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Objective: The flow downstream from aortic stenoses is characterised by the onset of shear-induced turbulence that leads to irreversible pressure losses. These extra losses represent an increased resistance that impacts cardiac efficiency. A novel approach is suggested in this study to accurately evaluate the pressure gradient profile along the aorta centreline using modelling of haemodynamic stress at scales that are smaller than the typical resolution achieved in experiments. Methods: We use benchmark data obtained from direct numerical simulation (DNS) along with results from in silico and in vitro three-dimensional particle tracking velocimetry (3D-PTV) at three voxel sizes, namely 750 $\mu$ m, 1 mm and 1.5 mm. A differential equation is derived for the pressure gradient, and the subvoxel-scale (SVS) stresses are closed using the Smagorinsky and a new refined model. Model constants are optimised using DNS and in silico PTV data and validated based on pulsatile in vitro 3D-PTV data and pressure catheter measurements. Results: The Smagorinsky-based model was found to be more accurate for SVS stress estimation but also more sensitive to errors especially at lower resolution, whereas the new model was found to more accurately estimate the projected pressure gradient even for larger voxel size of 1.5 mm albeit at the cost of increased sensitivity at this voxel size. A comparison with other methods in the literature shows that the new approach applied to in vitro PTV measurements estimates the irreversible pressure drop by decreasing the errors by at least 20%. Conclusion: Our novel approach based on the modelling of subvoxel stress offers a validated and more accurate way to estimate pressure gradient, irreversible pressure loss and SVS stress. Significance: We anticipate that the approach may potentially be applied to image-based in vivo , in vitro 4D flow data or in silico data with limited spatial resolution to assess pressure loss and SVS stresses in disturbed aortic blood flow.

Bacteria and phytoplankton are abundant in aquatic environments, forming the base of the food web and mediating elemental cycling at a global scale. Understanding the interactions these microorganisms have with their turbulent fluid environments is an active area of research, largely conducted in laboratory-based flow experiments. In this work, we provide an open-source design and rigorous flow characterization for a 1L, dual oscillating grid turbulence facility, the smallest volume facility to date which produces near-isotropic, homogeneous turbulence. We optimized the tank geometry (grid-to-grid and grid-to-wall spacing), the grid geometry (for both classical and fractal grids: effective mesh size, blockage ratio, and fractal grid parameters), and the grid forcing regimes (for both coupled, antiphase and decoupled, randomized forcing: frequency range, stroke range, and randomized forcing parameters) to minimize mean flows and to produce acceptably homogeneous and isotropic turbulence within the unique constraints of a litre-scale volume. We acquired particle image velocimetry (PIV) measurements for both classical and fractal grids across a wide range of grid forcing regimes. We discuss the resulting length- and timescales relevant to microorganism-flow interactions, from the integral to the Kolmogorov scales. Finally, we discuss how the range of turbulent kinetic energy (TKE) dissipation rates achieved across the operational space of the facility mimics oceanographic turbulence in a range of in situ conditions, from the nearshore to the open ocean. This facility meets a long-standing need in the oceanography community in which feasible experimental working volumes are constrained by labor-intensive culturing requirements for large volumes of aquatic bacteria and phytoplankton.

Finding mating partners can be challenging for copepods: the ocean is vast and turbulent, the average animal's concentration is sparse, and their swimming ability is limited. Therefore, the probability for locating a mate assuming a homogeneous distribution of animals and a random motion leads to low mating encounter rates. However, zooplankton distribution is not homogeneous; field observations since the 1950s have shown that plantkon have patchy distributions over multiple scales - from thousand of kilometers down to the millimeter scale1. Of relevance to mating is patchiness at small scales (on the order of the animal's size), leading to increased probability for sexual encounters due to higher local concentrations. Indeed, such mating clusters have been identified in ship transect observations2. However, how such clusters form in the diffusive turbulent environment is not fully understood.In certain species, males actively search for females to achieve sexual encounters. When a male locates a female it pursuits her to achieve contact3, and this behavior is thought to drive small-scale clustering4. Nevertheless, the details of this process are not so straightforward. Specifically, the random swimming pattern males perform in their search, and the (super) diffusive nature of turbulence5, both increases the animals' dispersion, thus opposing patch formation. Therefore, the existence of mating clusters requires a detailed balance between diffusion and pair-interactions. However, this equilibrium in zooplankton patch formation was not examined in the past. Our study examines the equilibrium between diffusion and pair-interactions in zooplankton. Specifically, we have formulated a numerical framework, the pair-interaction model, which allows to study patch formation. Remarkably, we observe that pair-interactions can lead to patches of numerous particles, similar to the field observations2. We thus explore the model's parameter space, to reveal what is required for patchiness to be sustained. Furthermore, we compare our model's results with laboratory measurements of calanoid copepod trajectories3 and show good agreement between the model and the experiment. Our results support the hypothesis that small-scale patchiness is driven by the animal's behavior and thus explain the details of how zooplankton achieve high mating encounter rates in their complex environment. 1 B. Pinel-Alloul and A. Ghadouani (2007). Spatial heterogeneity of planktonic microorganisms in aquatic systems, Springer Netherlands, Dordrecht.2 C. S. Davis, S. M. Gallager and A. R. Solow (1992). Science 257, 230-232. 3 F.-G. Michalec et al. (2017). Proc. Natl. Acad. Sci. U.S.A. 114 ; F.-G. Michalec et al. (2020). eLife 9, e62014.4 C. L. Folt and C. W. Burns (1999). Trends in Ecology and Evolution, 14, 300–305.5 J. P. Salazar and L. R. Collins (2009). Ann. Rev. Fluid Mech. 41, 405-432.

Bacterial biofilms can form in porous media that are of interest in industrial and particularly environmental applications such as in situ groundwater remediation. The presence of biofilms modifies pore-scale and bulk hydrodynamics and consequently solutes transport and reaction kinetics. Porous media consist of highly heterogeneous flow fields and thus biofilm growth is also highly variable resulting in spatially variable biofilm permeabilities. Random processes are often invoked in hydrogeology to model variable quantities. Geo-statistical simulations require numerous realizations of a stochastic process over a grid. Our study leverages highly resolved three-dimensional X-ray computed microtomography images of bacterial biofilms in a tubular reactor to numerically compute pore scale flow and solute transport on a fine grid by considering various realizations of the biofilm permeability field. Using a conservative tracer experiment we first validate our flow and transport model which is then used to understand the impact of a heterogeneous permeability field on fluid-fluid and biologically driven reactions.

We propose and validate a novel experimental technique to measure two-point statistics of turbulent flows. It consists of spreading rigid fibers in the flow and tracking their position and orientation in time and is therefore named “fiber tracking velocimetry.” By choosing different fiber lengths, i.e., within the inertial or dissipative range of scales, the statistics of turbulence fluctuations at the selected length scale can be probed accurately by simply measuring the fiber velocity at its two ends and projecting it along the transverse-to-fiber direction. By means of fully resolved direct numerical simulations and experiments, we show that these fiber-based transverse velocity increments are statistically equivalent to the (unperturbed) flow transverse velocity increments. Moreover, we show that the turbulent energy-dissipation rate can be accurately measured exploiting sufficiently short fibers. The technique is tested against standard particle tracking velocimetry (PTV) of flow tracers with excellent agreement. Our technique overcomes the well-known problem of PTV to probe two-point statistics reliably because of the fast relative diffusion in turbulence that prevents the mutual distance between particles to remain constant at the length scale of interest. This problem, making it difficult to obtain converged statistics for a fixed separation distance, is even more dramatic for natural flows in open domains. A prominent example is oceanic currents, where drifters (i.e., the tracer-particle counterpart used in field measurements) disperse quickly, but at the same time their number has to be limited to save costs. Inspired by our laboratory experiments, we propose pairs of connected drifters as a viable option to solve the issue., Physical Review X, 11 (3), ISSN:2160-3308

We present a novel stochastic model for quantifying gross solids (GS) physical disintegration under varying turbulent flow conditions and used a unique experimental setup for model calibration and validation. The stochastic deterioration model predicts faeces size evolution over time. It conceptually entails the two main processes of solid fragmentation, namely breakage and erosion. Model parameters were calibrated on synthetic faeces and validated with real human ones. A cylindrical reactor was used, where turbulent flow was forced by an array of water jets and the physical disintegration of the faeces was monitored using a high speed camera. Image analysis of breakage experiments obtained under backlight illumination allowed determination of the evolution of the solids' size over time. The flow field in the reactor was characterised by particle image velocimetry (PIV) using tracer particles seeded into the water. We found different disintegration behaviours depending on turbulence intensity and water content of the solid. In conditions of low shear stress, dense solids hardly disintegrated. Generally, the model predictions mirrored the broad range in the solids disintegration rate imparted by the high variability in flow conditions and in solids characteristics. It is expected that, similar to our experiments, also in real sewer systems both flow conditions and solid characteristics are highly variable and the stochastic model can be tailored to capture this variability. We thus anticipate that the model can be integrated into existing sewer models predicting sewer flows and solids' movement. From these, shear stress, flow velocities and transport of individual solids can be inferred. The integration of the present solids disintegration model may provide better predictions of hot-spots for solids accumulation and blockages in sewers.

Hedgehog (HH) signaling is important for embryonic pattering and stem cell differentiation. The G protein-coupled receptor (GPCR) Smoothened (SMO) is the key HH signal transducer modulating both transcription-dependent and transcription-independent responses. We show that SMO protects naive mouse embryonic stem cells (ESCs) from dissociation-induced cell death. We exploited this SMO dependency to perform a genetic screen in haploid ESCs where we identify the Golgi proteins TMED2 and TMED10 as factors for SMO regulation. Super-resolution microscopy shows that SMO is normally retained in the endoplasmic reticulum (ER) and Golgi compartments, and we demonstrate that TMED2 binds to SMO, preventing localization to the plasma membrane. Mutation of TMED2 allows SMO accumulation at the plasma membrane, recapitulating early events after HH stimulation. We demonstrate the physiologic relevance of this interaction in neural differentiation, where TMED2 functions to repress HH signal strength. Identification of TMED2 as a binder and upstream regulator of SMO opens the way for unraveling the events in the ER-Golgi leading to HH signaling activation.

We examine the validity of the commonly used Hagen-Poiseuille model of local resistance of porous media using direct numerical simulations. We provide theoretical arguments that highlight possible limitations of this model and formulate a new constitutive model that is based on the circularity of iso-pressure surfaces. We compare the performance of both models on three different three-dimensional artificial porous media. We show that the new model improves the root-mean-squared-relative error from 59%, 48% and 32% for the HP model to 12%, 14% and 18% for the three porous media respectively. We anticipate that our approach may find broad application in network models of porous media that are typically build from 3D images with intricate pore geometries., Geophysical Research Letters, 48 (22), ISSN:0094-8276, ISSN:1944-8007

Experimental and numerical approaches have their own advantages and limitations, in particular, when dealing with complex phenomena such as snow particles falling at moderate Reynolds numbers (Re). Time-resolved, three-dimensional particle tracking velocimetry (4D-PTV) experiments of free-falling, three-dimensional (3D)-printed snowflakes' analogs shed light on the elaborate falling dynamics of irregular snow particles but present a lower resolution (tracer seeding density) and a limited field of view (domain size) to fully capture the wake flow. Delayed-detached eddy simulations of fixed snow particles do not realistically represent all the physics of a falling ice particle, especially for cases with unsteady falling attitudes, but accurately predict the drag coefficient and capture the wake characteristics for steadily falling snowflakes. In this work, we compare both approaches on time- and space-averaged flow quantities in the snowflake wake. First, we cross validate the two approaches for low Re cases, where close agreement of the wake features is expected, and second, we assess how strongly the unsteady falling motion perturbs the average wake pattern as compared to a fixed particle at higher Re. For steadily falling snowflakes, the fixed-particle model can properly represent the wake flow with errors within the experimental uncertainty (+/-;15%). At moderate/high Re (unsteady falling motion), larger differences are present. Applying a co-moving frame to the experimental data to account for the particle movement or filtering the numerical data on larger grids reduces these differences only to some extent, implying that an unsteady fall significantly alters the average wake structure as compared to a fixed particle model., Physics of Fluids, 34 (5), ISSN:1070-6631, ISSN:1089-7666, ISSN:0031-9171

Turbulent mixing layers in nature are often characterised by the presence of a mean shear and an unstable buoyancy gradient between two streams of different velocities. Depending on the relative strength of shear versus buoyancy, either the former or the latter may dominate the turbulence and mixing between the two streams. In this paper, we present a phenomenological theory that leads to the identification of two distinct turbulent regimes: an early regime, dominated by mean shear, and a later regime dominated by buoyancy. The main theoretical result consists of the identification of a cross-over timescale that distinguishes between the shear- and the buoyancy-dominated turbulence. This cross-over time depends on three large-scale constants of the flow, namely, the buoyancy difference, the velocity difference between the two streams and the gravitational acceleration. We validate our theory against direct numerical simulations of a temporal turbulent mixing layer compounded with an unstable stratification. We observe that the cross-over time correctly predicts the transition from shear- to buoyancy-driven turbulence, in terms of turbulent kinetic energy production, energy spectra scaling and mixing layer thickness., Journal of Fluid Mechanics, 924, ISSN:0022-1120, ISSN:1469-7645

The surface area of turbulent/non-turbulent interfaces (TNTIs) is continuously produced and destroyed via stretching and curvature/propagation effects. Here, the mechanisms responsible for TNTI area growth and destruction are investigated in a turbulent flow with and without stable stratification through the time evolution equation of the TNTI area. We show that both terms have broad distributions and may locally contribute to either production or destruction. On average, however, the area growth is driven by stretching, which is approximately balanced by destruction by the curvature/propagation term. To investigate the contribution of different length scales to these processes, we apply spatial filtering to the data. In doing so, we find that the averages of the stretching and the curvature/propagation terms balance out across spatial scales of TNTI wrinkles and this scale-by-scale balance is consistent with an observed scale invariance of the nearby coherent vortices. Through a conditional analysis, we demonstrate that the TNTI area production (destruction) is localized at the front (lee) edge of the vortical structures in the interface proximity. Finally, we show that while basic mechanisms remain the same, increasing stratification reduces the rates at which TNTI surface area is produced as well as destroyed. We provide evidence that this reduction is largely connected to a change in the multiscale geometry of the interface, which tends to flatten in the wall-normal direction at all active length scales of the TNTI.

We compute the resistance matrices of realistic 3-D snow particle shapes obtained from microcomputed tomography data of snowpack samples and a phase field model. Using these resistance matrices, we calculate the sedimentation of the particles in still air in Stokes regime. We find that particles attain preferred orientations and the mode of motion is either drifting or spiraling. Simple laws, relating average drag and rotation torque coefficients to the particles' sphericity, are established which lead to a new formulation of a snow particle's average terminal velocity. The presented models are valid in Stokes regime in still air, corresponding to particle sizes up to ∼100 μm but can reasonably be extended to moderately higher Reynolds numbers (∼1 mm) and used for estimating mean settling velocity in turbulent conditions. Though not all relevant atmospheric conditions are covered, our study provides the basis for addressing more complex conditions in the future. © 2020 American Geophysical Union. ISSN:0094-8276 ISSN:1944-8007

The above mentioned article was submitted with incorrect author affiliations for George Haller and Markus Holzner. This has since been rectified in the online PDF and HTML copies. (J. Fluid Mech. (2020) 898 (A3) DOI: 10.1017/jfm.2020.414)

In this paper, we investigate the enstrophy dynamics in relation to objective Eulerian coherent structures (OECSs) and their impact on the enstrophy and scalar transport near the turbulent/non-turbulent interface (TNTI) in flows with and without stable stratification. We confirm that vortex-stretching produces enstrophy inside the boundaries of the OECSs, while viscous diffusion transfers the enstrophy across the boundaries of the structures. Although often overlooked in the literature, viscous dissipation of enstrophy within the boundaries of vortical structures is significant. Conversely, for the weakly stratified flows also investigated here, the effect of the baroclinic torque is negligible. We provide evidence that the OECSs advect the passive/active scalar and redistribute it via molecular diffusion. Finally, we use conditional analysis to show that the typical profiles of the enstrophy and scalar transport equation terms across the TNTI are compatible with the presence of OECSs positioned at the edge between the turbulent sublayer and the turbulent core region. We show that when these profiles are further conditioned to the presence of OECSs, their magnitude is considerably higher.

We derive a theory for material surfaces that maximally inhibit the diffusive transport of a dynamically active vector field, such as the linear momentum, the angular momentum or the vorticity, in general fluid flows. These special material surfaces (\emph{Lagrangian active barriers}) provide physics-based, observer-independent boundaries of dynamically active coherent structures. We find that Lagrangian active barriers evolve from invariant surfaces of an associated steady and incompressible \emph{barrier equation}, whose right-hand side is the time-averaged pullback of the viscous stress terms in the evolution equation for the dynamically active vector field. Instantaneous limits of these barriers mark objective \emph{Eulerian active barriers} to the short-term diffusive transport of the dynamically active vector field. We obtain that in unsteady Beltrami flows, Lagrangian and Eulerian active barriers coincide exactly with purely advective transport barriers bounding observed coherent structures. In more general flows, active barriers can be identified by applying Lagrangian coherent structure (LCS) diagnostics, such as the finite-time Lyapunov exponent and the polar rotation angle, to the appropriate active barrier equation. In comparison to their passive counterparts, these \emph{active LCS diagnostics} require no significant fluid particle separation and hence provide substantially higher-resolved Lagrangian and Eulerian coherent structure boundaries from temporally shorter velocity data sets. We illustrate these results and their physical interpretation on two-dimensional, homogeneous, isotropic turbulence and on a three-dimensional turbulent channel flow., 50 pages, 40 figures, to be published in J. Fluid. Mech

Flow fields in rotary blood pumps (RBPs) have a significant influence on hemocompatibility. Because flow characteristics vary with flow rate, different operating conditions play a role. Furthermore, turbulence is crucial in the evaluation of blood damage potential, but the level of turbulence in implantable RBPs is still unknown. In this study, we addressed both research aspects and for the first time measured turbulent flow fields in the HeartMate 3 (HM3) at different operating flows. The averaged, three-dimensional velocity field including fluctuating velocity components in a HM3 with a transparent lower housing was measured using three-dimensional particle tracking velocimetry (3D-PTV). In vitro results were compared with computational fluid dynamic (CFD) simulations for two flow cases, representing the lower and upper physiologic flow range (2.7 and 5.7 L/min), using two different turbulence models that account for fluctuating velocity fields: the k-ω shear stress transport and the Reynolds stress model (RSM). The measurements revealed higher mean and turbulent kinetic energies (TKEs) for the low-flow condition especially within the gap beneath the impeller. Computed mean fields agree well with 3D-PTV for both models, but the RSM predicts the TKE levels better than the k-ω model. Computational fluid dynamic results further show wall shear stresses higher than 150 Pa, a commonly used damage threshold, in the bottom gap for the lower flow condition. In conclusion, the low-flow condition was found to be more prone to blood damage. Furthermore, CFD predictions for turbulence must be carefully experimentally validated.

We investigate three-dimensional pulsatile aortic flow in the ascending aorta with mechanical prosthetic aortic valve implanted at two different orientations under physiological flow conditions using an anatomically accurate aorta. We perform 3D Particle Tracking Velocimetry measurements to assess the phase averaged and fluctuating velocity patterns as well as the shear stresses. A St Jude Medical prosthetic heart valve is implanted in an anatomically accurate silicone model of an aorta obtained from high resolution magnetic resonance imaging of a healthy proband at two different orientations. Our results show that the mechanical prosthetic valve orientation has considerable impact on the local kinetic energy and shear stress distributions but minor effects on the spatially averaged kinetic energy (10%) and shear stresses (15%). We show that the valve orientation plays a distinct role in spatial distribution of wall shear stresses and vortical structures. We show that our results, which show good agreement with the in silico and in vitro studies in the literature, provide full 3D kinetic energy and shear stress information over the entire cardiac cycle for different bileaflet prosthetic valve orientations under physiological flow conditions.

An aortic aneurysm is defined as a balloon-shaped bulging of all three histologic components of the aortic vessel walls (intima, media and adventitia). This dilation results from vessel weakening owing to remodeling, i.e. due to cystic degeneration of the Tunica media (Marfan), progression of atherosclerosis or presence of a bicuspid aortic valve. The growth rate of the aortic diameter varies from patient to patient and may progress until the aneurysm ultimately ruptures. The role of hemodynamics, i.e. blood flow patterns, and shear stresses that are supposed to intensify during aneurysm growth are not yet fully understood, but thought to play a key role in the enlargement process. The aim of this study is to characterize the aortic blood flow in a silicone model of a pathological aorta with ascending aneurysm, to analyze the differences in the blood flow pattern compared to a healthy aortic model, and to single out possible blood flow characteristics measurable using phase contrast magnetic resonance imaging (MRI) that could serve as indicators for aneurysm severity. MRI simulations were performed under physiological, pulsatile flow conditions using data obtained from optical three dimensional particle tracking measurements. In comparison to the healthy geometry, elevated turbulence intensity and pressure loss are measured in the diseased aorta, which we propose as a complimentary indicator for assessing the aneurysmal severity. Our results shed a light on the interplay between the blood flow dynamics and their contribution to the pathophysiology and possible role for future risk assessment of ascending aortic aneurysms.

© 2018 Elsevier Ltd This study investigates the functional correspondence between porescale hydrodynamics, mass transfer, pore structure and biofilm morphology during progressive biofilm colonization of a porous medium. Hydrodynamics and the structure of both the porous medium and the biofilm are experimentally measured with 3D particle tracking velocimetry and micro X-ray Computed Tomography, respectively. The analysis focuses on data obtained in a clean porous medium after 36 h of biofilm growth. Registration of the particle tracking and X-ray data sets allows to delineate the interplay between porous medium geometry, hydrodynamic and mass transfer processes on the morphology of the developing biofilm. A local analysis revealed wide distributions of wall shear stresses and concentration boundary layer thicknesses. The spatial distribution of the biofilm patches uncovered that the wall shear stresses controlled the biofilm development. Neither external nor internal mass transfer limitations were noticeable in the considered system, consistent with the excess supply of nutrient and electron acceptors. The wall shear stress remained constant in the vicinity of the biofilm but increased substantially elsewhere.

Climate model parametrization relies strongly on the prediction of snow precipitation, which in turn depends upon the snowflakes falling motion in air. The falling attitudes of such particles are elaborate because of the particles' irregular shapes, which produce meandering and turbulent wakes and give rise to convoluted trajectories. This also has an impact on the drag experienced by the particle. Especially for large snow particles falling close to the ground, Stokesian dynamics is not applicable, and the dependency of drag coefficient on Reynolds number becomes non-linear. This trend arises from the complex interaction between snowflakes and the surrounding air. We investigate the wake of complex-shaped snow particles using a validated delayed-detached eddy simulation model of airflow around a fixed snowflake, combined with experimental observations of free-falling, 3D-printed snowflake analogs. This novel approach allows us to analyze the wake topology and decompose its momentum flux to investigate the influence of shape and wake flow on the drag coefficient and its implications on falling attitudes by comparison with experiments. At low Re, the presence of separated vortex rings is connected to particle porosity and produces an increase in the drag coefficient. At moderate flow regimes, the particle flatness impacts the shear layer separation and the momentum loss in the wake, while at high Re the drag coefficient has almost the same value among the tested geometries although the contribution of different momentum flux terms differs. These results represent a further step toward a deeper understanding the drag of complex-shaped particles.

Significance Zooplankton possess narrow swimming capabilities, yet are capable of active locomotion amid turbulence. By decoupling the relative velocity of swimming zooplankton from that of the underlying flow, we provide evidence for an active adaptation that allows these small organisms to modulate their swimming effort in response to background flow. This behavioral response results in reduced diffusion at substantial turbulence intensity. Adjusting motility provides fitness advantage because it enables zooplankton to retain the benefits of self-locomotion despite the constraints enforced by turbulence transport. Vigorous swimming and reduced diffusion oppose turbulence advection, can directly affect the dispersal of zooplankton populations, and may help these organisms to actively control their distribution in dynamic environments., Calanoid copepods are among the most abundant metazoans in the ocean and constitute a vital trophic link within marine food webs. They possess relatively narrow swimming capabilities, yet are capable of significant self-locomotion under strong hydrodynamic conditions. Here we provide evidence for an active adaptation that allows these small organisms to adjust their motility in response to background flow. We track simultaneously and in three dimensions the motion of flow tracers and planktonic copepods swimming freely at several intensities of quasi-homogeneous, isotropic turbulence. We show that copepods synchronize the frequency of their relocation jumps with the frequency of small-scale turbulence by performing frequent relocation jumps of low amplitude that seem unrelated to localized hydrodynamic signals. We develop a model of plankton motion in turbulence that shows excellent quantitative agreement with our measurements when turbulence is significant. We find that, compared with passive tracers, active motion enhances the diffusion of organisms at low turbulence intensity whereas it dampens diffusion at higher turbulence levels. The existence of frequent jumps in a motion that is otherwise dominated by turbulent transport allows for the possibility of active locomotion and hence to transition from being passively advected to being capable of controlling diffusion. This behavioral response provides zooplankton with the capability to retain the benefits of self-locomotion despite turbulence advection and may help these organisms to actively control their distribution in dynamic environments. Our study reveals an active adaptation that carries strong fitness advantages and provides a realistic model of plankton motion in turbulence.

©2017. American Geophysical Union. All Rights Reserved. We study the evolution of velocity in time, which fundamentally controls the way dissolved substances are transported and spread in porous media. Experiments are conducted that use tracer particles to track the motion of substances in water, as it flows through transparent, 3-D synthetic sandstones. Particle velocities along streamlines are found to be intermittent and strongly correlated, while their probability density functions are lognormal and nonstationary. We demonstrate that these particle velocity characteristics can be explained and modeled as a continuous time random walk that is both Markovian and mean reverting toward the stationary state. Our model accurately captures the fine-scale velocity fluctuations observed in each tested sandstone, as well as their respective dispersion regime progression from initially ballistic, to superdiffusive, and finally Fickian . Model parameterization is based on the correlation length and mean and standard deviation of the velocity distribution, thus linking pore-scale attributes with macroscale transport behavior for both short and long time scales.

We investigate the effect of buoyancy on the small-scale aspects of turbulent entrainment by performing direct numerical simulation of a gravity current and a wall jet. In both flows, we detect the turbulent/nonturbulent interface separating turbulent from irrotational ambient flow regions using a range of enstrophy iso-levels spanning many orders of magnitude. Conform to expectation, the relative enstrophy isosurface velocity vn in the viscous superlayer scales with the Kolmogorov velocity for both flow cases. We connect the integral entrainment coefficient E to the small-scale entrainment and observe excellent agreement between the two estimates throughout the viscous superlayer. The contribution of baroclinic torque to vn is negligible, and we show that the primary reason for reduced entrainment in the gravity current as compared to the wall-jet are 1) the reduction of vn relative to the integral velocity scale uT; and 2) the reduction in the surface area of the isosurfaces., Environmental Fluid Mechanics, 18 (1), ISSN:1567-7419, ISSN:1573-1510

Zooplankton live in dynamic environments where turbulence may challenge their limited swimming abilities. How this interferes with fundamental behavioral processes remains elusive. We reconstruct simultaneously the trajectories of flow tracers and calanoid copepods and we quantify their ability to find mates when ambient flow imposes physical constrains on their motion and impairs their olfactory orientation. We show that copepods achieve high encounter rates in turbulence due to the contribution of advection and vigorous swimming. Males further convert encounters within the perception radius to contacts and then to mating via directed motion toward nearby organisms within the short time frame of the encounter. Inertial effects do not result in preferential concentration, reducing the geometric collision kernel to the clearance rate, which we model accurately by superposing turbulent velocity and organism motion. This behavioral and physical coupling mechanism may account for the ability of copepods to reproduce in turbulent environments., eLife, 9, ISSN:2050-084X