Chemically reacting flows through porous media are widespread in biological, environmental, and engineering applications. Yet, understanding these flows remains an outstanding challenging. This letter reveals that hydrodynamic dispersion affects reaction fronts in ways analogous to free turbulence. Our findings thus point to a regime diagram that elucidates the pore-scale coupling between fundamental processes, offering valuable theoretical insights into these complex flows.

This work presents an analytical solution of flow through disordered porous media with inertia effects at a finite Reynolds number (Re), and consequently a truncated quadratic formula for easy use without any fitting parameters. The derivation is based on an effective capillary model in which the effective radius of capillaries varies with Re. Inspired by the asymptotic solution of flow in curved capillaries, the Oseen-form equation is derived to capture the flow behavior in each capillary. The analytical formula has been validated by comparisons with numerous available experimental data.

Previous theoretical work predicted that the variance of the velocity in a suspension of spherical particles should diverge with system size, but experiments find the variance asymptotes to a finite value at large system size. Accounting for the inertia of the suspending fluid is shown to resolve this discrepancy and provides predictions for how the variance depends on the volume fraction and densities of the suspended particles and the densities of the fluid.

When the 17th century Dutch microscopist Antonie van Leeuwenhoek discovered swimming “animalcules” called rotifers he observed that they often adhere to surfaces. A new analysis explains this by showing that as rotifers swim by the action of groups of cilia on either side of their mouth, the resultant fluid flows turn the rotifer to align perpendicular to a surface, pulling it in until it makes contact. This is precisely the opposite of what happens with green algae, whose breaststroke beating of its two flagella turns a cell away from the wall. Once attached, the rotifer rotates in place until random motions detach it, and it swims off in a new direction, leading to a random walk.

Detonation initiation induced by thermal nonuniformity in a supersonic reactive flow is analyzed with a theoretical model in one and two dimensions. A self-strengthening coupling between the reaction front and the induced shock wave is found to provide an underlying mechanism for detonation initiation. To quantify the capability of the thermal nonuniformity to cause detonation initiation, we introduce a detonation initiation factor. This factor is found to change nonmonotonically depending on the temperature difference of the thermal nonuniformity.

This work presents a micro-macro model for polymeric fluids incorporating an Elastic-Plastic (EP) potential to examine irreversible bond breaking in polymer chains. Using numerical simulations, we reveal how microscopic polymer behaviors under shear flow, including elongation, rotation, and bond breaking, impact shear stresses and velocities at the macro scale. Comparisons with classical potentials (Hookean, FENE, Morse) highlight distinct stress and flow responses, with shear-thinning behavior observed at high shear rates due to polymer rotation.

If carbon dioxide dissolves into a body of water, a CO${}_2$-rich boundary layer forms at the interface, which is denser in comparison to pure water, leading to the onset of buoyancy-driven convection and, consequently, the shedding of a buoyant plume. We look at the influence of confinement on this process in two ways. First, we focus on expanding our understanding of the short-time, transient diffusion of CO${}_2$ into a vertical water barrier confined to a narrow cylindrical cell. Secondly, we investigate the long-time, steady mass transfer dynamics in the liquid barrier by trapping a slug bubble underneath the liquid barrier and varying the barrier height and partial CO${}_2$ pressure.

Liquid sheets are common in technology and nature, and can rupture due to intermolecular van der Waals (vdW) forces if they are sufficiently thin. Recent work by Burton and Taborek has demonstrated that contracting inviscid liquid sheets can break even without vdW forces. Here, we have used two-dimensional simulations and theory to show that when fluid viscosity is small but finite, contracting liquid sheets can escape from pinch-off in the absence of vdW forces due to two distinct mechanisms that depend on Ohnesorge number (a dimensionless group that is proportional to viscosity).

We explore the dynamics of alkane drops impacting a brine bath, where the temperature is tuned to freeze the drops on impact. Depending on the thermal shock and drop velocity, the result is either a flat or cupped frozen drop. By analyzing the competition between the impact dynamics and the formation of a thin layer of ice at the interface between the drop and the bath, we explain this morphological transition.

The present study provides a comprehensive analytical prediction for the steady-state deformation and inclination angle of drops under shear flow, considering both confinement and interface viscosity. By merging the theories for confined and unconfined drops, the model accurately captures the behavior across a wide range of conditions, offering a robust tool for applications in complex fluids. Immersed boundary-lattice Boltzmann simulations were performed to further validate the results.

Liquid-liquid interfaces typically exhibit a diffuse nature, with an interface thickness that is comparable with the electric double layer under practical conditions. In two-liquid electrokinetics, effects of solvent mixing become particularly pronounced when imbalanced ion partitioning dominates the interface charging, which is intricately linked to the interfacial physico-chemical properties. Our study presents a holistic framework to incorporate the general charging mechanisms into a diffuse interface description, paving the way for future research in two-liquid physico-chemical hydrodynamics, where the constitutive relationship of two-liquid interface charging is pivotal.

Although flows of electrically conducting fluids in circular pipes with applied magnetic fields occur in many engineering applications, the mechanisms behind their transition to turbulence are still not fully understood. In this context, we address the transient algebraic growth of three-dimensional disturbances in MHD pipe flow with a transverse magnetic field. Depending on its intensity, we identify four types of optimal perturbations, characterized by different topologies and varying underlying growth mechanisms. Additionally, we study the nonlinear evolution of the optimal perturbations using direct numerical simulations.

The maximum spreading radius of liquid metal droplets under magnetic fields is a key parameter for characterizing their spreading behaviors, which garners close attention in fusion engineering. While the scaling law for the maximum spreading of metal droplets under a vertical magnetic field has been established, no relevant studies have addressed the effects of horizontal magnetic fields due to anisotropic spreading induced by the Lorentz force. In this paper, we conduct a three-dimensional numerical simulation to investigate the maximum spreading features of GaInSn droplets under a horizontal magnetic field and propose a theoretical model to predict their maximum spreading area.

Undercurrents, which flow oppositely to the upper layer, are important in subsurface water transport and circulation connection. To understand Western Pacific Ocean undercurrent dynamics, we use an idealized model to study the nonlinear formation and secondary instability of jet meanders due to baroclinic instability. We develop a weakly nonlinear framework to track the perturbation evolution and along-stream mean flow. The instability of saturated meanders is analyzed with a three-dimensional Floquet-based secondary instability framework. The current and undercurrent interaction due to nonlinear and secondary instabilities is revealed. Implications for realistic oceanic flows are discussed.

Development of offshore wind farms in shallow coastal seas is becoming increasingly widespread, and raises questions as to the potential extent of hydrodynamic impacts to the oceanic environment. This work presents an idealized analytical model to study the potential alterations to the mean ocean currents due to the presence of the offshore wind farm foundation structures and their increased friction. We find that this “blocking” of ocean currents has a simple scaling that depends primarily on the ratio of the friction inside and outside the farms, and depending on the farm characteristics can either be negligible, or change mean currents by around 10% in existing farms in the North Sea.

Geothermal temperature gradients may influence the fluid dynamics and convection developed during CO${}_2$ sequestration in deep saline aquifers. Here, we explore the intricate interplay in thermosolutal convection developed by vertical temperature and concentration gradients. By analyzing instability, we present insights into optimum conditions for enhanced convection and mixing between CO${}_2$ and brine.

We investigate flow instability of the free convection boundary layer evolving along a vertical cylinder with a broad spectrum of surface curvatures. The random perturbation calculation shows that the boundary layer could filter disturbances for a high frequency band (HFB) and the single mode perturbation calculation determines the flow characteristic frequency $f_c$. The results suggest that as curvature $A$ increases, the characteristic frequency of the thermal boundary layer increases, while the disturbance amplitude decreases. The flow Reynolds stress is strongly amplified toward the downstream at $f_c$ and dramatically decreases at a decaying frequency $f_c$-3.5∆.

Adjoint methods have been central in gradient-based optimization but traditionally require known governing equations. In this paper, we introduce a data-driven approach that utilizes echo state networks (ESNs) to infer adjoint sensitivities from data, even in cases where the system’s equations are unknown, or the data are subjected to noise. By embedding physical knowledge into the network architecture, the method accurately predicts sensitivities to parameters and initial conditions in a nonlinear thermoacoustic system. This framework opens new possibilities for gradient-based data-driven design optimization.

Due to its high surface tension, the water-air interface is particularly susceptible to contamination by surface-active molecules, which can significantly alter the hydrodynamic behavior of the interface. This is especially true in the case of thermocapillary flows. In this study, we present a general framework that enables a quantitative analysis of this phenomenon, demonstrating how key properties of the otherwise undetectable surfactants can be derived from experimental data.

The drag-out problem for small Reynolds numbers (Re) admits the Landau-Levich-Derjaguin (LLD) solution for small capillary numbers (Ca), and Derjaguin’s solution for large Ca. We investigate whether these solutions are absolutely or convectively unstable, solving the Orr-Sommerfeld eigenvalue problem. We show that Derjaguin’s solution is convectively unstable for Ka$<$17 and absolutely unstable for Ka=0.15 Re${}^{1.7}$ for Re $>$ 10 where Ka is the Kapitza number. For water (Ka=3400), the LLD solution is always convectively unstable. The absolute instability is observed only when the dip-coated film is additionally fed from above.

A simple computational model simulating the evolving shape of the interface between two immiscible fluids such as oil and water in a turbulent flow has been validated using high-fidelity numerical simulations. Established theory is extended to predict that the dependencies of the smallest scale of interface wrinkling on turbulence intensity and surface tension collapse to dependence on a single parameter, involving two power-law regimes. The computational model reproduces all these features and the predicted power-law exponents. This and the other validations indicate that the model accurately represents the interaction between surface tension and turbulent fluid motion.

Aerodynamic modeling for aircraft often incurs high costs and time-intensive simulations. Our research addresses this challenge by utilizing a transfer learning model that effectively harnesses existing historical aerodynamic data. By leveraging point cloud data from previous simulations, we significantly reduce the need for new, costly simulations while achieving accurate predictions. This approach enables near-real-time aerodynamic analysis across different configurations, offering a solution that maximizes sample efficiency for future aircraft design and optimization.

Particle-resolved numerical simulations with a macroscopic gradient in the particle concentration are performed. The velocity contours for flows along (left) and against (right) the particle concentration gradient suggest different average particle-fluid interaction forces in these flows. We show that the average forces can be decomposed into the drag force, which is independent of the particle concentration gradient, and two terms related to the particle-fluid-particle (PFP) stress and the diffusion stress. The effect of the concentration gradient is accounted by the two stress related terms. These stresses can be studied in statistically uniform flows.

Vertical size segregation in sediment transport plays a crucial role in determining sediment rates and shaping river bed morphology. To gain deeper insights into the dynamics of segregation, laboratory experiments on bedload transport were carried out, tracking the movement of a large intruder particle buried within a granular bed composed of smaller particles. By varying the size of the larger particle, an extensive dataset was gathered, leading to robust conclusions on the spatial trajectory of the intruding particle and its segregation time. Using these data, a kinematic model was developed to predict the ascent duration of the intruder depending on size ratio.

Direct numerical simulations of two-way force-coupled particle-laden compressible turbulent boundary layers are performed to investigate the effects of particles on momentum and kinetic energy transport. The presence of particles suppresses turbulent fluctuations, as reflected in reduced Reynolds stresses, and diminished skin friction and turbulent kinetic energy production. Particle dissipation, due to the relative velocity between fluid and particles, accounts for under 1% of mean viscous dissipation and 10% of turbulent dissipation in the highest mass loading case. The near-wall mean temperature is elevated and influences the particle feedback force and reduced turbulent diffusion.

To consider fluid compressibility and multiscale features in cavitation simulations, we develop a compressible Euler-Lagrange method in OpenFOAM. Using this method, we investigate the characteristics of sheet/cloud cavitation and tip-leakage cavitation in detail. The results show that the evolution of microscopic bubbles has a great influence on the pressure fluctuations in the flow field. Furthermore, we also study the bubble size distribution and obtain two distinct power laws, namely -4/3 for small bubbles and -10/3 for large bubbles.

In the manufacturing process of composite materials, jet flows are commonly used to deposit anisotropic particles such as fibers. The strength or optical properties are dictated by fiber orientation, amongst others. This study investigated the motion of fibers in co-axial jet flows. In particular, the translational and rotational motion of fibers exiting from the inner jet is linked to the strong internal shear layer (ISL) existing between the fast moving outer jet and the slow moving inner jet. We show that fibers are strongly affected by the toroidal vortices in the ISL and that their translational and rotational motion can exceed that of the local fluid flow due to the “sling effect”.

The blood microcirculatory network is where nutrients, respiratory gases, and metabolic waste products are exchanged with the neighboring cells. Here, these components can take unexpected routes to get from one point to another. Whereas a simple fluid would follow the most direct route, we show in our $in$ $vitro$ experiments that red blood cells, which are responsible for oxygenating the body, can intermittently take side routes and remain in the network longer than expected. These observations, backed up by associated modeling, raise new questions regarding hypoxia mechanisms in organs, even under apparently healthy conditions.

Residence time distributions (RTDs) of a saturated unstable channel flow are investigated. To this aim, a new Lagrangian method for computing RTDs in any type of open flow is developed. The RTDs obtained display two kinds of pattern: for short travel distances, a pattern of peaks and valleys is observed for long residence times; for longer travel distances, a large probability peak is observed at the travel time of the Tollmien–Schlichting wave.

Many factors influence the long-time behavior and mixing of a passive scalar field transported by a two-dimensional (2D) fluid flow. Our investigations based on statistical mechanics and numerical simulations suggest that the correlation of the scalar field with the flow’s vorticity field is an important factor: strong correlation with the vorticity field is detrimental to mixing. This is linked to the inverse cascade in 2D turbulence and the persistence of large scale vortical structures.

New, high-resolution satellite altimetry is starting to reveal ocean turbulent flows at submesoscales, which are key to climate and marine ecology. However, the resulting velocity fields essentially represent the geostrophic flow component, while at these scales ageostrophic dynamics should start to become important. Using numerical simulations, we investigate the impact of unresolved ageostrophic motions on Lagrangian tracer dispersion. We find that filtering out ageostrophy only weakly affects dispersion, except for an overestimation of the typical pair-separation rate. Yet, it clearly misses transient particle clustering, which is found to be quite intense even at low Rossby numbers.

We have constructed a machine learning-based turbulence model for a shell model. Without $ad$ $hoc$ stabilizations, the constructed model becomes unstable when the cutoff wavenumber is lower than $0.2{\eta }^{-1}$, where $\eta$ is the Kolmogorov length. This wavenumber characterizes the subordination of smaller to larger scales in turbulence. This finding highlights a theoretical limitation of turbulence modeling without stabilization techniques.

To provide theoretical support for the development of wall models for simulating transcritical flows, we investigate structural properties in the turbulent boundary layers of transcritical flows. Primary innovations include: i) Substantiating the inner-outer interactions in turbulent boundary layers with strong variations in thermodynamic properties; ii) Extending the traditionally incompressible attached eddy model to transcritical flows and provide new scaling for the mixing length model and the wall-attached eddy model by considering inner-outer interactions. This mixing length model can be used in the nonequilibrium wall model for wall-modeled large eddy simulations (WMLES) methodology.

The limitations of data-driven extreme-event forecasting are examined by finding the minimum computational cost of producing accurate forecasts. For this purpose, the information bottleneck method is applied to a very large dataset of direct numerical simulations of turbulent trajectories in two-dimensional Kolmogorov flow. This method is used to construct optimal models to predict extreme dissipation bursts, exploring the trade-off between model complexity and predictive skill. The results show that model complexity must increase exponentially with the forecast horizon to produce accurate predictions and that this is connected with uncertainty in the causal origin of extreme events.

The present study proposes a method to estimate time-resolved three-dimensional velocity fields for underexpanded, screeching jets based on a linear stochastic estimation with non-time-resolved velocity data and time-resolved acoustic data. The proposed method can reconstruct three-dimensional velocity fluctuation fields associated with screech at the same sampling rate (200 kHz) as the microphone measurement. The azimuthal characteristics in different screech modes are investigated. We found that the flapping structure in the B mode exhibits random clockwise and counterclockwise rotations over an extended time domain. In addition, the flapping structure is first identified in the C mode.

Superfluid helium consists of a mixture of inviscid superfluid and viscous normal fluid. The normal fluid is affected by quantized vortices through mutual friction. Two models have been used to describe this interaction: the two-way coupled mutual friction (2W) model using experimental parameters and the self-consistent two-way coupled mutual friction (S2W) model independent of experimental parameters. This study compares the two models in detail regarding quantized vortex ring propagation, reconnection, and thermal counterflow, and provides their advantages and limitations.

Drag reduction within a turbulent boundary layer was achieved with dilute polymers that were controlled such that the Weissenberg number (Wi) was uniform in the flow. Two conditions were selected for comparison: (i) different Wi at similar drag reduction (DR) levels and (ii) different DR at comparable Wi. While the mean velocity had a secondary Wi dependence, the fluctuating statistics had a strong Wi dependence. Similarly, proper orthogonal decomposition showed the polymers deplete energy for the small scales. These trends underscore the importance of Wi when seeking a universal scaling of polymer-modified flows

We employ second-order spectral stochastic estimation (SSSE) to investigate scaling behaviors of the couplings between physical fields, which include velocity-temperature and velocity-pressure couplings. Particular attention is given to differences between the SSSE and the first-order version (FSSE). Several metrics are proposed to compare their accuracy in estimating the thermodynamic fields with the velocity input in the logarithmic region. The SSSE has an advantage over the FSSE in estimating strong events and thermodynamic field variations. However, there is little difference in the ability of FSSE and SSSE to capture transient characteristics of near-wall thermodynamic fields.

Although phase-averaged modeling of energy input from wind to waves is relatively mature, the effect of wind on wave evolution on a wave-by-wave basis has received less attention. In this paper, we perform parametric laboratory experiments in a large-scale wave tank to investigate the interaction between waves and the wind. We focus on the properties and evolution of deep-water gravity waves under the following wind forcing and analyze the effects of forcing wind on waves with different initial wave steepness. In addition, we discuss wave energy input in the wave spectra tail and the exceeding probability of wave height and wave crest height.

Jet impacts are a widely used method for surface cooling, prompting significant research into the thermal transfer processes that occur when a jet strikes a heated surface. However, hydrodynamic aspects of the problem have yet to be investigated. We demonstrate that low-inertia jets produce single and centimeter scale drops upon impact, whereas high-inertia jets generate millimeter or submillimeter scale droplets that are ejected axisymmetrically, but at a well-defined angle relative to the horizontal plane. We focus on the second regime and characterize the radius of the contact area below the jet and the properties (ejection angle, speed, radius, energy) of the ejected droplets.