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236 results for “hydrodynamics”
Hydrodynamic Model Output Used to Evaluate Chinook Salmon Movements and Distribution in the South Delta
This data release includes the output variables extracted from the UnTRIM Bay-Delta hydrodynamic model (hydrodynamic model) for use in evaluating the effects of hydrodynamics on the behavior of acoustically-tagged juvenile Chinook Salmon (Oncorhynchus tshawytscha) in the Sacramento-San Joaquin Delta. Work was funded by State Water Contractors (SWC) and completed by Anchor QEA; FlowWest, LLC; and University of Washington under a SWC 2023 Science Plan grant (study name Evaluation of the Influence of State Water Project and Central Valley Project on Chinook Salmon Movements and Distribution in the South Delta), contracted by SWC. Not all the hydrodynamic model output variables in the output provided with this memorandum were used in the final fish models used to analyze Chinook Salmon responses. Model output for additional variables and locations were included for completeness and to make these output files more broadly useful to researchers interested in other locations or variables in the Sacramento-San Joaquin Delta. Hydrodynamic model simulations were conducted for 2010, 2011, 2012, 2013, 2014, 2015, 2016, and 2017, with hydrodynamic model output variables provided at mostly the same locations for each period simulated. The years 2011 through 2016 were simulated previously for a prior project and model output provided through the Environmental Data Initiative (edi.1124.1). Files for these years were recreated from the prior simulations for this project to add an output location. Additional locations were added to the 2010 and 2017 simulations for the 2010 and 2017 hydrophone arrays, and thus 2010 and 2017 include additional model output, relative to 2011 through 2016. The model simulation for each year spanned the full period of Chinook Salmon detections in the telemetry data collected during that year.
Hydrodynamic, sediment, and bivalve data from seagrass edges in South Bay, VA, 2021 to 2022
The northern edge of the South Bay seagrass meadow was studied for two years to quantify flow characteristics, sediment movement, and bivalve abundance. ADCPs (Aquadopp, Vector, Vectrino) and wave gauges were used to measure hydrodynamic conditions, sediment sensors and sediment traps were used to measure sediment movement, and sediment cores were used to measure bivalve abundance. Data were collected across seagrass edges in vegetated and unvegetated locations, or along transects spanning the natural edge of meadow vegetation. Manmade bare patches were also created in the study area to collect data along patch edges. Study sites 1 and 2 were approximately 100m apart along the northern edge of the seagrass meadow. A PDF figure describing the locations is included as Site_Figure.pdf along with the data tables.
Compressible Hydrodynamics Simulation Data for "Standing Shock Prevents Propagation of Sparks in Supersonic Explosive Flows"
<p><strong>Background</strong></p> <p>This data is a 2D cross-section from a 3D compressible hydrodynamics simulation (Hyburn / AMRex code) of a rapid decompression / shock tube experiment at Special Technologies Laboratory. The simulated shot is a pure argon gas decompression from 1000Psi to atmosphere. </p> <p>This data is used in figures 3 and 5 of the paper "Standing Shock Prevents Propagation of Sparks in Supersonic Explosive Flows".</p> <p>Electric sparks and explosive flows have long been associated with each other. Flowing dust particles originate charge through contact and separate based on inertia, resulting in strong electric fields supporting sparks. These sparks can cause explosions in dusty environments, especially those rich in carbon, such as coal mines and grain elevators. Recent observations of explosive events in nature and decompression experiments indicate that supersonic flows of explosions may alter the electrical discharge process. Shocks may suppress parts of the hierarchy of the discharge phenomena, such as leaders. In our decompression experiments, a shock tube ejects a flow of gas and particles into an expansion chamber. We imaged an illuminated plume from the decompression of a mixture of argon and <100 mg of diamond particles and observe sparks occurring below the sharp boundary of a condensation cloud. We also performed hydrodynamics simulations of the decompression event that provide insight into the conditions supporting the observed behavior. Simulation results agree closely with the experimentally observed Mach disk shock shape and height. This represents direct evidence that the sparks are sculpted by the outflow. The spatial and temporal scale of the sparks transmit an impression of the shock tube flow, a connection that could enable novel instrumentation to diagnose currently inaccessible supersonic granular phenomena.</p> <p><strong>Accessing Data</strong></p> <p>The data is saved as python numpy zipped archives numbered by the timestep in the simulation. Files starting with 'tube' contain data from inside the shock tube. Files starting with 'near_vent' contain data from the expansion chamber above the nozzle. All units are in SI.</p> <p>Each .npz file is an array file generated with python numpy.savez(). It can be opened with:</p> <p><em>import numpy as np</em></p> <p><em>data = np.load('<name>.npz')</em></p> <p>The data is an python dictionary. The dictionary keys can be displayed with:</p> <p><em>print(data.files)</em></p> <p>The numpy arrays can be accessed by keyname:</p> <p><em>print(data['keyname'])</em></p> <p>The key names correspond to physical quantities (density, temperature, etc.). All particle quantities are 0 as the simulation did not include particles.</p>
Hydrodynamic field data near Galveston, Texas wetland edges to help assess storm impacts and erosion
<p>Water free surface elevation measurements via submerged pressure transducers along transects near Galveston Bay wetland edges</p>
A high-resolution, multi-decadal, free-running, hydrodynamic simulation of the East Australia Current System using the Regional Ocean Modeling System (Version 3.0, 1994-2019)
<p>The data is from a Regional Ocean Modelling System free-running, hydrodynamic simulation of the East Australian Current System. The model has a horizontal resolution of 2.5-6 km in the cross-shore direction and 5 km in the alongshore direction, and 30 vertical s-levels. The model domain covers the southeastern Australia oceanic region from 25.1-41.5°S and 147.1-162.2°E, and the grid is orientated 20 degrees clockwise to be predominantly orientated alongshore. The time period covered is 02 Jan 1994 to 28 Feb 2019. The model outputs provided are daily averages of the following variables: Two-dimensional variables: Sea surface height (zeta), barotropic cross-grid velocity (u) and barotropic along-grid velocity (v). Three-dimensional variables: Temperature (temp), salinity (salt), density (rho), cross-grid velocity (u), along-grid velocity (v) and vertical velocity (w), temperature time rate of change (temp_rate), temperature horizontal advection term (temp_hadv), temperature vertical advection term (temp_vadv), temperature horizontal diffusion term (temp_hdiff), temperature vertical diffusion term (temp_vdiff). In this version, the heat budget terms (temp_rate, temp_hadv, temp_vadv, temp_hdiff and temp_vdiff) are set to be zeros on the land.</p> <p> </p> <p>This model is part of the <a href="../records/8294716"><strong>South East Australian Coastal Ocean Forecast System (SEA-COFS)</strong></a> suite of models.</p>
Hydrodynamic modeling data for Synthesis of Juvenile Steelhead Responses to Hydrodynamic Conditions in the Sacramento-San Joaquin Delta
This data release includes the output variables extracted from the UnTRIM Bay-Delta hydrodynamic model (hydrodynamic model) for use in evaluating the effects of hydrodynamics on the behavior of acoustically-tagged juvenile steelhead in the Sacramento-San Joaquin Delta. Work was funded by Proposition 1 and completed by Anchor QEA, LLC, and U.S. Geological Survey for the State Water Contractors under a Proposition 1 Grant (Evaluating Juvenile Salmonid Behavioral Responses to Hydrodynamic Conditions in the Sacramento-San Joaquin Delta), contracted by Delta Stewardship Council. Not all the hydrodynamic model output variables in the output provided with this memorandum were used in the final fish models used to analyze steelhead responses. Model output for additional variables and locations were included for completeness and to make these output files more broadly useful to researchers interested in other locations or variables in the Sacramento-San Joaquin Delta. Hydrodynamic model simulations were conducted for 2011, 2012, 2013, 2014, 2015, and 2016, with hydrodynamic model output variables provided at the same locations for each period simulated. The model simulation for each year spanned the full period of steelhead detections in the telemetry data collected during that year.
Rigid and hinged very large floating structure (VLFS) dataset - Kelvin Hydrodynamics Laboratory
<p>This dataset corresponds to the measurements performed at the Kelvin Hydrodynamics Laboratory at the University of Strathclyde, in August 2022, to assess the motion performance and internal loading of a rigid and hinged very large floating structure (VLFS) under regular waves. The VLFS was constructed with three pontoons and two hinges. The hinges were replaced with aluminium steel bars to built the rigid VLFS. The dimensions of each pontoon of the VLFS were 580 mm x 580 mm x 52 mm. Each pontoon was built with 2 mm layer of carbon fibre and a 50 mm layer of PVC foam.</p><p>The VLFS was tested in regular waves at two incidences: 0 degrees and 30 degrees. For 0 degree incidence, the wave frequencies tested ranged from 0.4 to1.6 Hz in intervals of 0.1 Hz. Four wave heights were tested, h=5, 10, 20 and 40 mm. For 30 degree incidence, the same range of frequencies were tested, but only one wave height, h=5 mm. Preliminary results for some of the data at 0 degrees incidence can be found in the conference paper: https://doi.org/10.36688/ewtec-2023-389. Further analysis of this dataset and additional results are in preparation for a journal manuscript.</p><p>The following files are included as part of the dataset:</p><ol><li>Motion files (Matlab files).</li><li>Strain gauge and wave height files (Matlab files).</li><li>Data description file - Description of files.</li><li>Test matrix - Test cases summarised with nomenclature used in files.</li><li>Matlab script to sort out position of motion spheres as depicted in Figure 1.</li><li>Video of the hinged VLFS subject to a train of regular waves at f=0.8 Hz, i.e. when the wavelength is of similar length to the length of the platform, i.e. f=0.8 Hz.</li></ol><ul><li>The motion files contain the time series information recorded for each of the motion detection spheres. Because the motion raw data is not labelled sequentially, it is necessary to run the Matlab file included in the data repository to sort out the information of the spheres.</li><li>The strain gauge files contain the raw strain gauge data (8 channels) and the wave gauge data with the file number describing the corresponding test in the test matrix.</li></ul><p>The VLFS was equipped with 36 motion detection spheres and 8 strain gauges. The diagram and notation of each sphere is depicted in Figure 1. Figure 1 is available in the Data description document.</p><p> </p>
Kimbe Bay Current Meter Data associated with Hydrodynamics Paper
<p>These data are the current meter data from each site and sea surface temperature data used in the paper " Contrasting hydrodynamic regimes of submerged pinnacle and emergent coral reefs". </p>
Example input files and output data for 1D hydrodynamic simulations of shock compressed iron
<p>Example input files and output data for 1D hydrodynamic simulations of shock compressed iron. Input files consists of 3 examples from the SIMEX github wiki page for a 50 micron CH ablator with 5 micro Fe foil (laser pulse is a 6 ns flat top pulse, 1064 nm with 0.3 TW/cm<sup>2</sup>). Output data are from Esther hydrocode in .txt format and the SIMEX opmd.h5 format.</p>
Atmospheric, hydrodynamic and water quality observations from environmental-quality stations, water level sensors, acoustic Doppler velocimeters, and meteorological stations located at the Guadalquivir river estuary (2008 - 2010)
<p>The dataset included in this repository was obtained during the project entitled “Propuesta metodológica para diagnósticar las consecuencias de las actuaciones humanas en el estuario del Guadalquivir” funded by the Autoridad Portuaria de Sevilla (APS), by the Consejería de Innovación, Ciencia y Empresa (Junta de Andalucía), CTM2011-22580, MedEX (CTM2008-04036-E) and PR11-RNM-7722. The data were collected in real time from 2008 until 2010 with a remote monitoring system installed by the Institute of Marine Sciences of Andalusia (ICMAN-CSIC) (Navarro et al., 2011).</p> <p> </p> <p>The environmental quality station recorded turbidity, temperature, conductivity, normalized turbidity, dissolved oxygen, oxygen, oxygen saturation, percentage of oxygen saturation, fluorescence, normalized fluorescence, and salinity every thirty minutes. Current data were measured every 15 minutes by means of acoustic current profilers. The former datasets were obtained at several depths and different locations along the Guadalquivir estuary. Water level sensors recorded the position of the free water surface every 10 minutes at several locations along the Guadalquivir estuary. Wind velocity and direction and solar radiation were measured every 10 minutes in a meteorological station at the mouth of the Guadalquivir estuary.</p> <p>Brief description of dataset.</p> <ul> <li> <p>velocities.csv (in m/s)</p> </li> <li> <p>Turbidity.csv (in Volts), temperature (in Celsius), conductivity (in Siemens/m), normalized turbidity (in FNU), dissolved oxygen (mg/L), oxygen (in Volts), fluorescence (in Volts), normalized fluorescence (in Volts), oxygen saturation (mg/L), percentage of oxygen saturation (%), salinity (in PSU).</p> </li> <li> <p>qual_Salmedina.csv, R_mean (mean radiative flux in W/m²), R_max (max radiative flux in W/m²), Rel_humidity (relative humidity in %), D_mean (wind mean direction in degrees), D_max (wind maximum direction in degrees), D_sig (standard deviation of the wind direction in degrees), V_mean (mean wind velocity in m/s), V_max (maximum wind velocity in m/s), V_sig (standard deviation of the wind velocity in m/s), P_atm_mean (mean atmospheric pressure in mbar), T_mean (mean air temperature in Celsius), T_max (maximum air temperature in Celsius), T_sig (standard deviation of the air temperature in Celsius).</p> </li> <li> <p>Sealevel.csv (in meters)</p> </li> </ul> <p>A wide description of the datasets can be found in Navarro et al (2011).</p> <p>Contact person: infogdfa@ugr.es (or mcobosb@ugr.es)</p>
Measurement and prediction of bottom boundary layer hydrodynamics under modulated oscillatory flows
<p>Experimental and numerical model data pertaining to the manuscript "Measurement and prediction of bottom boundary layer<br> hydrodynamics under modulated oscillatory flows" accepted for publication in Coastal Engineering (<a href="https://doi.org/10.1016/j.coastaleng.2021.103954">https://doi.org/10.1016/j.coastaleng.2021.103954</a>)</p> <p>Please read the README.txt file for more information.</p>
Impact of nonlinear hydrodynamic modelling on geometric optimisation of a spherical heaving point absorber
<p>Due to the amount of iterative computation involved, researchers involved in geometric optimisation of wave energy devices typically employ linear hydrodynamic models. However, the exaggerated motion of wave energy devices, aided by energy maximising control action, challenges the assumptions upon which linear hydrodynamic modelling relies. Furthermore, the optimal device geometry is also sensitive to the nature of the energy-maximisation controller employed, and to the set of wave conditions over which the optimisation is carried out.<br> <br> In order to focus on the essential issues, this study takes the simplest possible device for optimisation, a heaving sphere (with just one free parameter), but one which exhibits nonlinear hydrodynamic characteristics, due to the non-uniform cross-sectional area. The study examines the sensitivity to the inclusion of nonlinear Froude-Krylov forces. In addition, the sensitivity of the optimal device size to differences in the applied control algorithm is also studied, as are effects due to different representative sea state representations and performance evaluation criteria.</p>
Modelled hydrodynamic profiles and salmon louse larval densities at Norwegian salmon farms
<p>Data compiled for use by the PreventLice web app, a decision support tool intended to help Norwegian salmon farmers avoid salmon louse infestations: <a href="https://havforskningsinstituttet.shinyapps.io/preventlice">https://havforskningsinstituttet.shinyapps.io/preventlice</a></p> <p>Each file contains the relevant data for a registered salmonid farm in Norway, identified by its locality number according to the Norwegian <a href="https://sikker.fiskeridir.no/akvakulturregisteret/web/sites">Aquaculture Registry</a>. A total of 1023 localities are included in version 1.0.0.</p> <p>The data are in long rectangular format, with each row corresponding to a single depth interval on a single date. Each row provides variables for locality number ("loc"), date ("date"), depth (m, "depth"), daily mean temperature (°C, "meanTemp"), daily mean salinity (ppt, "meanSal"), daily mean current speed (ms<sup>-1</sup>, "meanCurrSpd"), daily 95th percentile current speed (ms<sup>-1</sup>, "95PercCurrSpd"), daily salmon louse infestation pressure (copepodids m<sup>-3</sup>, "meanCopDensity"), and daily mean significant wave height (m, "SignWaveHeight").</p> <p>Temperature, salinity and current speeds are taken from the NorFjords-160 model (<a href="https://doi.org/10.1016/j.ecss.2020.107028">Dalsøren et al. 2020</a>), a finer-scale update of the NorKyst-800 model (<a href="https://doi.org/10.1007/s10236-020-01378-0">Asplin et al. 2020</a>). Wave height data are taken from the MyWaveWAM800m Norwegian coastal wave forecasting system (<a href="https://thredds.met.no/thredds/fou-hi/mywavewam800.html">Norwegian Meteorological Institute</a>). Salmon louse copepodid densities are estimated by coupling louse biology and behaviour parameters with hydrodynamic predictions from NorKyst-800 (<a href="https://doi.org/10.1371/journal.pone.0201338">Myksvoll et al. 2018</a>).</p>
The influence of the properties of inorganic solvents on the hydrodynamic diameter of TiO2 nanoparticles
<p>In this model the property of a nanomaterial is predicted not on the basis of descriptors characterizing the chemical composition of nanoparticles or physical properties of the initial nanoforms, but on the basis of descriptors describing the dispersion medium (pH, IP, D3_HeteroNonMetals) and the property of nanoparticles dependent on it (Potential ζ). </p> <p>The observed small size of the hydrodynamic diameter of TiO2 in solvents of strong acids and bases compared to other solvents may indicate stronger repulsive interactions between nanoparticles than in the case of other systems. Moreover, in the case of salt solutions, the observed large size of the hydrodynamic diameter of TiO2 may be the result of a thicker electrical layer surrounding the particles in the dispersion system.</p>
Data of the publication "Hydrodynamics in long-range interacting systems with center-of-mass conservation"
<p>In systems with a conserved density, the additional conservation of the center of mass (dipole moment) has been shown to slow down the associated hydrodynamics. At the same time, long-range interactions generally lead to faster transport and information propagation. Here, we explore the competition of these two effects and develop a hydrodynamic theory for long-range center-of-mass-conserving systems. We demonstrate that these systems can exhibit a rich dynamical phase diagram containing subdiffusive, diffusive, and superdiffusive behaviors, with continuously varying dynamical exponents. We corroborate our theory by studying quantum lattice models whose emergent hydrodynamics exhibit these phenomena.</p>
Hydrodynamic and morphological information, and the absolute variations of the vulnerability indices for the period 2000-2015 of the Spanish Iberia Peninsula estuaries.
<p>The dataset included in this repository was obtained during the project entitled 'Sensibilidad física y biotic de los estuarios peninsulares al cambio global (SENSES)' funded by 'Fundación Biodiversidad', PRCV00487. The data were used in the research article 'Sensitivity of Iberian estuaries to changes in sea water temperature, salinity, river-flow, mean sea level, and tidal amplitudes' submitted to <em>Estuarine, Coastal and Shelf Science</em>.</p> <p>Brief description of dataset:</p> <p>For each estuary, the following parameters were calculated</p> <ul> <li>Fachade: the location of the estuary</li> <li>Area (km<sup>2</sup>) </li> <li>D (m): water depth at the mouth of the estuary in 2000 and 2015</li> <li>Tidal Prim (m<sup>3</sup>)</li> <li>Q<sub><em>f</em></sub> (m<sup>3</sup>/s): river flow in 2000 and 2015</li> <li><em>a </em>(m): tidal amplitude of the free surface elevation in 2000 and 2015</li> <li>∆<em>U</em> (m/s): absolute variation of the tidal current amplitude between 2000 and 2015</li> <li>∆<em>E</em> (W/m<sup>2</sup>): absolute variation of the tidal energy flux propagation index between 2000 and 2015</li> <li>∆<em>Ri </em>: absolute variation of the bulk Richardson number index between 2000 and 2015</li> <li>∆<em>SI</em>: absolute variation of the salinity intrusion index between 2000 and 2015</li> </ul> <p>A wide description of the parameters can be found in Serrano, M. A. et al (submitted to <em>Estuarine, Coastal and Shelf Science</em>)</p> <p>Contact person: mserranog@ugr.es</p>
Hydrodynamic and turbulence under breaking waves at the CIEM flume, Hydralab +
<p>Processed phase-averaged experimental data of the bichromatic wave condition as reported in:</p> <ul> <li>van der Zanden, J., van der A, D.A., Cáceres, I., Eltard Larsen, B., Fromant, G., Petrotta, C., Scandura, P., Li, M. (2019). Spatial and temporal distributions of turbulence under bichromatic breaking waves. Coastal Engineering, 146, 65–80. https://doi.org/10.1016/j.coastaleng.2019.01.006</li> <li>Larsen, B.E., van der A, D.A., van der Zanden, J., Ruessink, G., Fuhrman, D.R. (2020). Stabilized RANS simulation of surf zone kinematics and boundary layer processes beneath large-scale plunging waves on a breaker bar, Ocean Modelling, 155, 101705. https://doi.org/10.1016/j.ocemod.2020.101705</li> </ul>
Datasets for "Hydrodynamic and hydromagnetic energy spectra from large eddy simulations"
<pre>This directory contains an index.html file with links to the run directories and idl plotting routines with secondary data for the other figures for the paper "Hydrodynamic and hydromagnetic energy spectra from large eddy simulations" Haugen & Brandenburg. If anything turns our to be incomplete, please email brandenb@nordita.org.</pre>
Data of physiology, biomechanics and hydrodynamics of a freshwater macrophyte
<p>This data package provides post-processed data used in the manuscript “Linking plant stress and hydrodynamics: evidence from freshwater macrophytes” submitted to Water Resources Research. The data package contains data obtained from direct measurements of maximum quantum yield of photosystem II, morphological characteristics and flexural rigidity of the freshwater macrophyte <em>Potamogeton natans</em>. Further, data of flow velocity, drag force, plant deflected height and plant centroid height obtained from flume experiments carried out with samples of <em>P. natans</em> are reported.</p>
Near-surface rheology and hydrodynamic boundary condition of semi-dilute polymer solutions
<p>Data appearing in the figures of the article DOI:10.1039/D0SM02116D.</p>
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