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33 results for “PIV”
HyPer SMM wind tunnel tests: PIV pictures
<p>In this study, windblown sand transport on flat ground is reproduced by means of Wind-Sand Tunnel Tests (WSTT) carried out in the wind tunnel L-1B of von Karman Institute for Fluid Dynamics. The aim of WSTT is twofold. On one hand, they are intended to characterize the incoming sand flux in open field conditions. On the other hand, they allow to properly tune cheaper Wind-Sand Computational Simulations. The wind tunnel setup implements a uniform 5-meter-long sand fetch as sand source. The wind speed boundary layer is characterized through 2D Particle Image Velocimetry (PIV) technique. Wind flow state variables are assessed along the sand fetch by setting the wind speed equal to 1.3, 1.5, 2 times the threshold one. For the complete wind tunnel setup and data analysis please refer to: Raffaele L., Coste, N., and Glabeke G. "Life-Cycle Performance and Cost Analysis of Sand Mitigation Measures: Toward a Hybrid Experimental-Computational Approach." Journal of Structural Engineering 148.7 (2022): 04022082.</p> <p>The study has been developed in the framework of the MSCA-IF-2019 research project Hybrid Performance Assessment of Sand Mitigation Measures (HyPer SMM, https://hypersmm.vki.ac.be/). This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant Agreement No. 885985</p>
Dataset of 'Complete flow characterization from snapshot PIV, fast probes and physics-informed neural networks'
<p>Dataset of the article 'Complete flow characterization from snapshot PIV, fast probes and physics-informed neural networks' (https://doi.org/10.1016/j.cma.2023.116652). The codes processing data here are on https://github.com/AlvaroMS90/Complete-flow-characterization-from-snapshot-PIV-fast-probes-and-physics-informed-neural-networks.</p> <p>This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No 949085) and by MCIN/AEI /10.13039/501100011033 and the European Union ‘NextGenerationEU/PRTR’ as part of the grant FJC2020-044342-I.</p>
SPLEEN - High Speed Turbine Cascade – Test Case Database - PIV Measurements
<p>This is an open-access database of Particle Image Velocimetry (PIV) measurements of the flow in the <strong>high-speed low-pressure turbine cascade SPLEEN C1</strong>. </p><p>This database complements aerodynamics measurements reported in the database "SPLEEN - High Speed Turbine Cascade – Test Case Database" which can be found at <a href="https://zenodo.org/doi/10.5281/zenodo.7264761">10.5281/zenodo.7264761</a>. </p><p>The data have been collected at the <strong>von Karman Institute for Fluid Dynamics</strong> during 2022 within the H2020 Clean Sky 2 project <strong>SPLEEN </strong>– Secondary and Leakage Flow Effects in High-Speed Low-Pressure Turbines.</p><p>This database contains documents that describe the experimental setup, instrumentation, measurement uncertainties, geometries, and the dataset structure related to the SPLEEN C1 PIV measurements.</p><p>The database contains experimental data of the test campaign conducted on the linear cascade codenamed SPLEEN C1 in the VKI high-speed wind tunnel S1/C.</p><p>PIV measurements were performed on the upstream blade-to-blade plane at cascade midspan, passage blade-to-blade plane at cascade midspan, and on a cascade outlet axial plane located 50% of the airfoil axial chord downstream the cascade trailing edge, near the cascade endwall (0-18% of the cascade span).</p><p>The turbine cascade geometry is representative of designs of high-speed low-pressure turbines for next-generation geared turbofan engines.</p><p>The measurement datasets describe the flow through the turbine cascade tested at on- and off-design conditions (cascade exit Reynolds and Mach numbers), with and without a turbulence grid located upstream of the cascade. The database includes measurements of flow velocity, flow angles, Mach numbers, and turbulence quantities.</p><p>The PIV measurements were performed on the <strong>SPLEEN C1 turbine cascade</strong> equipped <strong>WITH a REFERENCE CAVITY ENDWALL</strong> (Cavity Aref), <strong>WITHOUT WAKE GENERATOR</strong> (steady inlet flow), <strong>WITH and WITHOUT TURBULENCE GRID</strong> (different inlet turbulence level).</p><p>The project has received Funding from the Clean Sky 2 Joint Undertaking under the European Union's Horizon 2020 research and innovation program under the grant agreement 820883.</p>
Twin test 1: Effect of vegetation on urban flows. PIV data from NTUA WT experiment and LDV from KIT WT experiment
<p>The first Twin Test (TW1) of the TWEET-IE project (<a href="http://www.tweet-ie.eu">www.tweet-ie.eu</a>) involved measurements of the flow past a surface mounted cube with openings, representing a building exposed to an atmospheric boundary layer. Tests were performed for smooth building walls but also with modelled vegetation covering the windward façade and the roof of the building. The measurements were performed both at Karlsruhe Institute of Technology (KIT) and the National Technical University of Athens (NTUA), in wind tunnels, at common locations around the building. Laser Doppler Anemometry (LDA) was used at KIT and Particle Image Velocimetry (2C-2D and 3C-2D PIV) at NTUA. In the present data set shows the effect of vegetation on the flow velocities and a comparison of the twin wind tunnel measurements. </p>
An axisymmetric impinging jet under two-frequency external forcing: animations of low-order reconstruction from DMD modes of PIV data
<p>Animations of the low-order reconstruction of vortex structures dynamics in an impinging turbulent jet under external periodic forcing. The reconstruction is obtained from DMD modes of time-resolved PIV data. The flow cases correspond to the unmodulated (main case) and modulated amplitude of the forcing frequency. The modulation frequencies are set to as 1/2, 1/3, 1/4, 1/5 and 1/8 of the main one, respectively.</p>
Stereo PIV measurement of open channel flows in RA8 flume at the University of Sheffield
<p>Stereo PIV measurement of open channel flows in RA8 flume at the University of Sheffield</p> <p>Six flow conditions over a rough bed of spheres with 24mm diameter. PIV plane was at the centerline of the flow shining through the bed of spheres. Where the laser PIV plane shone up, the spheres were replaced with translucent hollow spheres to allow the light to go through. Gradient of the flow was 0.001.</p> <table> <tbody> <tr> <td>Water Depth</td> <td>Flow rate</td> <td>Velocity</td> <td>Reynolds’ number</td> <td>Manning’s number</td> <td>Froude number</td> <td>Weber number</td> <td>Relative Submergence</td> </tr> <tr> <td>(mm)</td> <td>(l/s)</td> <td>(m/s)</td> <td>(with depth)</td> </tr> <tr> <td>49</td> <td>1.87</td> <td>0.08</td> <td>3,740</td> <td>0.049</td> <td>0.11</td> <td>3.96</td> <td>2.04</td> </tr> <tr> <td>69</td> <td>5.05</td> <td>0.15</td> <td>10,100</td> <td>0.031</td> <td>0.18</td> <td>20.53</td> <td>2.88</td> </tr> <tr> <td>89</td> <td>7.46</td> <td>0.17</td> <td>14,920</td> <td>0.031</td> <td>0.18</td> <td>34.74</td> <td>3.71</td> </tr> <tr> <td>109</td> <td>11.21</td> <td>0.21</td> <td>22,420</td> <td>0.028</td> <td>0.2</td> <td>64.05</td> <td>4.54</td> </tr> <tr> <td>129</td> <td>15.4</td> <td>0.24</td> <td>30,800</td> <td>0.026</td> <td>0.21</td> <td>102.14</td> <td>5.38</td> </tr> <tr> <td>149</td> <td>20.7</td> <td>0.28</td> <td>41,400</td> <td>0.023</td> <td>0.23</td> <td>159.77</td> <td>6.21</td> </tr> </tbody> </table>
STAB paper FLOWlab raw PIV image data
<p>Raw PIV image data for the FLOWlab experiments. Data was captured and processed in PIVlab 3.0 (a free Matlab toolbox). Data can be processed with every PIV software. The files contain calibration images, and information about the laser pulse separation (in the files "acquisition_log.txt" in the column "pulse_sep"). This information can be used to convert velocities and scales to metric units.</p> <p>Data was captured by OPTOLUTION (cylinder, empty channel, flat plate) and Fachhochschule Kiel (NACA0015) in the FLOWlab with a 500 mW LD-PS and the OPTOcam 2/80 by OPTOLUTION.</p> <p>https://optolution.com/en/products/particle-image-velocimetry-piv/flowlab/</p>
Dataset of "Pressure from data-driven estimation of velocity fields using snapshot PIV and fast probes"
<p>Dataset of the article <em>Pressure from data-driven estimation of velocity fields using snapshot PIV and fast probes </em>(<a href="https://doi.org/10.1016/j.expthermflusci.2022.110647">https://doi.org/10.1016/j.expthermflusci.2022.110647</a>). A data-driven method is applied to combine non-time-resolved velocity field and fast probe data, and achieve time-resolved velocity and pressure field.</p> <p>The codes processing data here are on https://github.com/erc-nextflow/Data-driven-pressure-estimation-with-EPOD.</p> <p>This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No 949085, NEXTFLOW).</p>
Databases for NEXT-RSV-SEQ (RSV, HMPV, PIV)
<div> <div> <div> <div> <div> <div> <div> <div> <div> <div> <div> <div> <p>Here, we provide databases ready for use in sequencing read decontamination with our Next-RSV-SEQ pipeline (<a href="https://gitlab.com/rki_bioinformatics/next-rsv-seq" target="_new" rel="noreferrer">https://gitlab.com/rki_bioinformatics/next-rsv-seq</a>), designed for viral genome assembly using Illumina data.</p> <p><strong>Available Databases:</strong></p> <ul> <li><strong>Human orthopneumovirus / Human respiratory syncytial virus (RSV)</strong>: [RSV_GRCh38_2022-04-06.zip]</li> <li><strong>Human metapneumovirus (HMPV)</strong>: [HMPV_2022-05-28.zip]</li> <li><strong>Parainfluenza virus (PIV)</strong>: [PIV_2022-05-28.zip]</li> </ul> <p>These databases were created using <a href="https://github.com/DerrickWood/kraken2">Kraken2</a> and are based on all complete viral genome sequences available on NCBI Reference Sequence Database (<a href="https://www.ncbi.nlm.nih.gov/refseq/">RefSeq</a>) as of April 6, 2022 (for RSV), and May 28, 2022 (for HMPV and PIV). The RSV database also includes the human genome sequence GRCh38 (Genome Reference Consortium Human Build 38). The databases have been compressed into zip format for easy downloading. <strong>Before use, please unpack the respective zip archive.</strong></p> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div>
WASHTREET. Runoff velocity data using different Particle Image Velocimetry (PIV) techniques in a full scale urban drainage physical model
<p><strong>WASHTREET - Runoff velocity data using different Particle Image Velocimetry (PIV) techniques in a full scale urban drainage physical model.</strong></p> <p>This dataset contains raw data and runoff velocities results obtained using seeded and unseeded Particle Image Velocimetry (PIV) techniques in an urban drainage physical model, which is placed in the Hydraulic Laboratory of the Centre for Technological Innovation in Construction and Civil Engineering (CITEEC) at the University of A Coruña (Spain). The objective of this work is to obtain an accurate representation of the surface velocity distribution as part of the <a href="https://zenodo.org/communities/washtreet">WASHTREET project</a>, where a series of high-resolution experiments were performed measuring urban surface wash-off and sediment transport through gully pots and pipes under laboratory-controlled conditions. The experimental facility is a 36 m<sup>2</sup> full-scale street section and consists of a rainfall simulator placed over a concrete street surface with two gully pots that drain runoff into an underground pipe system. The dataset was used in the work developed in Naves et al. (2019) (DOI: <a href="https://doi.org/10.1016/j.jhydrol.2019.05.003">https://doi.org/10.1016/j.jhydrol.2019.05.003</a>).</p> <p>A detailed description of experimental setup, procedure, postprocessing and results can be consulted in ‘<em>1_TestsDescription.pdf’. </em>4K resolution and 25 fps raw videos from which frames are extracted for the PIV analysis are provided for each experiment performed in separated zip files (named as <em>‘2.</em>(test ID)<em>_RawVideos_</em>(configuration)<em>.zip’</em>). Experiments includes three different steady rainfalls of 30, 50 and 80 mm/h of rain intensity and were recorded with and without added fluorescent traces. Data to orthorectify frames from videos are provided in ‘<em>3_SpatialCalibration.zip</em>’. In addition, 60 seconds of steady conditions are extracted for each test and the frames are processed to obtain velocities from a PIV analysis. ‘<em>4_ProcessedFrames_SteadyFlow.zip’ </em>includes the 1500 rectified and processed frames for each experiment to perform the PIV analysis. Results of runoff velocity distributions are included in ‘<em>5_VelocityResults.zip’</em>.</p> <p>Further details of the rainfall simulator, physical model geometry and more hydraulic and sediment transport results can be consulted in <a href="http://doi.org/10.5281/zenodo.3233918"><em>WASHTREET hydraulic, wash-off and sediment transport experimental data</em></a>. In addition, data regarding the use of photogrammetry to obtain the elevation map of this physical model is included in <a href="http://www.doi.org/10.5281/zenodo.3241337">WASHTREET Structure from Motion data</a>.</p> <p>The WASHTREET project is being developed in the scope of the PhD thesis of the first author, which is in receipt of a Spanish Ministry of Science, Innovation and Universities predoctoral grant [FPU14/01778]. The project also receive funding from the Spanish Ministry of Science, Innovation and Universities under POREDRAIN project RTI2018-094217-B-C33 (MINECO/FEDER-EU)</p> <p>Derived publications:</p> <ul> <li>Naves, J., Anta, J., Puertas, J., Regueiro-Picallo, M., & Suárez, J. (2019). Using a 2D shallow water model to assess Large-Scale Particle Image Velocimetry (LSPIV) and Structure from Motion (SfM) techniques in a street-scale urban drainage physical model. <em>Journal of Hydrology</em>, <em>575</em>, 54-65. <a href="https://doi.org/10.1016/j.jhydrol.2019.05.003">https://doi.org/10.1016/j.jhydrol.2019.05.003</a></li> <li>Naves, J., Anta, J., Suárez, J., & Puertas, J. (2020). Hydraulic, wash-off and sediment transport experiments in a full-scale urban drainage physical model. <em>Scientific Data</em>, <em>7</em>(1), 1-13. <a href="https://doi.org/10.1038/s41597-020-0384-z">https://doi.org/10.1038/s41597-020-0384-z</a></li> <li>Naves, J., García, J. T., Puertas, J., & Anta, J. (2021). Assessing different imaging velocimetry techniques to measure shallow runoff velocities during rain events using an urban drainage physical model. <em>Hydrology and Earth System Sciences</em>, <em>25</em>(2), 885-900. <a href="https://doi.org/10.5194/hess-25-885-2021">https://doi.org/10.5194/hess-25-885-2021</a> </li> </ul>
PIV results from a kinematic study of robotic bird wings
Open the record for dataset details and reuse information.
Velocity vector files from PIV measurements of the wake behind a flying beetle
<p>These are the velocity vector files from the PIV measurements in the wake of <em>Batocera rufomaculata </em>flying tethered in a wind tunnel. The data correspond to the manuscript: </p> <p><b>The aerodynamics and power requirements of forward flapping flight in the mango stem borer beetle (<i>Batocera rufomaculata</i>)</b>, by Urca et al. published by the journal Integrative Organismal Biology. </p> <p>The abstract of the coresponding paper is: </p> <p>The need for long dispersal flights can drive selection for behavioral, physiological and biomechanical mechanisms to reduce the energy spent flying. However, some energy loss during the transfer of momentum from the wing to the fluid is inevitable, and inherent to the fluid-wing interaction. Here, we analyzed these losses during the forward flight of the mango stem borer (<i>Batocera rufomaculata</i>). This relatively large beetle can disperse substantial distances in search of new host trees, and laboratory experiments have demonstrated continuous tethered flights that can last for up to an hour. We flew the beetles tethered in a wind tunnel and used high-speed videography to estimate the aerodynamic power from their flapping kinematics and particle image velocimetry (PIV) to evaluate drag and kinetic energy from their unsteady wakes. To account for tethering effects, we measured the forces applied by the beetles on the tether arm holding them in place. The drag of the flying beetle over the flapping cycle, estimated from the flow fields in the unsteady wake, showed good agreement with direct measurement of mean horizontal force. Both measurements showed that total drag during flight is ~5-fold higher than the parasite drag on the body. The aerodynamic power estimated from both the motion of the wings, using a quasi-steady blade-element model, and the kinetic energy in the wake, gave mean values of flight-muscle mass-specific power of 87 and 65 W kg muscle<sup>-1</sup>, respectively.<sup> </sup>A comparison of the two values suggests that ~25% of the energy is lost within the fluid due to turbulence and heat. The muscle mass-specific power found here is low relative to the maximal power output reported for insect flight muscles. This can be attributed to reduced weight support during tethered flight or to operation at submaximal output that may ensure a supply of metabolic substrates to the flight muscles, thus delaying their fatigue during long-distance flights. </p>
Supporting Information for: Characterization of fingers resulting from settling-driven gravitational instabilities through simultaneous PIV and PLIF imaging of laboratory experiments
<p>This repositery contains supporting information accompanying the submission of the manuscript entitled: "Characterization of fingers resulting from settling-driven gravitational instabilities through simultaneous PIV and PLIF imaging of laboratory experiments" by Fries, Lemus, Jarvis, Clarke, Phillips, Manzella and Bonadonna. The manuscript has been submitted on 02 December 2024 to the Journal of Geophysical Research - Solid Earth. All the files present in this repositery are described in the file "Supporting_Information_Friesetal.pdf". Please refer to that file for additional information on the data present in the repositery.</p>
PIV vector fields from: Boundary layer hydrodynamics of patchy biofilms
<p>This dataset contains the instantaneous velocity vector fields from PIV data taken over large acrylic plates fouled with diatomaceous biofilm of varying patchiness. </p> <p>See associated article, Boundary layer hydrodynamics of patchy biofilms, for methods description.</p> <p>Each zip folder contains data for one of the 4 non-uniform biofilms examined, PB-1 (patchy biofilm 1); PB-2 (patchy biofilm 2); SB-1 (sparse biofilm 1); SB-2 (sparse biofilm 2). For each biofilm, the corresponding folder contains 4000 statistically independent instantaneous velocity vector fields. Each vector field is saved in a .mat file, and the workspace variable that contains the data is called ‘vecfield’. </p> <p>Size calibration and water temperature are provided in the spreadsheet ‘experiment_metadata.xlsx’</p> <p> </p> <p>Column 1: X (streamwise distance [pixels]) </p> <p>Column 2: Y (wall-normal distance from bottom of frame [pixels])</p> <p>Column 3: U (streamwise velocity vector [pixels / 250 microseconds]) </p> <p>Column 4: V (vertical velocity vector [pixels / 250 microseconds]) </p> <p>Column 5: CHC (number of tracked particles. A value < 1 gives the location of the biofilm, which was masked out)</p> <p> </p>
Synchronous PIV measurements of a self-powered blood turbine and pump couple for right ventricle support
<p>A blood turbine-pump system (iATVA) was proposed as a self-driven, motorless mechanical right-heart assist device. In this study, the iATVA system is investigated with particular emphasis on the blood turbine flow dynamics. A time-resolved 2D particle image velocimetry (PIV) set-up allowed simultaneous recordings from both the turbine and pump impellers. Results showed that magnetically coupled impellers operated synchronously. As the turbine flow rate increased from 1.6 to 2.4 LPM, the rotational speed and relative inlet flow angle increased from 630 to 900 rpm, and 38 to 55% respectively. At the trailing edges, backflow region spanned 3/5 of the total passage outlet flow, and an extra leakage flow was observed at the leading edge. For this initial turbine design, ~75% of the turbine blade passage was not contributing to the impulse operation mode. The maximum non-wall shear rate was ~2288 s<sup>-1</sup> near to the inlet exit, which is significantly lower than the commercial blood pumps, encouraging further research and blood experiments of this novel concept. Experimental results will improve the hydrodynamic design of the turbine impeller and volute regions and will be useful in computational fluid dynamics validation studies.</p>
TDENV PIV and LAV Dengue Prime-boost Strategy
ClinicalTrials.gov study NCT02239614. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Study of Varying Injection Schedules of TDENV-PIV Vaccine With AS03B Adjuvant and Placebo in Healthy US Adults
ClinicalTrials.gov study NCT02421367. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Nurse PIV Insertion Success With and Without Assistive Devices in Patients 0-12 Months of Age
ClinicalTrials.gov study NCT01637987. IPD Sharing: Not stated. Countries: 1. Publications: 4.
Velocity vector files from PIV measurements of the wake behind a flying beetle
Open the record for dataset details and reuse information.
PIV data of straight blade and swept blade wind turbine
<p>In large wind farms, the wake behind the upstream wind turbine affects the performance of the downstream turbines which reduces the overall power output. The geometry of the wind turbine blades has significant effects on the mechanical efficiency of this process. Here, we suggest to utilize a bio-inspired blade based on the common swift wing. Common swift is known to be a long-distance flyer, able to stay aloft for long periods of time by maintaining high lift and low drag. We study the near wake flow characteristics of a horizontal turbine model with swept blades and its aerodynamic loads. These are compared with a straight-bladed turbine. The experiments were conducted in a water flume using particle image velocimetry (PIV) technique. Both blades were studied for four different speeds with freestream Reynolds numbers ranging from 23,000 to 41,000. Our results show that the near wake developed behind the swept-back blade was significantly different from the straight blade configuration. The near wake developed behind the swept-back blade exhibited relatively lower momentum loss and suppressed turbulent activity (mixing and production) compared to the straight blade. Comparing the aerodynamic characteristics, though the swept-back blade generated relatively less lift than the straight blade, the drag was relatively lower as well. Thus, the swept-back blade produced 2-3 times higher lift-to-drag ratio than the straight blade. Based on the observations, we suggest that, with improved design optimizations, using the swept-back configuration in wind turbine blades can positively help to improve the energy loss in downstream wind turbines in wind farms and can increase the overall energy efficiency.</p>
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