CyberSec Research

Dinoflagellates are marine phytoplankton that emit flashes of light in response to flow-induced deformation; they are responsible for illuminating breaking-waves, wakes of ships, and other intensely turbulent spots of the upper ocean. Here, we ask how bioluminescence is affected by the fluctuating nature of turbulence -- a question motivated by the dependence of emitted flashes on both the extent and rate of deformation. Introducing a light-emitting dumbbell as a minimal model, we study the Lagrangian dynamics of flashing in a homogeneous isotropic turbulent flow, and contrast it with that in an extensional flow and a Gaussian random flow. We show that turbulent fluctuations strongly enhance bioluminescence, while introducing a Poisson-like stochasticity in the flashing dynamics. Furthermore, the intermittent fluctuations of the velocity-gradient subjects the dinoflagellate to bursts of extreme straining and produces bright flashes -- more intense, though less frequent, than what would result from Gaussian fluctuations. Our results suggest that radiant displays of marine bioluminescence are strongly promoted by turbulence and its dissipation-scale intermittency.

In the present work, Jet A-Hexane binary fuel droplet impact dynamics on heated solid surfaces were studied numerically. This study is crucial for practical applications such as fuel injection in combustors and thermal management of engine components. Volume of fluid (VOF) method was used to analyse the impact dynamics, spreading behaviour, vaporisation, and heat transfer of n-hexane and Jet-A blended fuel droplets on heated stainless-steel surfaces. Droplet impact dynamics were investigated for two Weber numbers, i.e., 25 and 50, and surface temperatures ranging from 50C to 227C to capture transitions from gentle spreading to nucleate boiling and rebound phenomena. This work examines how fuel blending influences inertia, lamella formation, vapour recoil, and film boiling regimes. The results show that higher inertia in blended fuels enhances spreading but also triggers stronger vapour recoil at elevated temperatures, leading to droplet rebound. In contrast, pure hexane transitions to a stable film boiling regime at high surface temperatures, resulting in a decline in smoother heat flux. New correlations were developed linking Weber number, spreading ratio, and wall heat flux, offering predictive insights for real-world combustion scenarios. These findings advance the understanding of bi-component fuel droplet impacts on heated surfaces and provide a framework for designing efficient spray systems in combustors and thermal management in propulsion and power generation applications.

We develop the Kazantsev theory of small-scale dynamo generation at small Prandtl numbers near the generation threshold and restore the concordance between the theory and numerical simulations: the theory predicted a power-law decay below the threshold, while simulations demonstrate exponential decay. We show that the exponential decay is temporary and owes its existence to the flattening of the velocity correlator at large scales. This effect corresponds to the existence of a long-living virtual level in the corresponding Schrodinger type equation. We also find the critical Reynolds number and the increment of growth/decay above and under the threshold; we express them in terms of the quantitative characteristic properties of the velocity correlator, which makes it possible to compare the results with the data of different simulations.

We present a direct inverse modeling method named SURGIN, a SURrogate-guided Generative INversion framework tailed for subsurface multiphase flow data assimilation. Unlike existing inversion methods that require adaptation for each new observational configuration, SURGIN features a zero-shot conditional generation capability, enabling real-time assimilation of unseen monitoring data without task-specific retraining. Specifically, SURGIN synergistically integrates a U-Net enhanced Fourier Neural Operator (U-FNO) surrogate with a score-based generative model (SGM), framing the conditional generation as a surrogate prediction-guidance process in a Bayesian perspective. Instead of directly learning the conditional generation of geological parameters, an unconditional SGM is first pretrained in a self-supervised manner to capture the geological prior, after which posterior sampling is performed by leveraging a differentiable U-FNO surrogate to enable efficient forward evaluations conditioned on unseen observations. Extensive numerical experiments demonstrate SURGIN's capability to decently infer heterogeneous geological fields and predict spatiotemporal flow dynamics with quantified uncertainty across diverse measurement settings. By unifying generative learning with surrogate-guided Bayesian inference, SURGIN establishes a new paradigm for inverse modeling and uncertainty quantification in parametric functional spaces.

The transport of CO2 across the air-water interface plays a critical role in physical oceanography and carbon sequestration. One of the key challenges in understanding such transport processes is their multiscale nature - the spatial and temporal scales of gas- and liquid-phase diffusion, absorption and reaction span over several orders of magnitude, which requires high-resolution diagnostic methods to unravel their detailed dynamics. The current study presents a novel diagnostic method to quantify the CO2 distribution at the air-water interface in a spatially and temporally resolved manner. This method combines the advantages of tunable diode laser spectroscopy and rapid spatial beam scanning for precision measurement of the CO2 concentration profile above the interface. The performance of this method was examined in a series of quasi-1D demonstration experiments conducted in a custom-built miniature gas chamber, where the cross-interface diffusion and absorption of gas-phase CO2 into pure water and alkaline solutions of different pH values were continuously monitored. An effective time resolution of 5 ms and an effective spatial resolution of 1 mm were achieved. The results of the gas-phase CO2 distribution evolution agreed well with the classic one-dimensional diffusion model, which verified the accuracy of the current method. Additionally, an interesting phenomenon was observed regarding the temporal evolution of interfacial CO2 concentration at different pH levels: its depletion rate exhibited strong pH sensitivity at relatively low pH but saturated near pH = 10. This could be attributed to competition between gas-/liquid-phase diffusion and absorption/reaction occurring within the interface layer. The high temporal and spatial resolution of the current method promises to be useful in experimental studies of cross-interface gas transport under more complex flow conditions as well.

This study presents a systematic characterization of burner-stabilized lean hydrogen flame morphology across a wide range of equivalence ratios, dilution factors, and flow rates. Spatially resolved measurements of three-dimensional temperature and OH distributions were achieved. A comprehensive dataset of over 200 flame cases was obtained, enabling accurate determination of regime diagrams for different flame modes. Linear stability analysis and direct numerical simulations were also performed and compared with the experimental results. The dominant wavenumbers of steady-state cellular flames were found to be consistently lower than the most unstable wavenumbers predicted by the linearized dispersion relation, indicating that nonlinear interactions between finite-amplitude perturbations of different length scales favored the growth of low-frequency components at long times. The cellular structures were found to be critically important in stabilizing the flame, especially at nominal equivalence ratios near the lean flammability limit. The mechanism of cellular flame stabilization was analyzed by complementary numerical simulations using a detailed reaction model. The combined effect of curvature-induced flame acceleration, local flow expansion/compression near the burner surface, and stratification of equivalence ratio caused by Soret diffusion created regions of reduced flow speed and enriched hydrogen concentration that helped anchor flames at nominal conditions where they would have blown off without the flame cells. The results of the present study are useful for understanding the fundamental flame dynamics of lean hydrogen mixtures and for improving the design of practical hydrogen combustors.

Uniform flow distribution across parallel channels directly impacts the performance and efficiency of many fluid and energy systems. However, designing efficient flow manifolds that ensure uniform flow distribution remains a challenge. This issue is even more pronounced in the design of multichannel three-dimensional manifolds. Hence, this study presents a scalable topology optimization framework for the systematic design of multi-channel flow manifolds. The proposed method extends the conventional density-based topology optimization formulation by introducing a flow maldistribution coefficient as an explicit constraint. This novel approach was implemented using the incompressible Navier-Stokes flow solver available in the open-source CFD suite SU2. The performance of the proposed method was benchmarked against two established topology optimization strategies using an exemplary planar z-type flow manifold, wherein both the inlet and outlet manifoldswere designed simultaneously. The results demonstrate that the proposed method achieves flow uniformity comparable to that obtained by established approaches while significantly reducing the associated computational cost. Furthermore, when applied to large-scale three-dimensional problems, the proposed method produces feasible designs that achieve uniform flow distribution and exhibit innovative geometrical features. Thus advocating for the robustness and scalability of the proposed method.

The dispersion of Lagrangian particle pairs is a fundamental process in turbulence, with implications for mixing, transport, and the statistical properties of particles in geophysical and environmental flows. While classical theories describe pair dispersion through scaling laws related to energy cascades, extreme events in turbulent flows can significantly alter these dynamics. This is especially important in stratified flows, where intermittency manifests itself also as strong updrafts and downdrafts. In this study, we investigate the influence of extreme events on the relative dispersion of particle pairs in stably stratified turbulence. Using numerical simulations we analyze the statistical properties of pair separation across different regimes, and quantify deviations from classical Richardson scaling. Our results highlight the role of extreme drafts in accelerating dispersion. These findings have important implications for turbulent mixing in natural systems, including atmospheric and oceanic flows, as well as applications in cloud microphysics and pollutant transport.

Generalization of the Chapman-Enskog method to the case of large gradients of hydrodynamic velocity allowed us to obtain an integral (over spatial coordinates) representation of the viscous stress tensor in the Navier-Stokes equation. In the case of small path lengths of the medium disturbance, the tensor goes over to the standard form, which, as is known, is difficult to apply to the description of tangential discontinuities and separated flows. The obtained expression can allow numerical modeling of the nonlocality of turbulence, expressed by the empirical Richardson t^3 law for pair correlations in a turbulent medium.

Vertical equilibrium (VE) models have been introduced as computationally efficient alternatives to traditional mass and momentum balance equations for fluid flow in porous media. Since VE models are only accurate in regions where phase equilibrium holds, while traditional simulations are computationally demanding, hybrid methods have been proposed to combine the accuracy of the full-dimensional approach with the efficiency of VE model. However, coupling both models introduces computational overhead that can make hybrid simulations slower than fully traditional ones. To address this, we introduce data-driven surrogates to predict the gas plume distance and coarse-level mobilities in the VE model, as well as predictors to accelerate the coupling scheme. We focus on surrogate models with short inference times to minimize computational overhead during frequent function calls. The proposed approach preserves key physical properties, such as mass conservation, while substantially reducing simulation runtimes. Overall, combining data-driven methods with the hybrid VE scheme yields an enhanced model that outperforms traditional simulations in speed while introducing only negligible errors.

Classical rupture is attributed to molecular (van der Waals) forces acting at nanometric thicknesses. Nonetheless, micron-thick liquid sheets routinely perforate far above the scale where these molecular forces act, yet the mechanism that selects opening versus healing has remained unclear. Using direct numerical simulations of a draining sheet with an entrained air bubble (cavity), we show that irreversible rupture occurs only when a deterministic double-threshold is crossed: (i) the outward driving (from airflow or inertia) is strong enough and (ii) the cavity is distorted enough. If either condition falls short, surface tension heals the cavity and the sheet reseals. The time for this process is set by the balance between inertia and viscosity -- fast for inertia-dominated sheets and slower for viscous ones. This double-threshold mechanism explains why micrometer-thick films perforate and offers practical control options -- driving strength and defect geometry -- for predicting and controlling breakup in spray formation processes, wave breaking, and respiratory films.

Condensation on vertical surfaces leads to fluid retention, which limits the efficiency of applications ranging from heat exchangers to atmospheric water harvesters. A common strategy is to structure the surface with grooves, yet whether grooves help drainage or worsen retention remains unclear. Here we use a high-throughput condensation setup to quantify retention on substrates patterned with parallel vertical grooves of fixed geometry ($d/w=1$) while varying the spacing $s$. We uncover two opposite regimes separated by the droplet detachment radius $R_d$. For large spacings ($s>R_d$), droplets grow and slide under gravity while grooves, acting as passive reservoirs, increase retention. For small spacings ($s<R_d$), grooves instead trigger active drainage, confining droplet growth and reducing retention to values even lower than on smooth surfaces. Two asymptotic models, a groove-volume reservoir model and a plateau-packing model, capture this transition and explain the scaling of retention with $s$. These findings show that groove spacing controls whether grooves act as drains or reservoirs, providing a simple geometric design rule for tailoring condensation retention in practical systems.

This study examines the relaminarization of turbulent puffs in pipe flow using highly resolved direct numerical simulations at Reynolds numbers of 1880, 1900, and 1920. The exponential decay of the total energy of streamwise velocity fluctuations and the weak dependence of the decay rate on the Reynolds number were verified. In the cross-section of the laminar-turbulent interface at the trailing edge of the puff, an analysis of the spatio-temporal evolution of the streamline patterns reveals a complex topology with saddle-node pairs. In this case, the saddle and the node move toward each other during relaminarization until they collide and vanish. By tracing the vanishing saddle-node pairs over time, we discovered that the distance between the saddle and the node scales as a square root function of time, a generic characteristic of a time-evolving saddle-node bifurcation.

Transonic buffet is a well-known aerodynamic instability of shock/boundary layer interaction in the transonic regime for aircraft. So far, this phenomenon has typically been investigated by modal and correlation analyses. Here, we present a perspective on low-frequency unsteadiness, of the order of St ~ O(-2), in transonic buffet, using results from temporal evolution of skin friction lines and correlation analysis on the surface of Benchmark Supercritical Wing (BSCW) with an aspect ratio AR = 2. Skin friction lines and critical point theory are well established to describe 3D separated flows based on critical points -- nodes, foci, and saddles. Dynamics of these critical points are found in a certain topology in separation regions for different angles of attack, Mach 0.85, and Reynolds number 4.491 million. The topology of critical points consists of pairs of contra-rotating unstable foci that contribute to the mechanism of formation and propagation of buffet cells -- pockets of shock foot oscillations. The dynamic nature of these critical points changes the pressure distribution on the surface, which is reflected as wave propagation in correlation plots.

We develop, simulate and extend an initial proposition by Chaves et al. concerning a random incompressible vector field able to reproduce key ingredients of three-dimensional turbulence in both space and time. In this first article, we focus on the important underlying Gaussian structure that will be generalized in a second article to account for higher-order statistics. Presently, the statistical spatial structure of this velocity field is consistent with a divergence-free fractional Gaussian vector field that encodes all known properties of homogeneous and isotropic fluid turbulence at a given finite Reynolds number, up to second-order statistics. The temporal structure of the velocity field is introduced through a stochastic evolution of the respective Fourier modes. In the simplest picture, Fourier modes evolve according to an Ornstein-Uhlenbeck process, where the characteristic time scale depends on the wave-vector amplitude. For consistency with direct numerical simulations (DNSs) of the Navier-Stokes equations, this time scale is inversely proportional to the wave vector amplitude. As a consequence, the characteristic velocity that governs the eddies is independent of their size and is related to the velocity standard deviation, which is consistent with some features of the so-called sweeping effect. To ensure differentiability in time while respecting the causal nature of the evolution, we use the methodology developed by Viggiano et al. to propose a fully consistent stochastic picture, predicting in particular proper temporal covariance of the Fourier modes. We finally derive analytically all statistical quantities in a continuous setup and develop precise and efficient numerical schemes of the corresponding periodic framework. Both exact predictions and numerical estimations of the model are compared to DNSs provided by the Johns Hopkins database.

In this letter, we characterize quantitatively the complex phenomenon of debubbling via aerophilic membranes by examining local interactions at the scale of single bubbles. We identify three asymptotic limits of evacuation dictated by Rayleigh, Ohnesorge and Darcy dynamics, the physics of which we capture using simple scaling laws. We show that beyond a threshold permeability, bubble evacuations become constant in time - a feature we understand as an inertio-capillary limit. Our experiments reveal that the fastest bubble evacuations require an interface that is nearly a liquid, but not quite.

Slow, viscous flow in branched structures arises in many biological and engineering settings. Direct numerical simulation of flow in such complicated multi-scale geometry, however, is a computationally intensive task. We propose a scattering theory framework that dramatically reduces this cost by decomposing networks into components connected by short straight channels. Exploiting the phenomenon of rapid return to Poiseuille flow (Saint-Venant's principle in the context of elasticity), we compute a high-order accurate scattering matrix for each component via boundary integral equations. These precomputed components can then be assembled into arbitrary branched structures, and the precomputed local solutions on each component can be assembled into an accurate global solution. The method is modular, has negligible cost, and appears to be the first full-fidelity solver that makes use of the return to Poiseuille flow phenomenon. In our two-dimensional examples, it matches the accuracy of full-domain solvers while requiring only a fraction of the computational effort.

We review, critique, and extend results related to the problem of closed loop shape equilibria of a string shooter, a type of catenary consisting of steady, axially moving configurations of an inertial, inextensible, perfectly flexible string in the presence of gravity and drag forces. We highlight recurring misconceptions, and relate to similar problems, including the lariat (no gravity), chain fountain (not closed), and heavy \emph{elastica} (bending stiffness). We focus on the difficulty inherent to continuing a catenary through a vertical orientation, necessary to close a loop, which difficulty changes in nature as the system undergoes bifurcations with increasing drag. We construct solutions by implementing available analytical results, and numerically generate additional solutions with added bending stiffness. We briefly discuss global balances of linear, angular, and pseudo- momentum for this system.