Understanding the high-pressure characteristics of nanobubbles is a significant step forward in unraveling the complexities of bulk nanobubble behavior. In this study, the effect of external pressure on the bulk nanobubbles is systematically investigated. The results demonstrate that as external pressure increases, both the concentration and lifetime of nanobubbles in methanol and water are significantly enhanced, indicating improved stability. Notably, the effect of external pressure on the surface charge is minimal, with the enhanced stability primarily attributed to increased supersaturation, reduced gas molecular diffusion, and the reinforcement of the hydrogen bond network.

A mathematical model is developed for the spontaneous Qunicke rotation of a dielectric sphere in an electric field, which accounts for fluid and particle inertia. The particle dynamics obey an integro-differential dynamical system that is a generalization of the celebrated Lorenz equations. Analysis and numerical solution of these modified Lorenz equations show that fluid inertia inhibits chaotic particle rotation, in qualitative agreement with prior experimental observations.

Liquid films govern processes from bubble lubrication to emerging soft nanofluidic memristors, yet their response to electric fields has remained unclear. We develop an analytical framework considering Maxwell stress, disjoining pressure, and Laplace pressure to capture both equilibrium and dynamic responses of bubble liquid films, which explains the conductance rectification and hysteresis observed in experiments. This work positions liquid films as a concept of electrohydrodynamic soft memristors, which aims for future energy-efficient and neuromorphic computing.

Ice melting is an important part of the climate system that involves complex fluid dynamics and interactive processes. Here we address the capsize problem in which melting-induced changes in size and shape of free floating ice can trigger it to rotate and turn over. Experiments show that “lab icebergs” lock to the waterline while gradually melting, then abruptly lose stability and roll over to assume a new posture, and this process repeats many times as the ice melts down. A particular angle of rotation is selected and, consequently, the ice tends towards a polygonal shape. These results are reproduced by a model that predicts the coupled shape-posture dynamics and uncovers the key mechanisms.

Near-space hypersonic vehicles at 40–60 km altitude encounter local rarefaction effects that influence the boundary-layer stability and the laminar–turbulent transition. By incorporating slip boundary conditions and nonlinear constitutive relations into the Navier–Stokes equations and linear stability theory, we systematically investigate hypersonic boundary-layer stability over a blunt cone under near-continuum conditions. The results show that rarefaction thins the boundary layer and stabilizes second-mode instabilities, particularly at high wall temperatures or with small bluntness. These results offer new insights into hypersonic stability and transition in the near-continuum regime.

This study advances the understanding of blast-driven interface instabilities by transitioning from qualitative Mie scattering to quantitative planar particle image velocimetry (PIV). The velocity field and vorticity evolution reveal key insights into mixed-mode Richtmyer-Meshkov and Rayleigh-Taylor instabilities in a cylindrical geometry. High-Atwood number cases exhibit prolonged circulation growth, consistent with stronger turbulence and earlier mixing transition. The PIV data captures how pressure impulse and decay shape the instability beyond what Mie images alone can resolve.

The stability characteristics of a compressible shear flow confined by two rigid plates are important in applications such as open-jet facilities and launching rockets. By performing linear spatiotemporal stability analysis, we identify the critical parametric regions within which absolute instability occurs. In particular, we show that at sufficiently high Mach numbers, a new type of absolutely unstable mode occurs, which arises from a feedback process due to the reflection of compressible waves by the rigid plates.

Interfacial Rayleigh–Taylor (RT) and Faraday instabilities are usually studied separately, one driven by pressure gradients, the other by parametric resonance. Their coexistence produces a previously unidentified multi-modal instability. Floquet analysis and numerical simulations reveal a bidirectional competition: the Faraday mechanism, amplified by vibration, suppresses RT modes, while residual RT dynamics nonlinearly attenuate Faraday responses. This interaction advances understanding of interfacial mixing under combined forcing.

We propose the Diffuse-Resistance-Domain (DRD) approach — a thermodynamically consistent DNS method for microscale fluid-structure interactions (mFSI) in multicomponent multiphase flows. By unifying interfacial dynamics through Onsager’s variational principle and smooth interpolation of resistance coefficients, DRD naturally enforces complex boundary conditions — like dynamic contact angles — without ad hoc assumptions. It avoids evolving solid-phase fields, cutting computational cost while enabling high-fidelity simulations of moving or deforming boundaries. DRD accurately captures interfacial phenomena in microfluidics, active matter, and porous media, showing strong agreement with experiments.

When do mucus films plug lung airways? We show that the answer is not determined by just the film’s volume. While very thin films always stay open and very thick films always plug, we find a range of intermediate films for which plugging is uncertain. The fastest-growing linear mode of the Rayleigh-Plateau instability ensures that the film’s volume is divided among multiple humps. However, the nonlinear growth of these humps can occur unevenly, due to spontaneous axial sliding—a hump that slides rapidly can sweep up a disproportionate share of the film’s volume and so form a plug. This sliding-induced plugging is robust and prevails with or without gravitational and ciliary transport.

Liquid droplets sliding under gravity slow down markedly on viscoelastic substrates.However the influence of substrate thickness has remained elusive. Focusing on droplets with Bond numbers below one, we uncover a strong dependence of sliding velocity on thickness when the latter varies from microns to millimeters. Building upon these results, we establish a scaling relation linking velocity, droplet size, and layer thickness that capture the experimental data.

Contact lines, where fluid interfaces meet solid surfaces, pose a fundamental challenge to modeling fluid-fluid displacement in confined geometries, as they violate the classical no-slip boundary condition. Recent experiments reveal that contact-line motion in a capillary tube produces compact displacement at low flow rates and unstable fingering at high flow rates. We present a phase-field model with a novel formulation of the boundary wetting conditions. Our model captures the equilibrium configurations at arbitrary wettability, and also predicts dynamic configurations, including wetting transitions, thin-film formation and interface pinch-off, in quantitative agreement with experiments.

Chemomechanical phenomena lie at the core of many biological and biomimetic systems. Particularly in the presence of free interfaces, such effects arise naturally due to chemically induced gradients of interfacial tension. We study a simple, thermodynamically consistent model for liquid drops on solid substrates that captures the coupling between an autocatalytic reaction of insoluble surfactants, the Marangoni effect and wetting dynamics. In the presence of chemical fuel, drops may exhibit complex self-organized motility modes like crawling and shuttling. The underlying chemomechanical feedback and the resulting bifurcation structure are studied in detail.

What happens when a jet plunges into a liquid foam? In this study, we show that it can generate new, tiny bubbles inside the foam and, at higher speeds, stretch the soap films to the point of rupture. To explain these behaviors, we reproduce them in an elementary foam. There, we show that the tiny bubbles arise from an inversion of the Plateau border, while the spreading of the jet entrains films’ surface, triggering an elastic transition that leads to thinning. The resulting scaling laws extend to the two-dimensional foam phase diagram.

Thin-film modeling provides a computationally inexpensive way to quantify viscous film transport arising due to gravity and/or shear flow in tubes. Previous work has largely focused on tubes with fixed mean radius; this study quantifies the impact of a time-dependent radius on film transport. Linear stability analysis of this periodically-forced model shows that tube contractions/expansions enhance instability growth relative to a rigid tube. Simulations of the full nonlinear model equation highlight the role of free-surface waves in enhancing transport. Parameter values used here are motivated by the human lung/airway system.

We investigate compressible laminar boundary layers over isotropic porous substrates. A new self-similar solution with nonlinear drag and heat conduction shows that high porosity, large grains, and elevated Mach numbers reduce adiabatic recovery temperature and velocity gradients, while the substrate’s bottom temperature has little effect on shear.

We numerically study the buoyancy-aided mixed convective flow of air past a square cylinder inclined at 45 degrees. Buoyancy is progressively increased through the Richardson number (Ri) in the range (0.0-1.0), keeping the Reynolds number (Re) constant at 100. With increasing Ri, the flow transitions from an inertia-dominated to a natural convection-dominated one, showing dual wake-plume flow. Vortex shedding occurring at low Ri is found to be suppressed beyond a critical Ri, with a simultaneous emergence of far-field plume-like unsteadiness. Competing effects of inertia and natural convection result in a vorticity inversion observed at a certain distance downstream of the cylinder.

Understanding the flow topology of Taylor (plug) flow in small channels and microchannels is imperative for mass and heat transfer applications, yet comprehensive analysis remains limited, particularly when viscous continuous phases are employed. This study investigates liquid-liquid flow in microchannels, examining internal vortices within Taylor plugs through experimental and computational methods. The results reveal new insights into vorticity and geometry diminishment, advancing understanding of liquid-liquid Taylor flow in microchannels and system mass transfer optimization.

Superhydrophobic grooves offer substantial slip and drag reduction; however, real fluids are seldom completely clean. Using many-body dissipative particle dynamics simulations, we demonstrate that the presence of contaminant particles at the interface significantly decreases both local and effective slip. The primary factors influencing this effect are particle wettability and interfacial coverage, while particle size and mass have a minor role. The reduction in effective slip follows Philip’s model, providing a rule-of-thumb predictor and informing designs that can tolerate or manage contamination.

Precise, localized flow control in microfluidic devices remains a difficult challenge. We demonstrate, theoretically, how active droplets might be harnessed to overcome this challenge. Active droplets are produced along the microchannel wall via stimulation of a responsive hydrogel, and the ensuing phoretic slip flows drive transport and mixing in the microfluidic device.

We investigate the low-Reynolds-number hydrodynamics of rigid circular and spherical particles near a plane wall in a heterogeneous viscous environment comprising both ambient and disturbance viscosity fields. Focusing on the resistance problem, we theoretically and numerically compute the forces and torques acting on the particle. Our results demonstrate that viscosity gradients induce novel hydrodynamic cross-couplings in near-wall particle motion, which are also directly reflected in the resulting trajectories. These findings have potential implications for controlled transport, sorting, and separation in microfluidic applications.

The evaluation of added and coupling mass is central to fluid-structure interaction studies. Revisiting Batchelor’s 1967 framework, this work introduces a refined approach based on superposition of acceleration fields and numerical evaluation of kinetic energy in potential flows. By distinguishing between added and coupling mass, the method clarifies inertial forces for diverse body geometries and highlights implications for seismic design, underwater dynamics, and multiphase flow modeling.

Drying of complex fluids in porous media is crucial for applications such as preserving cultural heritage materials, yet the role of sol–gel transitions in evaporation kinetics remains unclear. We develop a pore-network model to investigate the emergence of gel-like skin at the evaporation interface. By incorporating pore size gradients and a viscosity-dependent vapor pressure rule, the model captures skin formation. Its predictions quantitatively match experiments and explain the evaporation slowdown during sol–gel transition.

Channel and zero-pressure-gradient spatially developing turbulent boundary layer are the two canonical wall-bounded flows. Despite the long-standing controversies about their similarity, there is little attention paid to the similarity/dissimilarity between these two types of particle-laden turbulence, which is one of the most important topics in turbulence research. The particle distribution, turbulent statistics, and structures in the two kinds of particle-laden flow are thoroughly compared for the identical particle Stokes number and bulk volume fraction at turbulent Reynolds number of Re${}_{\tau }$≈400. Qualitative and quantitative differences are observed throughout the turbulence region.

Previous research on gravity currents, the flow of a denser fluid through a less dense one, has largely focused on channels with rectangular cross-sections. How do these currents flow through more complex, nonrectangular shapes found in nature, like river estuaries or valleys? A generalized model that accounts for crucial effects of entrainment and drag in channels of various shapes is presented. This model reveals how these factors significantly reduce the current’s propagation speed while increasing its height and volume, especially in nonrectangular geometries. This work provides enhanced understanding of these flows, with findings that can be applied to diverse natural and engineered systems.

We present data-driven models for predicting the motion of a freely settling sphere in a quiescent fluid using experimentally measured trajectories. Deterministic and stochastic neural differential equations reconstruct individual particle paths and capture the statistical features of settling dynamics without resolving the surrounding flow. Our results reveal the strengths of each modeling approach. Deterministic models excel at trajectory prediction, while stochastic models reproduce long-time statistical trends, thus providing a framework for reduced-order modeling of particulate flows.

The paper examines rectilinear two-dimensional miscible viscous fingering in response to both injection and withdrawal of low viscosity fluid. Whether or not substantial fingering occurred during the injection controls the dynamics in the withdrawal period. At the end of injection, the fingers generally have a tip with a localized peak in concentration of the low viscosity fluid. This region then changes direction upon withdrawal. The low viscosity tip retraces the original finger because flow there is preferential as the viscosity is lower relative to the ambient fluid.

When one fluid moves through rocks or porous materials and displaces another, it creates branching structures known as “viscous fingering.” This phenomenon affects oil extraction, carbon dioxide storage, and drug mixing in microfluidic experiments. Traditionally, researchers have relied on costly computer simulations to study these patterns, which can become unstable. We present a new AI-based approach that accurately captures both small-scale details, such as the growth and merging of fingers, and large-scale outcomes, such as overall mixing of the two fluids. It operates significantly faster and remains reliable even where traditional methods struggle.

Understanding the dynamics of gravity currents is crucial in various engineering and environmental applications, such as CO${}_2$ sequestration and underground hydrogen storage. Gravity currents in porous media have often been studied considering a sharp interface between two fluids of different densities in the medium, overlooking the effects of mixing. In our study, we mark the importance of mixing in axisymmetric gravity currents and show that mechanical dispersion significantly alters the behavior of the gravity currents. We present formulations for estimating the rate of mixing and consequent evolution of gravity current length and volume.

The wall-normal Reynolds stress has a negligible contribution to the wall-normal momentum equation in low-Mach, zero pressure gradient boundary layers, and conservation of momentum indicates that pressure is uniform throughout the boundary layer. In hypersonic boundary layers analysis suggests the wall-normal Reynolds stress becomes significant compared to mean pressure and that it must balance with pressure. We validate this and show that the wall-normal Reynolds stress results in non-negligible pressure deficits. We show that errors in standard RANS models for the wall-normal Reynolds stress have a noticeable impact (5% for a Mach 14 cold-wall flow) on wall quantities of interest.

Characterization of the turbulent flow field in a constant-pressure, dual-chamber, expanding flame apparatus is presented, based on high-resolution particle imaging velocimetry. Turbulent flame speeds were measured for C${}_2$H${}_4$/air and NH${}_3$/CH${}_4$/air mixtures across turbulent Reynolds number ranges of 29–2706 and 69–2560, respectively. An extended scaling correlation for turbulent flame speed is proposed, applicable to both corrugated flamelets and thin reaction zones regimes. The proposed model demonstrates improved accuracy, with the mean absolute percentage error between experimental and predicted values of 7.8% for C${}_2$H${}_4$/air and 8.5% for NH${}_3$/CH${}_4$/air flames, demonstrating a comparative advantage over existing scaling models.

We examine the effect of compressibility on drag reduction in turbulent boundary layers actuated by spanwise traveling transversal surface waves. Wall-resolved simulations are performed at Mach numbers $M_1=0.2$ and $M_2=0.7$ over the same actuation space. The results show that drag reduction is greater at higher Mach number, but at $M_2=0.7$ the increased wave speed induces spanwise shock waves. These shocks disrupt turbulence, redistribute turbulent kinetic energy, and alter skin-friction contributions. The findings highlight the trade-off between enhanced drag reduction and reduced actuation efficiency in compressible flows.

Opposition control (OC) mitigates near-wall turbulence by local blowing and suction and is effective in reducing drag at low Reynolds numbers. Using direct numerical simulations up to Re${}_{\tau }$=2000, we show that drag reduction progressively deteriorates with increasing Re${}_{\tau }$ due to the enhanced influence of outer large- scale motions that OC fails to suppress. Our results quantify the Reynolds-number dependence of optimal control parameters and predict that about 15% drag reduction remains achievable at very high Re${}_{\tau }$. These findings highlight the need for hybrid strategies targeting both inner- and outer-layer turbulence to sustain drag reduction in realistic high-Re${}_{\tau }$ flows.

Quantum vortex lines are angstrom-scale tubes with quantized circulation ±κ, the Feynman–Onsager constant, that form the backbone of the superfluid velocity field in He-II flows. When forced to turbulence, they organize into a tangle characterized by its mean intervortex spacing. Combining second-sound resonant cavity measurements with 3D Lagrangian tracking for the first time, we observe that the mean intervortex spacing scales with the κ based Reynolds number following a Kolmogorov-like –3/4 power law. We then show both this scaling and the prefactor value can be explained with classical turbulence formalism due to the quantum restricted depth of the superfluid component energy cascade.

The interaction of vortex rings with solid surfaces is a classic problem in fluid dynamics, yet their collision with concave hemicylindrical shells remains poorly understood. This experimental study investigates vortex ring impingement on concave surfaces with varying curvature ratios (D${}_m$ /D${}_e$ = 15,10,5,2,1) at Re=1500. Using planar laser-induced fluorescence and particle image velocimetry, we reveal how curvature controls secondary vortex formation, rotation, and three-dimensional evolution. Dynamic models are proposed to explain the transition from tertiary to secondary vortex dominance as curvature increases, offering new insights into confined vortex-wall interactions.

We study the counter-rotating vortex pair in laminar jets in crossflow via a vorticity transport analysis at various jet-to-crossflow velocity ratios ($R$). At high $R$, most vorticity is generated in the pipe, but boundary layer vorticity is entrained into the pair at low $R$.

The vortex pair undergoes bubble vortex breakdown at low-to-intermediate $R$, due to the adverse pressure gradient through the vortex cores. Breakdown persists at the onset of hairpin vortex shedding with decreasing $R$, but disappears upon further growth in instability amplitude. A new low frequency and spanwise symmetry-breaking instability characterized by alternating breakdown of the vortex pair was also identified.

We develop a nonlinear wave reconstruction and prediction model with a dynamic averaging algorithm, in which shipborne radar images are used for data assimilation to improve the accuracy of wave reconstruction and prediction. Waves around the ship can be accurately predicted for the next few minutes under various sea states. Compared with the linear and second- order models, the new model includes the third-order nonlinear effects; thus, it significantly improves the prediction accuracy of extreme waves under rough sea states, providing effective safety guarantees for ship navigation and operations.

This work presents a novel Physics-Informed Neural Network (PINN) approach for nonlinear ocean wave data assimilation and prediction. The method leverages potential flow theory to parameterize wave dynamics and integrates physical constraints into the loss function, enabling accurate reconstruction and prediction of phase-resolved, nonlinear, and dispersive wave fields from sparse measurements. Validated against analytical solutions and laboratory experiments, this PINN framework infers full spatiotemporal wave and velocity potential fields efficiently and thus advances the use of physics-informed machine learning for ocean wave modeling and understanding.

A new hybrid Reynolds-Averaged-Navier-Stokes/Large Eddy Simulation (RANS/LES) model is proposed. With the discontinuous Galerkin spectral element method (DGSEM), it gives a robust and efficient approach for simulating high-speed and high-Reynolds-number turbulent flows. A change of variable from omega in the k-omega model to g, gives the k-g model, which avoids the singularity near the wall and makes the model work in DGSEM. The model is tested in various cases, including wall-bounded turbulence, wall-modeled LES, flow separation, and compressible flows, with good performance.

Machine learning can accelerate the prediction of fluid flow around obstacles, but existing models often struggle to generalize to geometries not seen during training. We introduce a generative diffusion model that uses an obstacle’s geometry as a conditional prompt to predict the corresponding instantaneous flow field. Trained only on elementary shapes, the model demonstrates superior generalization by capturing key features like vortex shedding and pressure distributions for unseen and complex geometries. By generating more physically consistent results, it outperforms standard neural network and variational autoencoder models, showing promise for accelerating CFD workflows.

Experimental measurements were performed of convective heat transfer fluctuations beneath a grazing turbulent boundary layer flow. Spatiotemporal wall-temperature fields were acquired with an infrared camera and a heated-thin-foil sensor. Inferred Nusselt number fluctuations showed elongated features with scales similar to near-wall streaks. An analysis in the frequency–wavenumber domain revealed dispersive convection: larger streaks moved near freestream velocity, while smaller energetic features traveled at 10 times the friction velocity. These measurements provide a promising method for wall-based turbulence sensing and flow control.

Data assimilation provides a rigorous framework for integrating measurements with numerical simulations to estimate the flow. We developed a machine-learning-based assimilation strategy to infer unknown upstream flow conditions in a high-speed boundary layer from sparse wall-pressure measurements. Our method uses a Bayesian optimization to efficiently search for the optimal control parameters. Applied to a transitional boundary layer, the method accurately estimates the oncoming disturbances, and subsequent direct numerical simulation (DNS) predictions using the estimated conditions show excellent agreement with the true flow.