Thermal forcing in natural environments, such as Earth’s surface, exhibits complex spatiotemporal variations due to daily and seasonal cycles. This motivates our study of Rayleigh–Bénard convection with hybrid spatiotemporal modulation at the thermal boundary, achieved by applying a travelling thermal wave to a bottom plate with modulated wavenumber $k$ and frequency $f$. At low frequencies, spatial modulation dominates, organising coherent thermal plumes. At high frequencies, the rapid propagation of the thermal wave smooths out the plumes, thereby reducing convective efficiency. We find that the emergence of the ‘smoothing’ effect is governed by the ratio between the wave speed ($c = f/k$) and the pseudo-speed of thermal diffusion, $c_{\textit{diff}} = 4\pi k/\sqrt {\textit{RaPr}}$, a scale-dependent measure of thermal damping. By comparing these speeds, we identify distinct regimes: (i) a spatially modulated-dominated regime ($c\lt c_{\textit{diff}}$), in which the slow movement of the boundary thermal wave allows coherent thermal plumes to follow the wave, maintaining coherence in both time and space; and (ii) a travelling-wave-dominated regime ($c\gt c_{\textit{diff}}$), where the fast-moving thermal wave disrupts the spatial coherence of thermal structures near the boundary layer. These findings establish a new framework for understanding the interplay of spatial and temporal modulation, advancing our knowledge of heat transfer in systems with complex boundary conditions.

A model for galloping detonations is conceived as a sequence of very fast re-ignitions followed by long periods of evolution with quenched reactions. Numerical simulations of the one-dimensional Euler equations are conducted in this limit. While the mean speed and structure is found in reasonable agreement with Chapman–Jouguet theory, very strong pulsations of the lead shock appear, along with a train of rear-facing N-waves. These dynamics are analysed using characteristics. A closed-form solution for the lead shock dynamics is formulated, which is found in excellent agreement with numerics. The model relies on the presence of a single time scale of the process, the pulsation period, which controls the shock dynamics via the shock change equations and establishes a shock decay with a single time constant. These long periods of shock decay with known dynamics are punctuated by energy release events, with ‘kicks’ in the shocked speed controlled by the pressure increase and resulting lead shock amplification. Model predictions are found in excellent agreement with previous numerical results of pulsating detonations far from the stability limit.

Cross-shelf transport in the inner continental shelf is governed by wind, wave and tidal interactions, but the role of Langmuir circulation (LC), induced by wave–current interaction and modulated by tides, has remained under-studied in this setting. We develop a Reynolds-averaged Navier–Stokes (RANS) model incorporating the Craik–Leibovich vortex force to resolve LC, coupled with a mass-conserving undertow and oscillating along-shelf tidal currents, and compare results against field data from the Martha’s Vineyard Coastal Observatory (MVCO). Under strong wave forcing (significant wave height $H_{\textit{sig}} = 2.12\,\mathrm{m}$ and significant wave period $T_w = 5.8\,\mathrm{s}$), LC persists throughout the tidal cycle, reducing vertical shear in the tidally averaged cross-shelf velocity profile compared with simulations excluding LC. During peak tidal velocity (reaching $25\,\mathrm{cm\,s^{-1}}$ with period of $ 12.42\,\mathrm{h}$), LC is temporarily suppressed but reforms rapidly as tidal energy declines, sustaining high vertical mixing. Conversely, under weak wave forcing ( $H_{\textit{sig}} = 0.837\,\mathrm{m}$, $T_w = 4.3\,\mathrm{s}$), tidal currents persistently suppress LC, resulting in a cross-shelf undertow profile with greater vertical shear compared with strong-wave conditions. Model–observation comparisons show that only simulations including both the Craik–Leibovich vortex force and tidal forcing reproduce the observed undertow structure at MVCO. These results demonstrate that accurate prediction of cross-shelf transport at tidal and subtidal time scales requires resolving both the generation and disruption of LC by tides.

We study the dynamics of salt fingers in the regime of slow salinity diffusion (small inverse Lewis number) and strong stratification (large density ratio), focusing on regimes relevant to Earth’s oceans. Using three-dimensional direct numerical simulations in periodic domains, we show that salt fingers exhibit rich, multiscale dynamics in this regime, with vertically elongated fingers that are twisted into helical shapes at large scales by mean flows and disrupted at small scales by isotropic eddies. We use a multiscale asymptotic analysis to motivate a reduced set of partial differential equations that filters internal gravity waves and removes inertia from all parts of the momentum equation except for the Reynolds stress that drives the helical mean flow. When simulated numerically, the reduced equations capture the same dynamics and fluxes as the full equations in the appropriate regime. The reduced equations enforce zero helicity in all fluctuations about the mean flow, implying that the symmetry-breaking helical flow is generated spontaneously by strictly non-helical fluctuations.

Turbulent separating and reattaching flows are known to exhibit low-frequency fluctuations manifested in a large-scale contraction and expansion of the reverse-flow region. Previous experimental investigations have been restricted to planar measurements, while the computational cost to resolve the low-frequency spectrum with high-fidelity simulations currently appears to be unaffordable. In this article, we make use of volumetric measurements to reveal the low-frequency dynamics of a turbulent separation bubble (TSB) formed in the fully turbulent flow past a smooth backward-facing ramp. The volumetric velocity field measurements cover the entire separated flow region over a domain with a spanwise extent of $S=0.6\, {\textrm{m}}$. Spectral proper orthogonal decomposition (SPOD) of the velocity fluctuations reveals low-rank low-frequency behaviour at Strouhal numbers ${\textit{St}}\lt 0.05$, which was also observed in previous planar measurements. However, in contrast with the interpretation of a two-dimensional contraction/expansion motion, the low-frequency dynamics is shown to be inherently three-dimensional, and governed by large elongated structures with a spanwise wavelength of approximately $S/2$. A low-order model constructed with the leading SPOD mode confirms substantial changes of the TSB extent in the centre plane, linking it to the modal pattern that is strongly non-uniform in the spanwise direction. The findings presented in this study promote a more complete understanding of the low-frequency dynamics in turbulent separated flows, thereby enabling novel modelling and control approaches.

The present work brings to light the vibrations emerging when a circular cylinder, elastically mounted along a rectilinear path in quiescent fluid, is subjected to a forced rotation about its axis. These rotation-induced vibrations (RIV) are explored numerically for ranges of the four governing parameters. The Reynolds number and the reduced velocity (inverse of the non-dimensional natural frequency of the oscillator), based on the surface velocity of the rotating body and its diameter, are varied up to $100$ and $250$, respectively, and the structural damping ratio up to $50\,\%$. The structure to displaced fluid mass ratio ranges from $0.1$ to $1000$. Vibrations are found to occur over a vast region of the parameter space, including the four orders of magnitude of the mass ratio under study, and high levels of structural damping. The amplitude of RIV may exceed $30$ body diameters, while their frequency varies and deviates from the oscillator natural frequency, even though it is always lower. Despite its simplicity and the steady nature of the actuation, the system exhibits a considerable diversity of behaviours. Three distinct RIV regimes are encountered: two periodic regimes whose responses differ by their spectral contents, i.e. sinusoidal versus multi-harmonic, and an aperiodic regime. These regimes are all closely connected to flow unsteadiness, in particular via the interplay of the cylinder with previously formed vortices, which persist in the vicinity of the body.

To study the physics of small-scale properties of homogeneous isotropic turbulence at increasingly high Reynolds numbers, direct numerical simulation results have been obtained for forced isotropic turbulence at Taylor-scale Reynolds number $R_\lambda =2500$ on a $32\,768^3$ three-dimensional periodic domain using a GPU pseudo-spectral code on a 1.1 exaflop GPU supercomputer (Frontier). These simulations employ the multi-resolution independent simulation (MRIS) technique (Yeung & Ravikumar 2020, Phys. Rev. Fluids, vol. 5, 110517) where ensemble averaging is performed over multiple short segments initiated from velocity fields at modest resolution, and subsequently taken to higher resolution in both space and time. Reynolds numbers are increased by reducing the viscosity with the large-scale forcing parameters unchanged. Although MRIS segments at the highest resolution for each Reynolds number last for only a few Kolmogorov time scales, small-scale physics in the dissipation range is well captured – for instance, in the probability density functions and higher moments of the dissipation rate and enstrophy density, which appear to show monotonic trends persisting well beyond the Reynolds number range in prior works in the literature. Attainment of range of length and time scales consistent with classical scaling also reinforces the potential utility of the present high-resolution data for studies of short-time-scale turbulence physics at high Reynolds numbers where full-length simulations spanning many large-eddy time scales are still not accessible. A single snapshot of the $32\,768^3$ data is publicly available for further analyses via the Johns Hopkins Turbulence Database.

Layer formation can occur within stratified fluids, often associated with the effect of ‘double diffusion’ where the fluid buoyancy depends on two components with differing molecular diffusivities (e.g. heat and salt in seawater). However, since layering also occurs in one-component stratified fluids, the generation mechanism for layers is often unclear. In this paper, we present a framework that unifies multiple-layer generation mechanisms across both one- and two-component stratified fluids. We demonstrate how these mechanisms can be assessed using simulations of double-diffusive intrusions. Our simulations illustrate the importance of the negative turbulent diffusivity for buoyancy in contributing to layer formation.

The attainable metastability is key to the behaviour of liquids undergoing rapid depressurisation. This tells us how far the liquid can be depressurised, or stretched, before phase change occurs. Previous work on the depressurisation of liquids through nozzles and pipes shows that classical nucleation theory (CNT) can predict the attainable metastability close to the critical point, but fails at lower temperatures. In the latter case, it is common to correct the CNT prediction using a strongly temperature-dependent empirical reduction factor. In the present work, we show that the trend at low temperatures naturally follows if the metastability of the liquid is limited by the growth of pre-existing bubbles. With the new volume balancing method, we calculate the attainable metastability for systems with pre-existing bubbles and attain excellent fit with data for both $\textrm {CO}_2$ and water systems. The method has one tuning parameter related to the number of available bubbles in the flow, which is temperature independent.

Active colloidal particles create flow around them due to non-equilibrium processes on their surfaces. In this paper, we infer the activity of such colloidal particles from the flow field created by them via deep learning. We first explain our method for one active particle, inferring the $2s$ mode (or the stresslet) and the $3t$ mode (or the source dipole) from the flow field data, along with the position and orientation of the particle. We then apply the method to a system of many active particles. We find excellent agreements between the predictions and the true values of activity. Our method presents a principled way to predict arbitrary activity from the flow field created by active particles.

Flame–flame interactions in continuous combustion systems can induce a range of nonlinear dynamical behaviours, particularly in the thermoacoustic context. This study examines the mutual coupling and synchronisation dynamics of two thermoacoustic oscillators in a model gas-turbine combustor operating within a stochastic environment and subjected to external sinusoidal forcing. Experimental observations from two flames in an annular combustor reveal the emergence of dissimilar limit cycles, indicating localised lock-in of thermoacoustic oscillators. To interpret these dynamics, we introduce a coupled stochastic oscillator model with sinusoidal forcing terms, which highlights the critical role of individual synchronisation in enabling local lock-in. Furthermore, through stochastic system identification using this phenomenological low-order model, we mathematically demonstrate that a transition towards self-sustained oscillations can be driven solely by enhanced mutual coupling under external forcing. This combined experimental and modelling effort offers a novel framework for characterising complex coupled flame dynamics in practical combustion systems.

Elastoviscoplastic (EVP) fluid flows are driven by a non-trivial interplay between the elastic, viscous and plastic properties, which under certain conditions can transition the otherwise laminar flow into complex flow instabilities with rich space–time-dependent dynamics. We discover that under elastic turbulence regimes, EVP fluids undergo dynamic jamming triggered by localised polymer stress deformations that facilitate the formation of solid regions trapped in local low-stress energy wells. The solid volume fraction $\phi$, below the jamming transition $\phi\lt\phi_J$, scales with $\sqrt {\textit{Bi}}$, where $\textit{Bi}$ is the Bingham number characterising the ratio of yield to viscous stresses, in direct agreement with theoretical approximations based on the laminar solution. The onset of this new dynamic jamming transition $\phi \geqslant \phi _J$ is marked by a clear deviation from the scaling $\phi \sim \sqrt {\textit{Bi}}$, scaling as $\phi \sim \exp {\textit{Bi}}$. We show that this instability-induced jamming transition – analogous to that in dense suspensions – leads to slow, minimally diffusive and rigid-like flows with finite deformability, highlighting a novel phase change in elastic turbulence regimes of complex fluids.

We study the mixing of passive scalars in a velocity field generated by selected-eddy simulations (SES), an approach where only a randomly selected subset of spectrally distributed modes obey Navier–Stokes dynamics. The Taylor Reynolds number varies from 140 to 400 and the Schmidt number ($Sc$) varies from 0.25 to 1. By comparing the results with direct numerical simulations (DNS), we show that most statistics are captured with as low as $0.5\,\%$ of Navier–Stokes modes in the velocity field. This includes scalar gradients, spectra, structure functions and their departures from classical scaling due to intermittency. The results suggest that all modes need not be resolved to accurately capture turbulent mixing for $Sc\leqslant 1$ scalars.

An experimental study was conducted to investigate the impingement of a vortex ring onto a porous wall by laser-induced fluorescence and particle image velocimetry. The effects of different Reynolds numbers (${{Re}}_{\it\Gamma } = 700$ and $1800$) and hole diameters ($d_{h}^{*} = 0.067$, $0.10$, $0.133$ and $0.20$) on the flow characteristics were examined at a constant porosity ($\phi = 0.75$). To characterise fluid transport through a porous wall, we recall the model proposed by Naaktgeboren, Krueger & Lage (2012, J. Fluid Mech., vol. 707, 260–286), which shows rough agreement with the experimental results due to the absence of vortex ring characteristics. This highlights the need for a more accurate model to correlate the losses in kinetic energy ($\Delta E^{*}$) and impulse ($\Delta I^{*}$) resulting from the vortex ring–porous wall interaction. Starting from Lamb’s vortex ring model and considering the flow transition from the upstream laminar state to the downstream turbulent state caused by the porous wall disturbance, a new model is derived theoretically: $\Delta E^{*} = 1 - k(1 - \Delta I^{*})^2$, where $k$ is a parameter dependent on the dimensionless core radius $\varepsilon$, with $k = 1$ when no flow state change occurs. This new model effectively correlates $\Delta E^{*}$ and $\Delta I^{*}$ across more than 70 cases from current and previous experiments, capturing the dominant flow physics of the vortex ring–porous wall interaction.

We investigate flow-induced choking in soft Hele-Shaw cells comprising a fluid-filled gap in between a rigid plate and a confined block of elastomer. Fluid injected from the centre of the circular rigid plate flows radially outwards, causing the elastomeric block to deform, before exiting through the cell rim. The pressure in the fluid deforms the elastomer, increasing the size of the gap near the inlet, and decreasing the gap near the cell rim, because of volume conservation of the solid. At a critical injection flow rate, the magnitude of the deformation becomes large enough that the flow is occluded entirely at the rim. Here, we explore the influence of elastomer geometry on flow-induced choking and, in particular, the case of a thick block with radius smaller than its depth. We show that choking can still occur with small-aspect-ratio elastomers, even though the confining influence of the back wall that bounds the elastomer becomes negligible; in this case, the deformation length scale is set by the radial size of the cell rather than the depth of the block. Additionally, we reveal a distinction between flow-induced choking in flow-rate-controlled flows and flow-rate-limiting behaviour in pressure-controlled flows.

This study uses the diffusion analogy (Miyake, Sci. Rep., 5R-6, 1965, Univ. of Washington, Seattle, USA) to predict the full growth behaviour of internal boundary layers (IBLs) induced by a roughness change for neutrally – and especially stably – stratified boundary layers with finite thickness. The physics of the diffusion analogy shows that the streamwise variation of the IBL thickness is dictated by $\sigma _w/U$ at the interface, where $\sigma _w$ and $U$ represent wall-normal Reynolds stress and mean streamwise velocity, respectively. The existing variants of the model, summarised by Savelyev & Taylor (2005, Boundary-Layer Meteorol., vol. 115, pp. 1–25), are tailored to IBLs confined within the constant shear stress layer. To extend the applicability of the model to the outer region, we investigate the relation between $\sigma _w/U$ and $U/U_\infty$ in the outer region across varying stratification, where $U_\infty$ is the free-stream velocity. Our analysis reveals that wind tunnel data from a number of facilities collapse onto a master curve when $\sigma _w/U$ is premultiplied by a height-independent parameter, which is a function of the ratio of Monin–Obukhov length to the boundary layer thickness. The scaled $\sigma _w/U$ decreases inversely with $U/U_\infty$ in the surface layer, transitioning to a linear decrease as $U/U_\infty$ increases. The new model, which integrates these findings, along with the effects of streamline displacement and acceleration, captures the complete characteristics of IBLs as they develop within turbulent boundary layers of finite thickness.

Turbulent flows exhibit large intermittent fluctuations from inertial to dissipative scales, characterised by multifractal statistics and breaking the statistical self-similarity. It has recently been proposed that the Navier–Stokes turbulence restores a hidden form of scale invariance in the inertial interval when formulated for a dynamically (nonlinearly) rescaled quasi-Lagrangian velocity field. Here we show that such hidden self-similarity extends to the large-eddy-simulation (LES) approach in computational fluid dynamics (CFD). In particular, we show that classical subgrid-scale models, such as implicit or explicit Smagorinsky closures, respect the hidden scale invariance at all scales – both resolved and subgrid. In the inertial range, they reproduce the hidden scale invariance of Navier–Stokes statistics. These properties are verified very accurately by numerical simulations and, beyond CFD, turn LES into a valuable tool for fundamental turbulence research.

Viscous fingering is a hydrodynamic instability typically occurring when a less viscous fluid displaces a more viscous one and which deforms the interface between the two fluids into finger-shaped intrusions. For miscible fluids, the fingering pattern is usually followed visually by adding a passive dye into one of the two fluids. The reverse displacement of a less viscous fluid by a more viscous one is classically stable, featuring a planar interface. Here, we show experimentally that in some cases, the dye can actively modify the viscosity of a polymer solution and trigger fingering in the reverse displacement. This dye-induced destabilisation is shown to be due to double-diffusive effects triggering a non-monotonic viscosity profile with a maximum because the dye diffuses faster than the polymer.

This study investigated the cylindrically divergent Rayleigh–Taylor instability (RTI) on a liquid–gas interface and its dependence on initial conditions. A novel hydrophobic technique was developed to generate a two-dimensional water–air interface with controlled initial conditions. The experimental configuration utilised high-pressure air injection to produce uniform circumferential acceleration. Amplitude measurements over time revealed that the cylindrical RTI growth depends strongly on the azimuthal wavenumber. Experimental results demonstrated that surface tension significantly suppresses the liquid–gas cylindrical RTI, even inducing a freeze-out and oscillatory perturbation growth – a phenomenon observed for the first time. Spectrum analysis of the interface contours demonstrated that the cylindrical RTI evolves in a weakly nonlinear regime. Linear and weakly nonlinear models were derived to accurately predict the time-varying interface amplitudes and high-order modes. The linear model was further used to determine conditions for unstable, freeze-out and oscillatory solutions of the cylindrically divergent RTI. These findings offer valuable insights into manipulating hydrodynamic instabilities in contracting/expanding geometries using surface tension.

Turbulence closures are essential for predictive fluid flow simulations in both natural and engineering systems. While machine learning offers promising avenues, existing data-driven turbulence models often fail to generalise beyond their training datasets. This study identifies the root cause of this limitation as the conflation of generalisable flow physics and dataset-specific behaviours. We address this challenge using symbolic regression, which yields interpretable, white-box expressions. By decomposing the learned corrections into inner-layer, outer-layer and pressure-gradient components, we isolate universal physics from flow-specific features. The model is trained progressively using high-fidelity datasets for plane channel flows, zero-pressure-gradient turbulent boundary layers (ZPGTBLs), and adverse pressure-gradient turbulent boundary layers (PGTBLs). For example, direct application of a model trained on channel flow data to ZPGTBLs results in incorrect skin friction predictions. However, when only the generalisable inner-layer component is retained and combined with an outer-layer correction specific to ZPGTBLs, predictions improve significantly. Similarly, a pressure-gradient correction derived from PGTBL data enables accurate modelling of aerofoil flows with both favourable and adverse pressure gradients. The resulting symbolic corrections are compact, interpretable, and generalise across configurations – including unseen geometries such as aerofoils and Reynolds numbers outside the training set. The models outperform baseline Reynolds-averaged Navier–Stokes closures (e.g. the Spalart–Allmaras and shear stress transport models) in both a priori and a posteriori tests. These results demonstrate that explicit identification and retention of generalisable components is key to overcoming the generalisation challenge in machine-learned turbulence closures.