Basics and principles of particle image velocimetry (PIV) for mapping biogenic and biologically relevant flows

Stamhuis, Eize

doi:10.1007/s10452-005-6567-z

Cited by 65 publications

(58 citation statements)

References 34 publications

(40 reference statements)

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“…Average particle displacements in the jet and cohering vortex ring were in the order of magnitude of 1-6·pixels, and the displacement detection limit was below 0.05·pixels. Erroneous vectors and obvious outliers were removed in a manual validation procedure and replaced using 2D spline interpolation (Stamhuis and Videler, 1995;Stamhuis, 2005a). In general, maximally between 2 and 10 flow vectors were interpolated on a typical data set of 400 vectors.…”

Section: Flow Analysismentioning

confidence: 99%

Propulsive force calculations in swimming frogs II. Application of a vortex ring model to DPIV data

Stamhuis

Nauwelaerts

2005

Journal of Experimental Biology

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Frogs propel themselves by kicking water backwards using a synchronised extension of their hind limbs and webbed feet. To understand this propulsion process, we quantified the water movements and displacements resulting from swimming in the green frog Rana esculenta, applying digital particle image velocimetry (DPIV) to the frog's wake.The wake showed two vortex rings left behind by the two feet. The rings appeared to be elliptic in planform, urging for correction of the observed ring radii. The rings' long and short axes (average ratio 1.75:1) were about the same size as the length and width of the propelling frog foot and the ellipsoid mass of water accelerated with it. Average thrust forces were derived from the vortex rings, assuming all propulsive energy to be compiled in the rings. The calculated average forces (F av =0.10±0.04·N) were in close agreement with our parallel study applying a momentum-impulse approach to water displacements during the leg extension phase.We did not find any support for previously assumed propulsion enhancement mechanisms. The feet do not clap together at the end of the power stroke and no 'wedgeaction' jetting is observed. Each foot accelerates its own water mantle, ending up in a separate vortex ring without interference by the other leg.

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Section: Flow Analysismentioning

confidence: 99%

Propulsive force calculations in swimming frogs II. Application of a vortex ring model to DPIV data

Stamhuis

Nauwelaerts

2005

Journal of Experimental Biology

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“…André et al (1993) used PTV to study cannibalism on larvae by Cerastoderma edule. Stamhuis and colleagues (Stamhuis et al, 2002;Stamhuis, 2006) discussed suspension-feeding flows as part of two broader reviews of applications of PIV to biological problems.…”

Section: Introductionmentioning

confidence: 99%

Model-assisted measurements of suspension-feeding flow velocities

Clos

Jones

Carrier

et al. 2017

Journal of Experimental Biology

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Benthic marine suspension feeders provide an important link between benthic and pelagic ecosystems. The strength of this link is determined by suspension-feeding rates. Many studies have measured suspension-feeding rates using indirect clearance-rate methods, which are based on the depletion of suspended particles. Direct methods that measure the flow of water itself are less common, but they can be more broadly applied because, unlike indirect methods, direct methods are not affected by properties of the cleared particles. We present pumping rates for three species of suspension feeders, the clams Mya arenaria and Mercenaria mercenaria and the tunicate Ciona intestinalis, measured using a direct method based on particle image velocimetry (PIV). Past uses of PIV in suspensionfeeding studies have been limited by strong laser reflections that interfere with velocity measurements proximate to the siphon. We used a new approach based on fitting PIV-based velocity profile measurements to theoretical profiles from computational fluid dynamic (CFD) models, which allowed us to calculate inhalant siphon Reynolds numbers (Re). We used these inhalant Re and measurements of siphon diameters to calculate exhalant Re, pumping rates, and mean inlet and outlet velocities. For the three species studied, inhalant Re ranged from 8 to 520, and exhalant Re ranged from 15 to 1073. Volumetric pumping rates ranged from 1.7 to 7.4 l h for C. intestinalis. We also used CFD models based on measured pumping rates to calculate capture regions, which reveal the spatial extent of pumped water. Combining PIV data with CFD models may be a valuable approach for future suspension-feeding studies.

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“…Nevertheless, there is considerable variation be tween published values of the exhalant jet velocity of mussels (Jørgensen et al 1986, André et al 1993, Newell et al 2001, Stamhuis 2006, Maire et al 2007, Frank et al 2008, MacDonald et al 2009, Troost et al 2009), and little is known about the detailed fluid mechanics of flow near a mussel that is generated by the flow through the exhalant siphon appearing as a well structured jet (André et al 1993, Green et al 2003. This flow in conjunction with a possible imposed external flow from currents or other mussels will influence the grazing impact and thus the concentration distribution of food particles reaching the inhalant aperture; hence affecting the feeding conditions of the mussel.…”

Section: Introductionmentioning

confidence: 99%

“…2) is a well de scribed phenomenon (e.g. Riisgård & Randløv 1981, Newell et al 2001, Riisgård et al 2003, 2006 which in the present work was used to evaluate the effect of reduced shell opening degree on exhalant jet velocity (cf. 'reduced filtration rate values' in Tables 1 & 3).…”

Section: Allometric Equations and Scalingmentioning

confidence: 99%

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The exhalant jet of mussels Mytilus edulis

Riisgård¹,

Jørgensen²,

Lundgreen³

et al. 2011

Mar. Ecol. Prog. Ser.

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The exhalant jet flow of mussels in conjunction with currents and/or other mussels may strongly influence the mussels' grazing impact. Literature values of mussel exhalant jet velocity vary considerably and the detailed fluid mechanics of the near-mussel flow generated by the exhalant jet has hitherto been uncertain. Computational modelling of this phenomenon depends on knowledge of the velocity distribution near the exhalant siphon aperture of mussels to provide appropriate boundary conditions for numerical flow models. To be useful such information should be available for a range of mussel shell lengths. Here, we present results of a detailed study of fully open mussels Mytilus edulis in terms of filtration rate, exhalant siphon aperture area, jet velocity, gill area and body dry weight, all as a function of shell length (mean ± SD) over the range 16.0 ± 0.4 to 82.6 ± 2.9 mm, with the corresponding scaling laws also presented. The exhalant jet velocity was determined by 3 methods: (1) measured clearance rate divided by exhalant aperture area, (2) manual particle tracking velocimetry (PTV) using video-microscope recordings, and (3) particle image velocimetry (PIV). The latter provides detailed 2-component velocity distributions near the exhalant siphon in 5 planes parallel to the axis of the jet and the major axis of the oval aperture, and hence estimates of momentum and kinetic energy flows in addition to mean velocity. Data obtained on particles inside the exhalant jet of filtered water was verified by the use of titanium dioxide seeding particles which were de-agglomerated by ultrasound to a size range of 0.7 to 2 µm prior to addition, to avoid retention by the gill filter of the mussels. We found that exhalant jet velocity was essentially constant at ~8 cm s −1 , and independent of shell length. Based on geometric similarity and scaling of mussel pump-system characteristics we found that these characteristics coincide approximately for all sizes when expressed as pressure head versus volume flow divided by shell length squared. KEY WORDS: Filtration rate · Exhalant siphon area · Particle image velocimetry · Particle tracking velocimetry · Exhalant jet velocity · Velocity field · Allometric equation · Scaling law Resale or republication not permitted without written consent of the publisherMar Ecol Prog Ser 437: [147][148][149][150][151][152][153][154][155][156][157][158][159][160][161][162][163][164] 2011 will influence the grazing impact and thus the concentration distribution of food particles reaching the inhalant aperture; hence affecting the feeding conditions of the mussel. Of particular interest is the undesirable phenomenon of re-filtration where part of the once filtered and exhaled water reaches the inhalant aperture of either the same or other mussels. This has been studied to some extent for mussel beds where a number of attempts have been made to model phytoplankton concentration gradients caused by dense beds of filter-feeding bivalves in relatively strong currents with a high ...

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Basics and principles of particle image velocimetry (PIV) for mapping biogenic and biologically relevant flows

Cited by 65 publications

References 34 publications

Propulsive force calculations in swimming frogs II. Application of a vortex ring model to DPIV data

Propulsive force calculations in swimming frogs II. Application of a vortex ring model to DPIV data

Model-assisted measurements of suspension-feeding flow velocities

The exhalant jet of mussels Mytilus edulis

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