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Particle tracking velocimetry (PTV) is one of the latest and most powerful flow visualization techniques, using numerous cameras to track flow tracers in two or three dimensions. This book provides a review of both experimental and computational aspects of PTV for academic and industrial researchers and engineers.

Transparent exopolymer particles (TEP), a major component of coral mucus, are responsible for particle aggregation. These particles contribute substantially to the carbon cycle in coral reefs, and serve as an energy source for bacteria and other microorganisms. Water flows and induced turbulent mixing control material exchange between the coral canopy and the surrounding water, which is critical for coral health. However, how these factors affect TEP release by coral colonies has yet to be evaluated. Using a recirculating flume, we assessed TEP release by branching Acropora coral colonies and associated bacterial growth in the water column under different unidirectional flows. Changes in TEP and bacterial concentrations after 24-h incubation were quantified for flow speeds of 0, 5, 10, and 30 cm/s. Particle image velocimetry (PIV) measurements provided an estimate of turbulent mixing efficiency above the coral canopy. TEP and bacterial concentrations in the water column increased after 24 h of incubation. The increase in TEP and bacterial concentrations were 6.2–9.3 times and 3.4–5.1 times higher in the absence of flows, respectively, than mean values under water flows. Although mixing efficiency increased linearly with mean flow speeds, TEP release and bacterial growth differed only marginally at flows ranging from 5–30 cm/s. Detailed flow measurements combined with evaluation of TEP release suggest that the complex geometry of corals facilitates efficient material exchange at a range of flow speeds, and highlight the importance of considering these factors when estimating coral reef biogeochemistry.

The present paper aims at establishing the synthetic jet technology capabilities in controlling the von Kármán street behind a circular cylinder. The circular cylinder, placed in an open-circuit wind tunnel, presents a slot in its rear position, through which the synthetic jet is issued. The Reynolds number, based on the circular cylinder diameter and the free-stream velocity, is equal to 4600 and the von Kármán street is characterized, in the baseline configuration (i.e. without synthetic jet), by a shedding frequency of 16.2 Hz. Several synthetic jet operating conditions are tested. Therefore, the effects of the momentum coefficient ($C_{\\mu } = 5.4$%, 10.8% and 21.6%) and the dimensionless frequency ($f^{+} = 0.49$, 0.98 and 1.96) on the von Kármán street behaviour can be analysed. Instantaneous two-dimensional in-plane velocity fields are measured in a plane containing the synthetic jet slot axis using multigrid/multipass cross-correlation digital particle image velocimetry. These measurements have been used to investigate the mean flow quantities and turbulent statistics of the phenomenon. In addition, the wake extent and behaviour (i.e. symmetric or asymmetric) are analysed as well as the drag coefficient, for each configuration. The extent of the wake region decreases as the momentum coefficient and/or the dimensionless frequency increase, while the symmetric/asymmetric wake behaviour is found to be governed by a different control parameter: the synthetic jet Reynolds number based on its impulse. As regards the drag coefficient, a maximum reduction, of approximately 35%, is found for the configuration at $C_{\\mu }=10.8\\,\\%$ and $f^{+}=0.98$.

Background In this paper, we introduce an image analysis approach for spatiotemporal segmentation, quantification, and visualization of movement or contraction patterns in 2D+t and 3D+t microscopy recordings of biological tissues. The development of this pipeline was motivated by the observation of contraction waves in the extra-embryonic membranes of the red flour beetle Tribolium castaneum . These contraction waves are a novel finding, whose origin and function are not yet understood. The objective of the proposed approach is to analyze the dynamics of the extra-embryonic membranes in order to provide quantitative evidence for the existence of contraction waves during late stages of embryonic development. Results We apply the pipeline to live-imaging data of Tribolium embryonic development recorded with light-sheet fluorescence microscopy. The proposed pipeline integrates particle image velocimetry (PIV) for quantitative movement analysis, surface detection, tissue cartography, and algorithmic identification of characteristic movement dynamics. We demonstrate that our approach reliably and efficiently detects contraction waves in both 2D+t and 3D+t recordings and enables automated quantitative analyses, such as measuring the area involved in contractile behavior, wave duration and frequency, spatiotemporal location of the contractile regions, and their relation to the underlying velocity distribution. Conclusions The pipeline will be employed in future work to conduct a large-scale characterization and quantification of contraction wave behavior in Tribolium development and can be readily adapted for the identification and segmentation of characteristic tissue dynamics in other biological systems.

As tools and techniques to measure experimental granular flows become increasingly sophisticated, there is a need to rigorously assess the validity of the approaches used. This paper critically assesses the performance of particle image velocimetry (PIV) and particle tracking velocimetry (PTV) for the measurement of granular flow properties. After a brief review of the PIV and PTV techniques, we describe the most common sources of error arising from the applications of these two methods. For PTV, a series of controlled experiments of a circular motion is used to illustrate the errors associated with the particle centroid uncertainties and the linear approximation of particle trajectories. The influence of these errors is then examined in experiments on dry monodisperse granular flows down an inclined chute geometry. The results are compared to those from PIV analysis in which errors are influenced by the size of the interrogation region. While velocity profiles estimated by the two techniques show strong agreement, second order statistics, e.g. the granular temperature, display very different profiles. We show how the choice of the sampling interval, or frame rate, affects both the magnitude of granular temperature and the profile shape determined in the case of PTV. In addition, the determined magnitudes of granular temperature from PIV tends to be considerably lower when directly measured or largely overestimated when theoretically scaled than those of PTV for the same tests, though the shape of the profiles is less sensitive to frame rate. We finally present solid concentration profiles obtained at the sidewalls and and examine their relationship to the determined shear rate and granular temperature profiles.

Stroke has emerged as the primary contributor to morbidity and mortality in patients undergoing treatment with Left Ventricular Assist Devices (LVADs), possibly arising from the turbulent flow and elevated wall shear stresses generated in these devices. A minimally invasive LVAD (LifeheART) has been proposed to address these issues, employing an intra-aortic location and a shaftless impeller design. The current study uses Particle Image Velocimetry (PIV) flow visualization, carried out in a Cardiovascular Mock Circulation Loop (CMCL), to identify the velocity distribution at the pump outlet in order to validate the developed CFD model. Subsequently, the model evaluates the blood shear stress distribution and blood damage index. The results showed that the calculated viscous shear stress (VSS) and the blood damage index of the LifeheART prototype is significantly lower than the published data for current clinically available devices, confirming the potential utility of the new design to improve patient outcomes.

Continuous, high‐resolution data for characterizing freshwater habitat conditions can support successful management of endangered salmonids. Uncrewed aircraft systems (UAS) make acquiring such fine‐scale data along river channels more feasible, but workflows for quantifying reach‐scale salmon habitats are lacking. We evaluated the potential for UAS‐based mapping of hydraulic habitats using spectrally based depth retrieval and particle image velocimetry (PIV) by comparing these methods to a more well‐established flow modeling approach. Our results indicated that estimates of water depth, depth‐averaged velocity, and flow direction derived via remote sensing and modeling techniques were comparable and in good agreement with field measurements. Predictions of spring‐run Chinook salmon (Oncorhynchus tshawytscha) juvenile rearing habitat produced from PIV and model output were similar, with small errors relative to direct field observations. Estimates of hydraulic heterogeneity based on kinetic energy gradients in the flow field were generally consistent between PIV and flow modeling, but errors relative to field measurements were larger. PIV results were sensitive to the velocity index (α)$(\\alpha )$used to convert surface velocities to depth‐averaged velocities. Sun glint precluded PIV analysis along the margins of some images and a large degree of overlap between frames was thus required to obtain continuous coverage of the reach. Similarly, shadows cast by riparian vegetation caused gaps in spectrally based bathymetric maps. Despite these limitations, our results suggest that for sites with sufficient water surface texture, UAS‐based PIV can provide detailed hydraulic habitat information at the reach scale, with accuracies comparable to traditional field methods and multidimensional flow modeling. Plain Language Summary River systems provide some of the most diverse freshwater ecosystems on the planet, but changing environmental conditions have resulted in significant declines in the populations of many aquatic organisms, including endangered salmonids. Improved tools for mapping and modeling salmon habitats across a range of spatial and temporal scales are thus needed. Here, we introduce a workflow for using uncrewed aircraft systems (UAS) to acquire the remotely sensed input data needed to estimate two key variables influencing salmon habitat suitability: water depth and flow velocity. We found that UAS‐based predictions of hydraulic habitat agreed closely with values based on a flow model and with field observations. Remote sensing provides an efficient means of quantifying fine‐scale habitat heterogeneity and could help advance our understanding of biophysical interactions in river ecosystems and thus contribute to improved management of endangered fish. Key Points We evaluated the potential to quantify salmon habitat at a reach scale by inferring flow velocities from images acquired from an uncrewed aircraft system (UAS) Estimates of water depth and the magnitude and orientation of velocity vectors derived from images were comparable to those from a flow model Modeled and remotely sensed salmon habitat quality estimates were less sensitive to velocity errors than predicted kinetic energy gradients in the flow field

Surface velocity is traditionally measured with in situ techniques such as velocity probes (in shallow rivers) or Acoustic Doppler Current Profilers (in deeper water). In the last years, researchers have developed remote sensing techniques, both optical (e.g., image-based velocimetry techniques) and microwave (e.g., Doppler radar). These techniques can be deployed from Unmanned Aerial Systems (UAS), which ensure fast and low-cost surveys also in remotely-accessible locations. We compare the results obtained with a UAS-borne Doppler radar and UAS-borne Particle Image Velocimetry (PIV) in different rivers, which presented different hydraulic–morphological conditions (width, slope, surface roughness and sediment material). The Doppler radar was a commercial 24 GHz instrument, developed for static deployment, adapted for UAS integration. PIV was applied with natural seeding (e.g., foam, debris) when possible, or with artificial seeding (woodchips) in the stream where the density of natural particles was insufficient. PIV reconstructed the velocity profile with high accuracy typically in the order of a few cm s−1 and a coefficient of determination (R2) typically larger than 0.7 (in half of the cases larger than 0.85), when compared with acoustic Doppler current profiler (ADCP) or velocity probe, in all investigated rivers. However, UAS-borne Doppler radar measurements show low reliability because of UAS vibrations, large instrument sampling footprint, large required sampling time and difficult-to-interpret quality indicators suggesting that additional research is needed to measure surface velocity from UAS-borne Doppler radar.

Experimental rotation effects on flow past cylinders have been observed. The cylinders have the porous media coatings (PMC) named PMC1, PMC2, PMC3 and PMC4. For the range of rotation rates, including α = 0.52, α = 1.05 and α = 1.57, the flow characteristics have been presented at a Reynolds number of Re = 2500. In comparison with the experimental results for stationary cases (α = 0), the zones with lower streamwise velocity values became closer to the bodies as the rotation rates were enhanced. The maximum wake displacements have been obtained as 1.8D for the circular cylinder with no coating. For coated cylinders, these are 1.9D, 1.9D, 1.7D and 1.95D for the PMC1, PMC2, PMC3 and PMC4, respectively. For the same reason, the cross-stream velocity components also approached the circular cylinders. However, asymmetrical distributions for flow patterns have been attained. For this reason, the lower values for cross-stream velocity became more dominant in the wake. Moreover, separated flows were obviously seen by velocity fluctuations. The interaction of separated and wake flows induced these fluctuations. Wake lengths have been reduced compared to those of the cases with no rotation. The highest percentage for wake length reduction has been obtained as 92.9% by α = 1.05 for the bare cylinder. The maximum reductions have been attained as 89.7% by α = 1.05 for PMC1, 96.3% by α = 1.05 for PMC2, 85.7% by α = 1.57 for PMC3 and 90% by α = 1.05 for PMC4. The experimental results have also been presented for turbulence values. The highest turbulence kinetic energy value, 0.236, has been obtained at α = 1.05 for the bare cylinder. These values are 0.271 at α = 0.52 for the PMC1, 0.271 at α = 1.05 for PMC2, 0.245 at α = 1.05 for the PMC3 and 0.217 at α = 0.52 for the PMC4. As with the flow patterns, the induction by surface coating has been clearly observed through the augmentation of α values. Since surface movement for coating has also been seen for these situations, boundary layer thickness values have been reduced.

Phase-averaged and cycle-to-cycle analysis of key contributors to sound production in phonation is examined in a scaled-up vocal-fold model. Simultaneous temporally and spatially resolved pressure and velocity measurements permitted examination of each term in the streamwise integral momentum equation. The relative sizes of these terms were used to address the issue of whether transglottal pressure is a surrogate for vocal-fold drag, a quantity directly related to sound production. Further, time traces of transglottal pressure and volume flow rate provided insight into the role of cycle-to-cycle variations in voiced sound production which affect voice quality. Experiments were conducted using a 10× scaled-up model in a free-surface water tunnel. Two-dimensional vocal-fold models with semi-circular ends inside a square duct were driven with constant opening and closing speeds. The time from opening to closed, To, was half the oscillation period. Time-resolved digital particle image velocimetry (DPIV) and pressure measurements along the duct centreline were made for 3650 ≤ Re ≤ 8100 and equivalent life frequencies from 52.5 to 97.5 Hz. Results showed that transglottal pressure does serve as a surrogate for the vocal-fold drag. However, smaller but non-negligible momentum flux and inertia terms, caused by the jet and vocal-fold motions, may also contribute to vocal-fold drag. Further, cycle-to-cycle variations including jet switching and modulation are inherent in flows of this type despite their high degrees of symmetry and repeatability. The origins of these variations and their potential role in sound production and voice quality are discussed.