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52 results for “channel flow”
SBC LTER: Ocean: HFR-derived surface flow metrics, surface water retention times, and related factors in the Santa Barbara Channel (2012-2019)
This data package include three files: 1. daily maps of High-Frequency Radar (HFR) measured surface currents, indices of mesoscale eddy locations, and local retention times on a 2km grid; 2. monthly time series of wind stress, alongshore pressure gradient, surface current EOF principal components, vorticity, eddy area, eddy presence, and spatially averaged retention times from January 2012 to December 2019; 3. A MATLAB script for plotting the maps and timeseries. These data were processed in order to investigate the drivers of surface water retention in the Santa Barbara Channel, CA, details of which are available in the study: Brokaw, R.J., D.A. Siegel, and L. Washburn. Physical Drivers of Surface Water Retention in the Santa Barbara Channel. [In preparation for Journal of Geophysical Research: Oceans.]
Dataset for "Impact of the flow-field distribution channel cross-section geometry on PEM fuel cell performance: stamped vs. milled channel"
<p>Experimental data comprises raw data from load curve characterisation of a PEM fuel cell used for the validation of the mathematical model. Model data comprise of space-dependent values of hydrogen and oxygen concentration, local current densities, gas pressures and gas velocities in the modelled cell. These data were used for the investigation of the effect of different geometric parameters of flow-field channels on the performance of a PEM fuel cell.</p>
Lagrangian statistics in turbulent channel flow
<p>A set of Lagrangian statistics of passive tracers in a turbulent channel flow. The particle trajectories are obtained by means of integration of a simulated flow field, computed via Direct Numerical Simulation, at four different Reynolds numbers. The Reynolds numbers here employed are <span class="math-tex">\(\mathrm{Re}_{\tau} = \frac{u_{\tau}\delta}{\nu} = 180,\,395,\,590,\,950\)</span>, where <span class="math-tex">\(u_{\tau}\)</span>is the frictional velocity, <span class="math-tex">\(\delta\)</span> is the channel half height and <span class="math-tex">\(\nu\)</span> is the kinematic viscosity.</p> <p>Additional information about the database is provided in the included documentation.</p> <p>v1.0 -> Added statistics at ReT = 950</p> <p>v1.1 -> Added statistics at ReT = [180, 395, 590]</p> <p>v1.2 -> Added statistics at ReT = 265</p>
Data and scripts for reproducing "Quantifying Uncertainties in Direct Numerical Simulations of a Turbulent Channel Flow"
<p>This is the accompanying data and Python scripts to reproduce the figures in "Quantifying Uncertainties in Direct Numerical Simulations of a Turbulent Channel Flow", currently under review.</p>
ADCP data of ice-covered and open-channel (macro-turbulent) flow, Pulmanki River, 2016-2020
<p>README of ADCP_data_Lotsari_et_al_Water_opened.zip</p> <p><br> The ADCP data was the basis of the following paper:<br> Macro-turbulent flow and its impacts on sediment transport potential of a subarctic river during ice-covered and open-channel conditions <br> Eliisa Lotsari (1, 2), Michael Dietze (3), Maria Kämäri (4), Petteri Alho (2,5), Elina Kasvi (6,2)</p> <p>1 Department of Geographical and Historical Studies, University of Eastern Finland, Yliopistokatu 2, P.O. Box 111, FI-80101, Joensuu, Finland. eliisa.lotsari@uef.fi<br> 2 Department of Geography and Geology, University of Turku, FI-20014 Turun yliopisto, Turku, Finland.<br> 3 Section 4.6 Geomorphology, German Research Centre for Geosciences GFZ Potsdam, D-14473 Potsdam, Germany. mdietze@gfz-potsdam.de<br> 4 Finnish Environment Institute, Latokartanonkaari 11, FI-00790 Helsinki, Finland. maria.kamari@ymparisto.fi<br> 5 Finnish Geospatial Research Institute, National Land Survey of Finland, Geodeetinrinne 2, FI-02430, Masala, Finland. mipeal@utu.fi<br> 6 Turku University of Applied Sciences, Joukahaisenkatu 3, FI-20520, Turku, Finland. elina.kasvi@turkuamk.fi</p> <p>(Note: During the time of data gathering, Maria Kämäri worked at the University of Eastern Finland, and Elina Kasvi at the University of Turku)</p> <p>The data set has been measured with Sontek M9 or S5 sensors, depending on the time step (Table 1).</p> <p>Table 1. The measurement times, their acronyms (applied in the above mentioned publication)<br> and applied sensors. In the acronyms of the measurement times W=winter low flow period, S=spring<br> (snow-melt flood period), A=autumn low flow period. These information are presented also<br> in the Table 1 of the above-mentioned publication.<br> Date Acronym Sensor<br> 17.2.2016 W2016 M9<br> 25.5.2016 S2016 S5 <br> 10.9.2016 A2016 M9<br> 16.2.2017 W2017 M9 <br> 31.5.2017 S2017 M9 <br> 9.9.2017 A2017 M9 <br> 9.2.2018 W2018 M9 <br> 23.5.2018 S2018 S5 <br> 8.9.2018 A2018 S5 <br> 8.2.2019 W2019 M9 <br> 21.5.2019 S2019 M9 <br> 6.2.2020 W2020 M9 </p> <p>RiverSurveyor Live software, and its most recent version, was used each time.<br> The measurements have been done at Pulmanki River (69°55'59.09" N; 28° 2'34.32" E), Northern Finland, during 2016 - 2020. <br> The data is in directories of corresponding measurement times. The measurement<br> locations cs1, cs2, cs3, cs4, csA, csB and csC can be found in the paper (Figs. 1 and 2). <br> The data is in raw Matlab file format, as exported from the RiverSurveyor Live software.<br> The coordinate system is ENU.</p> <p>When used, the referencing to the paper and DOI ( 10.5281/zenodo.3855035 ) are required.</p>
Data and MATLAB Code for the paper entitled "A modified Chezy formula for one-dimensional unsteady frictional resistance in open channel flow"
<p>This link includes the data and MATLAB code files for the research paper entitled "A modified Chezy formula for one-dimensional unsteady frictional resistance in open channel flow" by Zhou, J.W.; Bro, W.M.; Tick*, G.R.; Mofatakari, H.; Li, Y.; and Cheng, L., which has been submitted to the Journal of Fluids Engineering. These files are edited under the GB18030 character set standard.</p>
Laboratory Open Channel Flow: Video, Waterlevel and Surface Velocity
<p>Video footage of an open channel flow in a laboratory setting, associated with the surface velocity and water level.</p> <p><br> - Video footage was collected using a Raspberry Pi Camera Module v2 attached to a Raspberry Pi 4 at 25fps from three positions and split into roughly 15s chunks.<br> - A "mic+35/IU/TC" ultrasonic sensor (accuracy: ±1%) measured the water level<br> - A "Nortek Vectrino" (accuracy: ±1% ±1mm/s) velocimeter measured the velocity at the surface</p> <p> </p> <p>- The video files can be found in the folders position1, position2 and position3, each file name contains the initial timestamp to match frames to the measurements<br> - The file "waterlevel.csv" contains the timestamps, Waterlevel [mm] and Percentage Full [%]. The waterlevel column is reversed, as the distance between the sensor and the surface was measured. This means, that lower values correspond to higher water levels.<br> - The file "velocity.csv" contains the timestamps and surface velocity measurements [m/s]</p>
Dataset: Effect of Macrorough Sidewalls on Flow Resistance in Steep Rough Channels
<p>The data set includes reach-averaged flow velocity measurements and bed and sidewall roughness parameters for flume experiments conducted at the Laboratory of Hydraulics, Hydrology, and Glaciology (VAW) at ETH Zurich.</p>
Visualization of adiabatic gas-liquid flow in a cross-corrugated plate heat exchanger channel: Part 1 - Original photographs, uniform two-phase distribution
<p>These measurement data are obtained and analyzed as part of a research project on adiabatic gas-liquid flow in a cross-corrugated plate heat exchanger channel. (See list of publications below). <br> The following Creative Commons license applies to the research data (images and measurement values) uploaded to the online repositories:<br> CC-BY 4.0<br> Author: Susanne Buscher</p> <p>The measurement data is published in 2 data sets: </p> <p>Data set I: Original image data (4 parts): <br> - uniform gas injection, part 1: https://doi.org/10.5281/zenodo.7985771; <br> - uniform gas injection, part 2: https://doi.org/10.5281/zenodo.7986374; <br> - uniform gas injection, part 3: https://doi.org/10.5281/zenodo.7986384; <br> - non-uniform gas injection (part 4): https://doi.org/10.5281/zenodo.8067163<br> This data set contains the original photographs of the two-phase flow in the cross-corrugated channel obtained with a high-resolution camera. In addition, the corresponding experimental parameters and flow patterns (for part 1-3 only) are included in the CSV files.<br> For uniform and non-uniform gas injection, respectively, the images were stored in sequentially numbered folders. The numbers of the folders correspond to the numbers of the measurement points listed in the attached CSV files with the associated experimental parameters.<br> The image folders are grouped in ZIP archives. Each ZIP archive contains the single-phase reference images which can be used for the two-phase images to conduct background subtraction, because the lighting conditions are equal for all images in one ZIP archive. </p> <p>Data set II: Measurement values and processed image data: <br> - https://doi.org/10.14279/depositonce-17868; <br> This data set contains all measurement values and calculated results of all measurement points in the Excel and CSV files (e.g. pressure drop, volumetric flow rates, void fraction, measurement uncertainties).<br> In addition, the results of the image processing algorithm are included in the Excel and CSV files (e.g. mean bubble diameter, maximum bubble diameter, local film flow ratio, extent of the two-phase distribution across the channel width, measurement uncertainties).<br> The image folders contain the pre-processed images which were the input to the digital image analysis (i.e. the aligned and cropped image section of the channel without inlet, outlet, and peripheral regions and after subtraction of the image background), and the post-processed images visualizing the output of the digital image analysis for this image (i.e. detected objects are inserted as colored regions in the image section; the meaning of colors was explained in the publications of 2022 and 2023). <br> In this dataset, the image folders are also subdivided into measurements with uniform and non-uniform gas injection and designated with the numbers of the measurement points, which are listed in the Excel and CSV files.</p> <p>The two datasets are the supplementary research data for the following publications: <br> - S. Buscher, 2023, Visualization, measurement, and modelling of adiabatic gas-liquid flow in a cross-corrugated plate heat exchanger channel, Doctoral thesis, Technische Universität Berlin, https://doi.org/10.14279/depositonce-17866. (supplemented by data sets I and II) <br> - S. Buscher, 2019, Visualization and modelling of flow pattern transitions in a cross-corrugated plate heat exchanger channel with uniform two-phase distribution, International Journal of Heat and Mass Transfer 144, 118643, https://doi.org/10.1016/j.ijheatmasstransfer.2019.118643. (supplemented by data set I, part 1-3)<br> - S. Buscher, 2021, Two-phase pressure drop and void fraction in a cross-corrugated plate heat exchanger channel: Impact of flow direction and gas-liquid distribution, Experimental Thermal and Fluid Science 126, 110380, https://doi.org/10.1016/j.expthermflusci.2021.110380. (supplemented by the measurement values in the Excel and CSV files of data set II)<br> - S. Buscher, 2022, Digital image analysis of gas-liquid flow in a cross-corrugated plate heat exchanger channel: A feature-based approach on various two-phase flow patterns, International Journal of Multiphase Flow 154, 104149, https://doi.org/10.1016/j.ijmultiphaseflow.2022.104149. (supplemented by data set II)</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>
Model data for "Flow Separation and Increased Drag Coefficient in Estuarine Channels with Curvature"
<p>These are the model data we generated using ROMS and analyzed for the journal article "Increased Drag Coefficient in Estuarine Channels with Curvature". Files include 8 sinuous channel models and 2 straight channels. sinuous_channel_1.nc and straight_channel_1.nc are the pair of models analyzed in section 3. sinuous_channel_1_avg.nc and straight_channel_1_avg.nc are the one-hour average result. sinuous_channel_2_avg.nc and straight_channel_2_avg.nc are the pair of deep channel models. sinuous_channel_3_avg.nc and others are the other different sinuous channel models.</p>
Three-dimensional crustal channel flows beneath the southeastern Tibetan Plateau revealed by full-waveform ambient noise tomography
<p>This is a new version of Vp and Vs models for paper titled "Three‐Dimensional Crustal Channel Flows Beneath the Southeastern Tibetan Plateau Revealed by Full‐Waveform Ambient Noise Tomography" published in Geophysical Research Letters.</p> <p>Modification history: new Vs model includes from surface downward to 120 km depth.</p> <p>Please ignore the models in version 1 and 2.</p>
Data and scripts for Journal of Geophysical Research – Earth Surface publication: Identification of debris-flow channels using high-resolution topographic data: A case study in the Quebrada del Toro, NW Argentina
<p>This data source contains scripts and data associated with the JGR Earth Surface publication <strong>“Identification of debris-flow channels using high-resolution topographic data: A case study in the Quebrada del Toro, NW Argentina”</strong> by A. Mueting, B. Bookhagen, and M. R. Strecker. The Digital Elevation Model (DEM) of the lower part of the Quebrada del Toro and Río Capilla catchment in the NW Argentinian Andes was generated from SPOT-7 tri-stereo images using Ames Stereo Pipeline. The final dataset has a spatial resolution of 3 m. A full description of the DEM generation process and accuracy assessment can be found in the associated paper. The scripts are also available at https://github.com/UP-RS-ESP/DEM_ConnectedComponents.</p>
Metamorphic evolution of the Greater Himalayan Sequence, Bhagirathi Valley (India) through a combination of channel flow and in-sequence shearing
<p>Dataset of a manuscript entitled "Metamorphic evolution of the Greater Himalayan Sequence, Bhagirathi Valley (India) through a combination of channel flow and in-sequence shearing " submitted in Tectonics (AGU)</p>
Bankfull and Mean-flow Channel Geometry Dataset across the CONtiguous United States (CONUS)
<p>This dataset includes estimated river channel geometry attributes, specifically width and depth, under bankfull and mean-flow conditions across the CONtiguous United States (CONUS). The method utilized for providing these estimations are based on eXtreme Gradient Boosting Regression (XGBR). This dataset can be linked to the National Hydrograohy Dataset Plus (NHDPlusV2.1) through Common identifier of the NHD feature, known as COMID.</p>
Optical trapping of micro-particles and bacterial cells in single channel and flow-focusing microfluidic devices
<p><strong>Video 1</strong> - The video shows the flow-focusing and trapping of 1.84 μm bacteria-sized particles flowing at a sample flow rate of 0.1 μL/min. The horizontal sheath flow rate 1 μL/min and the vertical sheath flow rate is 0.5 μL/min. Trapping is achieved using a maximum laser power of 250mW. </p> <p><strong>Video 2</strong> - The video shows the flow and fluorescence trapping of 1.84 μm bacteria-sized particles flowing at a flow rate of 0.013 μL/min. The channel surface is treated with pluronic F-127 to prevent cell adhesion. </p> <p><strong>Video 3</strong> - The video shows the flow and trapping of 1.84 μm bacteria-sized particles flowing at a flow rate of 1 μL/min. Increased flow rate results in continuous transient trapping of the cells is achieved at a trapping power of 250mW. The microchannel surface is not treated with pluronic F-127, therefore lot of particles stick to the channel surface. </p> <p><strong>Video 4</strong> - The video shows the flow and trapping of 1.84 μm bacteria-sized particles flowing at a flow rate of 0.013 μL/min. Trapping is achieved at a laser power of 250mW. The channel surface is treated with pluronic F-127 to prevent cell adhesion. </p> <p><strong>Video 5</strong> - The video shows the flow and trapping of <em>E. coli</em> MG1655 flowing at a flow rate of 0.013 μL/min. Trapping is achieved at a laser power of 250mW. The channel surface is treated with pluronic F-127 to prevent cell adhesion. </p> <p><strong>Video 6</strong> - The video shows the flow and trapping of <em>S. aureus</em> 6538 flowing at a flow rate of 0.013 μL/min. Trapping is achieved at a laser power of 250mW. The channel surface is treated with pluronic F-127 to prevent cell adhesion. </p>
Data from: A study on the Influence of submergence ratio on the transportation of suspended sediment in a partially vegetated channel flow
<p><span>Riparian or aquatic vegetation thrives with seasons. The understanding of canopies' Submergence-Ratio SR (stems' height to water depth) influence on suspended sediments' transportation is still limited. Thus, Large Eddy Simulations (LES) coupled with the Discrete Phase Method (DPM) are used to investigate the particles' 3-dimensional distribution in a partially vegetated straight channel. The spanwise distribution of particles is quantified by the Probability Density Function (PDF), showing a non-uniformity of particles in time as quantified by the PDF variance. The findings and conclusions: (Ⅰ) With SR rising, the particles' depletion effects exerted by the vegetation-side mixing layer are improved along the interface between vegetated and vegetation-side bare channel region. However, the SR has little effect on the variance of the particles' PDF in the spanwise direction when the mixing layer is fully developed. (Ⅱ) During the developing stage of the over-canopy mixing layer, submerged vegetation with higher SR gain a stronger upwards (vertical) entrainment capability. </span><span>The case (SR=60%) has a higher sediment concentration than other cases in the fully developed vertical mixing layer region above canopy.</span><span> (III) </span><span>The vertical suspension of particles in the vegetation-side bare channel region is analysed. Particles migrating from the vegetated region are entrained into the vegetation-side bare channel region by turbulent structures. Nevertheless, the vertical concentration profile is more uniform in the vegetated region than in the vegetation-side bare channel at the same streamwise location. The cases SR=40% and 60% still have higher sediment concentrations than other cases in the vegetation-side bare channel's upper region.</span></p>
Supporting information for "Kinetics of CN(v=1) reactions with butadiene isomers at low temperature by cw-Cavity Ringdown in a pulsed Laval flow with theoretical modelling of rates and entrance channel branching
<p>This file contains the master equation inputs for all the reactions studied, as well as all the details on stationary points and VRC-TST fluxes necessary to reproduce the simulations. </p>
Channel flow with hydrodynamically controlled benthic-pelagic coupled oxygen fluxes
<p>This dataset was used for the manuscript "Hydrodynamic control of sediment-water fluxes: Consistent parameterization and impact in coupled benthic-pelagic models" by Umlauf et al. (2023, JGR Oceans, <a href="https://doi.org/10.1029/2023JC019651" target="_blank" rel="noopener">10.1029/2023JC019651</a>).</p>
Data from: A study on the Influence of submergence ratio on the transportation of suspended sediment in a partially vegetated channel flow
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