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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.

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.

A Lean Premixed Prevaporized (LPP) low-emission combustor which is applied with the combustion technology of staged lean fuel is developed. To study the cold flow dynamics and the combustion performance of the LPP combustor, both experimental tests using the Particle Image Velocimetry (PIV) to quantify the flow dynamics and numerical simulation using the Fluent software are conducted respectively. To investigate the emissions of the LPP combustor, four kinds of inlet conditions (viz. 7%, 30%, 85% and 100% F∞ (Thrust Force)) were conducted using numerical simulation. Numerical results are in good agreement with the experimental data. Results show that:1) a Primary recirculation zone (PRZ), a Corner recirculation zone (CRZ) and a Lip recirculation zone (LRZ) exist in the LPP combustor, and the velocity gradients between pilot swirling flow and primary swirling flow have contributed to the exchanges of mass, momentum and energy. 2) With the decrease of thrust force, NO mass fraction, CO2 mass fraction and total pressure losses at the exit of LPP combustor fall gradually. 3) Thermal NO formation rate closely relate to the zone area where gas temperature overruns 1900K and the maximum temperature in LPP combustor. 4) The combustion performance of the LPP combustor proposed in this paper is very well, and through comparative analysis with four kins of typical gas tubine combustor, the NO emission is very low and is equivalent to the CAEP6 43.87%.

Advanced optical methods, specifically time-resolved particle image velocimetry, were used to analyse the aerodynamics of the NACA0012 airfoil at a 17-degree angle of attack. A circular microcylinder (d/c = 0.015) was positioned at three locations ahead of the airfoil's leading edge to examine its effect on the flow dynamics. The results demonstrate that an optimally positioned microcylinder can significantly modify the flow field, enhancing the aerodynamic performance of airfoils and wind turbines. Detailed physical analysis of the flow fields, including streamlines and vortex structures, elucidates the flow control mechanisms. The findings highlight the potential for enhancing the aerodynamic properties of airfoils and wind turbines. The integration of microcylinders represents a novel approach to passive flow control, underscoring the technique's potential to enhance liftand reduce drag. These findings not only deepen our understanding of flow dynamics but also showcase the practical utility of innovative particle image velocimetry techniques in experimental aerodynamics. Consequently, this research contributes to both fundamental physics and the practical applications in aerospace engineering and wind energy optimization.

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.

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.

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.

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.

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.