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5,371 results for “Flow”
Evaluation Data of the Implementation of the Approach for Automatic Test Generation for Information-Flow Properties
<p>This data set contains the programs for which the automatic test generation approach of the KeY theorem prover was used to automatically generate noninterference tests.</p> <p>The approach is described in <a href="http://dx.doi.org/10.1145/3297280.3297500 ">http://dx.doi.org/10.1145/3297280.3297500 </a></p> <p>DATA<br> ---------<br> The data folder contains the secure and insecure programs which were evaluated and the tests which were generated for them.</p> <p>Each program is in the folder "program" and is written in Java and specified in an extended version of the JML specification language. Check out <a href="http://dx.doi.org/10.5445/IR/1000046878">http://dx.doi.org/10.5445/IR/1000046878</a> for a reference on the used specification language.</p> <p>For each example we provide the tests that were generated. For the insecure examples we provide the tests generated with each of the two options of our approach. The tests generated with the option for searching for counterexamples is in the folder "WithPost" of each insecure example.</p> <p> </p>
Shear Wave Splitting and Mantle Flow beneath Alaska Data Set
<p>Entire data set for the (under review) publication "Shear Wave Splitting in Alaska."</p> <p>McPherson_S1_Station_Info is a table that contains the following columns (with header row): Station Name, Network, Latitude (Deg), Longitude (Deg). This is a table of all the seismic stations in Alaska and western Canada that we downloaded data from. Only stations that were active from Jan 1, 2010, to Aug 18, 2017 are included.</p> <p>McPherson_S2_Event_Info is a table that contains the following columns (with header row): Julian Date, Origin Time, Latitude (Deg), Longitude (Deg), Depth (km), Magnitude (Mw). This is a table of all the seismic events that occurred between Jan 1, 2010, to Aug 18, 2017 within the distance range 80 to 140 degrees from a station, over moment magnitude 5.</p> <p>McPherson_S3_Results_Info is a table that contains the following columns (with header row): Station Name, Back Azimuth (Deg), Distance (Deg), Fast Direction (Deg), Lower Bound (Deg), Upper Bound (Deg), Time Difference (sec), Lower Bound (sec), Upper Bound (sec), Julian Date, Origin Time. This table contains all of the minimum energy method (Silver & Chan, 1991) results that are displayed in Figures 4, 6-12 of the paper under review.</p> <p>McPherson_S4_Nulls_Info is a table that contains the following columns (with header row): Station Name, Back Azimuth (Deg), Distance (Deg), Julian Date, Origin Time. This tables contains all the null results displayed in Figure 5 of the paper under review.</p>
Participant survey data from the citizen science project FLOW, 2021
<p>This dataset is linked to the following publication:</p> <p>von Gönner, J., Masson, T., Köhler, S., Fritsche, I., Bonn, A. (in press): Citizen science promotes knowledge, skills and collective action to monitor and protect freshwater streams. People and Nature.</p> <p> </p>
Daily river flow records for the River Lochy (Mucomir Cut) at Gairlochy, Scotland
<p>Daily river flows of the River Lochy (Mucomir Cut) at Gairlochy. Approx grid reference NN183840</p> <p>Data collected by Capt. W. N. McClean via his organisation River Flow Records.</p> <p>Record spans the period 1935-10-01 to 1944-09-30 with no gaps.</p> <p>Units cubic feet per second. Based on a calibration developed from curret meter measurements applied to stage measurements taken once per day.</p> <p>We acknowledge the sponsorship of Scottish Hydro-Electric and the Scottish Environment Protection Agency in suporting the costs of creating digital time series.</p> <p>The catchment is in many respects natural, but Loch Lochy has the Caledonian Canal running through it, completed in 1822.</p> <p>Subsequent to McClean's colletion of these records, the flow of the River Lochy via the Mucomir Cut was harnessed by the North of Scotland Hydro-Electric Board by the construction of the Mucomir Power Station, commissioned in 1962.</p> <p>At the time of writing (2024), the Scottish Environment Protection Agency (SEPA) operate gauges in the Lochy system at Gairlochy and Camisky.</p>
A new in vitro blood flow model for the realistic evaluation of antimicrobial surfaces
<p>Dataset to the publication</p> <p>A new <em>in vitro</em> blood flow model for the realistic evaluation of antimicrobial surfaces</p> <p>Juliane Valtin, Stephan Behrens, André Ruland, Florian Schmieder, Frank Sonntag, Lars D. Renner, Manfred F. Maitz, Carsten Werner</p> <p><em>Adv. Healthcare Mater.</em> 2023, 2301300. <a href="https://doi.org/10.1002/adhm.202301300">https://doi.org/10.1002/adhm.202301300</a></p>
Dataset for "Deflected Mantle Flow and Shearing-aligned Lithospheric Melt under the Strike-slip Dead Sea Rift"
<p>Dataset 1: All of the individual shear-wave splitting measurements in the Dead Sea rift, including 1855 A and B measurements and 1088 Null measurements</p> <p>Dataset 2: Three component seismic waveforms used for shear-wave splitting measurement, for PKS, SKKS, and SKS, respectively</p> <p>Dataset 3: Earthquake catalogue with magnitude Mb 2.6 or above in the Dead Sea rift. Downloaded from the International Seismological Centre (https://www.isc.ac.uk/)</p> <p> Reference: International Seismological Centre (2024), On-line Bulletin, [Dataset] doi:10.31905/D808B830</p> <p>Dataset 4: Holocene Volcano List. Downloaded from Global Volcanism Program (https://volcano.si.edu/volcanolist_holocene.cfm)</p> <p> Reference: Global Volcanism Program, 2024. Volcanoes of the World (v. 5.2.2; 22 Aug 2024). Distributed by Smithsonian Institution, compiled by Venzke, E. [Database] doi:10.5479/si.GVP.VOTW5-2024.5.2</p>
Data supporting 'Ice loss in the European Alps until 2050 using a fully assimilated, deep-learning-aided 3D ice-flow model'
<p>The dataset supporting our publication '<strong>Ice loss in the European Alps until 2050 using a fully assimilated, deep-learning-aided 3D ice-flow model</strong>' in <em>Geophysical Research Letters.</em></p> <p>The main .zip archive contains a set of NetCDF files detailing:</p> <ul> <li>Initial optimised glacier states (geology-optimized...)</li> <li>Simulation results (Prog20...)</li> </ul> <p>Initial states and results are given by cluster (see Figure 1 in the paper), as shown in all filenames (C1 through to C12). Prognostic simulation filenames additionally distinguish between runs between 1999 and 2019 (Prog2020) and between 2020 and 2050 (Prog2050). 'NV'/'NoVel' and 'NT'/'NoThk' refer to simulations using the partial optimisation (optimisation without including velocity/thickness observations) as detailed in the paper. 'AV' at the end of the filename denotes the integrated area/volume results file, as opposed to the 2D raster results file. A 'V' before the cluster designation shows that the simulation used the variable SMB as opposed to the fixed SMB (see the paper for details). 'ID' before the cluster designation shows that the simulation was using extrapolated SMB based on the trend in SMB since 2000, instead of assuming the continuation of the current SMB. 'ID' on its own denotes linear extrapolation and 'IDQ' denotes quadratic extrapolation (not used in the published paper). 'SMBF' in the filename shows that the simulation used the SMB-elevation feedback.</p> <p>The additional .zip archive contains the code of IGM v1.0 used to produce the model results. For details on installing and using IGM, please see the Github page at <a href="https://github.com/jouvetg/igm.The">https://github.com/jouvetg/igm</a>.</p> <p>A further .zip archive (in version 3 - Sims2010-2022.zip) contains the simulations based on linear extrapolation of the observed trend in SMB between 2010 and 2022, following the same nomenclature as in the principal archive (see above).</p> <p>Version 4 contains an additional mosaicked DEM of the results for the whole Alps with the ice removed to give the complete basal topography (kindly processed by T. Léger at UNIL) using the Japan Aerospace Exploration Agency (2021) ALOS World 3D 30 meter DEM. V3.2, Jan 2021. Distributed by OpenTopography. <a title="https://doi.org/10.5069/G94M92HB" href="https://doi.org/10.5069/G94M92HB" target="_blank" rel="noreferrer noopener">https://doi.org/10.5069/G94M92HB</a>. Accessed: 2024-09-09.</p>
Data files for the manuscript "Extended kinetic theory applied to pressure-controlled shear flows of frictionless spheres between rigid, bumpy planes"
<p>This depository contains the data of all DEM simulations used in the manuscript titled "Extended kinetic theory applied to pressure-controlled shear flows of frictionless spheres between rigid, bumpy planes" submitted to Soft Matter in July 2024.</p> <p>The data in the excel file are the measurements obtained after the coarse graining procedure.</p>
Data for "Impact of the Out-of-Plane Flow Shear on Magnetic Reconnection at the Flanks of Earth's Magnetopause"
<p>Data for Figures 3-8 in the paper (data for Figures 5 has been updated on 2024-09-20). The data is compatible with all data-analysis software. Here are the guidelines for reading and visualizing the data:</p> <p>(1) The filenames "noshear", "MA0p7", and "MA2p3" correspond to the simulation runs with no flow shear, Mach number M_A=0.7 flow shear, and M_A=2.3 flow shear.</p> <p>(2) The "upper" and "lower" mean upper and lower current sheet, corresponding to dusk-side and dawn-side reconnection respectively. For the "noshear" case, only the "upper" is considered.</p> <p>(3) Each data file (*.dat) is written in ASCII format and has multiple columns. The first row is the header.</p> <ul> <li>The first column is always the x-coordinates of the figure. </li> <li>For the line plots, all columns starting from the second column are the y-coordinates for different variables. The variables names can be found at the header. </li> <li>For the 2D image plots, the second column is the y-coordinates, and the third column is the value of the variable at a given (x,y) location. </li> </ul> <p>(4) The files "fig4_*_field_*.dat" are the magnetic potential in the x-y domain. The contour of this potential gives the in-plane field line configurations.</p>
Labor flows and input-output connections in Hungary
<p>Aggregated data on labor flows and input-output connections in Hungary (2015-2017).</p> <p>Related preprint: https://arxiv.org/abs/2405.07071</p> <p>Interactive visualization site: https://vis.csh.ac.at/colocation-suppliers/</p> <p>The related research by Sándor Juhász was supported by the European Union’s Marie Sklodowska-Curie Postdoctoral Fellowship Program (SUPPED, grant number 101062606).</p> <p>The data preparation was done with the help of the Databank of HUN-REN Centre for Economic and Regional Studies. The shared datasets are based on the value-added tax return data files of the Hungarian Central Statistical Office. The calculations and conclusions drawn from them are the sole intellectual property of the authors.</p> <p> </p>
Experimental data for validation of a variational RANS level III flow model: water waves over an array of obstacles and Ogee weir flows
<p>Experimental dataset for the validation of a variational RANS level III flow model. The experimental data correspond to experiments on unsteady of water waves over an array of obstacles and steady curved flows over an Ogee weir. The experiments were conducted at the Hydraulics Laboratory at the Univeristy of Córdoba. </p>
Advancing Vanadium Redox Flow Battery Analysis: A Deep Learning Framework for High-Throughput 3D Visualization and Bubble Quantification via Synchrotron X-ray Tomography
<p>Dataset and model of UTILE-Redox - Deep Learning based Tool for Autonomous 3D Bubble Analysis of Vanadium Flow Batteries from Synchrotron X-ray Imaging. This project focuses on the deep learning-based automatic analysis of Vanadium Redox Flow Batteries (VRFB) Synchrotron X-ray tomographies. This repository contains the Python implementation of the UTILE-Redox software for automatic volume analysis, feature extraction, and visualization of the results.</p>
Dataset of a multiphase flow and reactive transport benchmark for radioactive waste disposal
<p>The files include the full dataset (tables and figures) of the comparion the results of a multiphase flow and reactive transport<br>benchmark for radioactive waste disposal. The codes INVERSE-FADES-CORE V2, DuMuX , TOUGHREACT and<br>iCP were benchmarked with 6 test cases of increasing complexity, starting with conservative tracer transport under variably<br>unsaturated conditions and ending with water flow, gas diffusion, minerals and cation exchange.</p>
Ultrasensitive detection of cancer-associated nucleic acids and mutations by primer exchange reaction-based signal amplification and flow cytometry
<p>This dataset contains the raw data that were used for the publication entitled, "Ultrasensitive detection of cancer-associated nucleic acids and mutations by primer exchange reaction-based signal amplificaiton and flow cytometry" published in Biosensors and Bioelectronics on 5 October 2024.</p>
Daily observed, modelled, and infilled river flows for an Irish hydrometric reference network of river flow stations
<p>Here we present a dataset of observed, modelled, and infilled daily river flow data relating to the newly updated Irish Hydrometric Reference Network (IHRN) of high-quality gauging stations located across the Republic of Ireland. Internationally applied selection criteria, analysis of historical observations and flow gauge metadata, stakeholder feedback, and trend assessments aided in the identification of the network’s 51 stations. A combination of the GR4J conceptual hydrological model and a backpropagation neural network driven by catchment specific precipitation and temperature extracted from gridded datasets was used to model flows that subsequently infilled gaps in the observational record for each of the series (from commencement of each station’s record till the end of 2022). Also included are the 2.5 and 97.5 quantile values for each station’s modelled data, which represent the upper and lower uncertainty bounds of the respective ensemble flows derived during the flow generation process. As well as providing a useful means for evaluating the impact of changing climatic conditions on Irish catchments, the IHRN data offers utility for assessing catchment based impacts for flow extremes, and the generation of both historical reconstructions and future climate projections for a range of flow regimes across the island of Ireland.</p>
River flow and catchment rainfall records for the River Garry at Invergarry (Inverness-shire), Scotland, 1913-1915
<p>Daily mean flows for the River Garry at Invergarry (Inverness-shire), Gauge A1, spanning the period 1913-01-01 to 1915-12-31.</p> <p>Data collected by Capt. W. N. McClean via his organisation River Flow Records, assisted by local observers.</p> <p>We acknowledge the sponsorship of Scottish Hydro-Electric and the Scottish Environment Protection Agency in suporting the costs of creating digital time series.</p> <p>Subsequent to the colletion of these records, the River Garry was developed by the construction of dams and hydro power stations below Loch Quoich and Loch Garry.</p> <p>The Scottish Environment Protection Agency (SEPA) subsequently opened a river flow gauging station on the River Garry at Craigard in 1997, approximately 3 km upstream of McClean's gauge, operated until May 2011.</p>
Dataset and code for "Adjoint-aided homogenization for flows through heterogeneous membranes"
<p>This dataset and code support the manuscript 'Adjoint-aided homogenization for flows through heterogeneous membranes' by Kevin Wittkowski, Edouard Boujo, François Gallaire and Giuseppe A. Zampogna, under revision in the <em>Journal of Fluid Mechanics</em>, 2024. The data are Stokes flow simulations around an elliptical solid inclusion with periodic boundary conditions. Direct computations of the average flow quantities for several geometry parameters are compared with shape-sensitivity-based predictions obtained by solving a set of direct and adjoint equations around a circular solid inclusion. Please refer to the manuscript for further details.</p> <p><strong>Contents:</strong></p> <ul> <li><em>comsol_code/Mnn.mph, Mtt.mph:</em> COMSOL Multiphysics 6.0 codes used to generate the datasets;</li> <li><em>README.txt</em>: a .txt file describing the code usage;</li> <li><em>Mnn.txt,Mtt.txt</em>: dataset of the direct evaluations of these two average microscopic quantities, input of the .m files;</li> <li><em>S1_Mnn.txt, S2_Mnn.txt, S1_Mtt.txt, S2_Mtt.txt</em>: dataset containing the first and second order shape sensitivities computed on the reference circular geometry, input of the .m files;</li> <li><em>Mnn.m,Mtt.m:</em> MatLab code used to compare the direct evaluations and adjoint predictions of the microscopic quantities;</li> <li><em>ellipse.m</em>: Matlab function to generate the elliptical deformation;</li> <li><em>.fig</em> files: Matlab figures, output of the .m files. They are used to compare the direct evaluation with the prediction based on the adjoint computations.</li> </ul>
Development and analysis of entropy stable no-slip wall boundary conditions for the Eulerian model for viscous and heat conducting compressible flows
<p>The database used in the submission of "Development and analysis of entropy stable no-slip wall boundary conditions implementation of the Eulerian model for viscous and heat conducting compressible flows."</p> <p>Abstract: Nonlinear entropy stability analysis is used to derive entropy stable no-slip wall boundary conditions for the Eulerian model proposed by Svärd ( <em>Physica A: Statistical Mechanics and its Applications, 2018 </em>). and its spatial discretization based on entropy stable collocated discontinuous Galerkin operators with the summation-by-parts property for unstructured grids. A set of viscous test cases of increasing complexity are simulated using both the Eulerian and the classic compressible Navier–Stokes models. The numerical results obtained with the two models are compared, and differences and similarities are then highlighted.</p>
3D geological models of dolomitized clinoforms and flow simulation results: scenario 2 in Teoh, C.P. et al (2021)
<p>3D geological models of dolomitized clinoforms (10 different realisations) and flow simulation results according to Scenario 2 in Teoh, C.P. et al (2021) doi:<a href="http://doi.org/10.1016/j.marpetgeo.2021.105344">10.1016/j.marpetgeo.2021.105344</a>.<br> Models are built using surface-based modelling approach (doi:<a href="https://doi.org/10.1007/s11004-018-9764-8">10.1007/s11004-018-9764-8</a>). Flow simulations are run with IC-FERST, using unstructured tetrahedral meshes that adapt to geological heterogeneity and flow behaviour throughout the simulation to improve simulation quality and performance.</p> <p>For each of the 10 stochastic realisations, 5 geological models are available with corresponding flow simulation results:<br> - Only clinoforms and facies boundaries<br> - 1 dolomite body per clinothem (~20% dolomite)<br> - 2 dolomite bodies per clinothem (~40% dolomite)<br> - 3 dolomite bodies per clinothem (~60% dolomite)<br> - 4 dolomite bodies per clinothem (~80% dolomite)<br> <br> Input model files for simulation are provided in Exodus (.e) and GMSH (.msh) formats.<br> Flow simulation settings are provided for IC-FERST in .mpml files (<a href="http://multifluids.github.io/">multifluids.github.io</a>)<br> Flow simulation results are provided as:</p> <ul> <li> 3D unstructured adaptive mesh in .vtu format, which can be opened with Paraview (www.paraview.org). Time interval between successive mesh outputs is 1 month.</li> <li> In- and outflow rates and volumetric proportions per phase in .csv</li> </ul> <p>Naming of files and folders:<br> <em>Sxxxxxx_yyyyz</em> where:<br> '<em>xxxxxx</em>' is the stochastic seed number used to sample the input statistics and create the geological model<br> '<em>yyyy</em>' is either 'clino' or 'dolo' to indicate if the model represents respectively only clinoforms, or contains dolomite bodies <br> '<em>z</em>' corresponds to the number of dolomite bodies per clinothem</p>
3D geological models of dolomitized clinoforms and flow simulation results: scenario 1 in Teoh, C.P. et al (2021)
<p>3D geological models of dolomitized clinoforms (10 different realisations) and flow simulation results according to Scenario 1 in Teoh, C.P. et al (2021) doi:<a href="http://doi.org/10.1016/j.marpetgeo.2021.105344">10.1016/j.marpetgeo.2021.105344</a>.<br> Models are built using surface-based modelling approach (doi:<a href="https://doi.org/10.1007/s11004-018-9764-8">10.1007/s11004-018-9764-8</a>). Flow simulations are run with IC-FERST, using unstructured tetrahedral meshes that adapt to geological heterogeneity and flow behaviour throughout the simulation to improve simulation quality and performance.</p> <p>For each of the 10 stochastic realisations, 5 geological models are available with corresponding flow simulation results:<br> - Only clinoforms and facies boundaries<br> - 1 dolomite body per clinothem (~20% dolomite)<br> - 2 dolomite bodies per clinothem (~40% dolomite)<br> - 3 dolomite bodies per clinothem (~60% dolomite)<br> - 4 dolomite bodies per clinothem (~80% dolomite)<br> <br> Input model files for simulation are provided in Exodus (.e) and GMSH (.msh) formats.<br> Flow simulation settings are provided for IC-FERST in .mpml files (<a href="http://multifluids.github.io/">multifluids.github.io</a>)<br> Flow simulation results are provided as:</p> <ul> <li> 3D unstructured adaptive mesh in .vtu format, which can be opened with Paraview (www.paraview.org). Time interval between successive mesh outputs is 1 month.</li> <li> In- and outflow rates and volumetric proportions per phase in .csv</li> </ul> <p>Naming of files and folders:<br> <em>Sxxxxxx_yyyyz</em> where:<br> '<em>xxxxxx</em>' is the stochastic seed number used to sample the input statistics and create the geological model<br> '<em>yyyy</em>' is either 'clino' or 'dolo' to indicate if the model represents respectively only clinoforms, or contains dolomite bodies <br> '<em>z</em>' corresponds to the number of dolomite bodies per clinothem</p>
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