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161 results for “Numerical Simulation”
Discrete-continuum numerical simulations of saltation over a rigid, bumpy bed
<p><span><span><span>The data provided here were obtained from discrete-continuum numerical simulations of saltation over a rigid, bumpy bed. The details of the simulation</span></span><span><span>s</span></span><span><span> are reported in the article entitled “</span></span><span><span><strong>Collisionless kinetic theory for saltation over a rigid, bumpy bed” </strong></span></span><span><span>by D. Berzi, A. Valance and J.T. Jenkins published in 2024 in the Journal of Fluid Mechanics.</span></span></span></p>
The dataset used in numerical simulations based on the resistivity structure of Kusatsu-Shirane Volcano, Japan
<p>The dataset used in the numerical simulations based on the resistivity structure of Kusatsu-Shirane Volcano, Japan. </p> <p>Descriptions of included files:</p> <p><strong>TOUGH_model.zip</strong></p> <p>The data used in the numerical simulations by the TOUGH3 code. It includes ten cases with different permeability structures considered.</p> <p><strong>HT_model.zip</strong></p> <p>The data used in the numerical simulations by the HYDROTHERM code. It includes seven cases with different permeability structures considered.</p>
'Reconciling Surface Deflections From Simulations of Global Mantle Convection' : Numerical model dataset
<p><strong>Output data from TERRA simulations included in 'Reconciling Surface Deflections From Simulations of Global Mantle Convection'</strong></p> <p>Dataset includes:</p> <ul> <li>Full density field (`NC_visc_dens_037.tar.gz`)</li> <li>Radial stresses (directory `radial_stresses`)</li> <li>Spherical harmonic coefficients for density field (`density_sph.037`)</li> <li>Radial viscosity factors (`visc.dat`)</li> </ul> <p>Radial stresses are calculated at depths of:</p> <ul> <li>0 km (surface)</li> <li>45 km</li> <li>180 km</li> <li>270 km</li> </ul> <p>and with various amounts of shallow structure removed:</p> <ul> <li>NC_DT_rmir0 - No shallow structure removed</li> <li>NC_DT_rmir1 - 45 km removed</li> <li>NC_DT_rmir2 - 90 km removed</li> <li>NC_DT_rmir3 - 135 km removed</li> <li>NC_DT_rmir5 - 225 km removed</li> <li>NC_DT_rmir7 - 270 km removed</li> </ul>
Spatio-temporal Features of Intra-seasonal Oceanic Variability in the Philippine Sea from Mooring Observations and Numerical Simulations
<p>This dataset contains the NPOCE (http://npoce.org.cn) data used in the following submission for Journal of Geophysical Research: Oceans:</p> <p>Hu, S., J. Sprintall, C. Guan, B. Sun, F. Wang, G. Yang, F. Jia, J. Wang, D. Hu, and F. Chai (2018), Spatio-temporal Features of Intra-seasonal Oceanic Variability in the Philippine Sea from Mooring Observations and Numerical Simulations, Journal of Geophysical Research: Oceans.</p> <p>Variables in this dataset are eddy kinetic energy (EKE) observed by the NPOCE moorings, longitudes, latitudes, depths and dates.</p> <p> </p> <p> </p>
Development of a dense cratonic keel prior to the destruction of the North China Craton: Constraints from sedimentary records and numerical simulation
<p>This file is created for Liu et al. (2019) -- ‘<em>Development of a dense cratonic keel prior to the destruction of the North China Craton: Constraints from sedimentary records and numerical simulation</em>’. The folder 'mutils-0.2' contains the quick search algorithm tsearch2 (Mutilspackage:http://milamin.sourceforge.net/downloads)</p>
Numerical data pertaining to phase-field simulations of quartz cementation in polycrystalline sandstones
<p>The numerical data in this repository pertains to the simulation results of quartz cementation in polycrystalline sandstones. The simulations were performed using the software package named "Pace3D version 2.5.1". The software license can be purchased at Steinbeis Network (www.steinbeis.de) in the management of Britta Nestler and Michael Selzer under the subject area ‘Material Simulation and Process Optimization’. </p> <p>The data is organized, the way it appears in the figures in the manuscript. Thus, the folders are named according to the figure number in the manuscript. Each folder contains a separate ReadMe.dat file, which contains all the information regarding the data present in that folder.</p> <p> </p> <ul> <li> For the sake of convenience, the simulation data that comprises the pictures is converted to .stl and .vtk format, for visualization using open source software packages like Paraview and MeshLab.</li> <li>The original complete output data is in the formats (e.g. *.phiindex.p3s, *.fluiddynamics_velocity.p3v etc.) which can be visualized using the in-house visualization tools GLviewer and XSimview.</li> <li>The data presented in plots is extracted from the simulation output using the post-processing tool chain of "Pace3D".</li> </ul> <p> </p>
Free surface evolution from numerical wave tank simulations - Experiment W6N5D5
<p>An ensemble of two-dimensional numerical wave tank (NWT) simulations of breaking and non-breaking wave packets. The NWT uses the Gerris software package, a two-phase Navier-Stokes solver that utilises the volume-of-fluid method and explicitly models viscosity and surface tension effects. It is configured in non-dimensional coordinates scaled by the length and time characteristics of a deep-water wave with wavelength 1 m. This dataset contains simulations from experiment W6N5D5 (wind forcing speed equal to 6 times the wave speed, chirped wave packet with 5 waves in the packet signal, deep water) and forms part of an ensemble of experiments available <a href="https://doi.org/10.5281/zenodo.12797829" target="_blank" rel="noopener">here</a>. A full description of the NWT is provided in:</p> <p><a href="https://doi.org/10.1017/jfm.2023.134" target="_blank" rel="noopener">Boettger, D. G., Keating, S. R., Banner, M. L., Morison, R. P., & Barthelemy, X. (2023). An energetic signature for breaking inception in surface gravity waves. Journal of Fluid Mechanics, 959, A33.</a></p> <p><a href="https://doi.org/10.1103/PhysRevFluids.9.054803" target="_blank" rel="noopener">Boettger, D. G., Keating, S. R., Banner, M. L., Morison, R. P., & Barthelemy, X. (2024). Energetic inception of breaking in surface gravity waves under wind forcing. Physical Review Fluids, 9 (5), 054803.</a></p>
Free surface evolution from numerical wave tank simulations - Experiment W0N5D2
<p>An ensemble of two-dimensional numerical wave tank (NWT) simulations of breaking and non-breaking wave packets. The NWT uses the Gerris software package, a two-phase Navier-Stokes solver that utilises the volume-of-fluid method and explicitly models viscosity and surface tension effects. It is configured in non-dimensional coordinates scaled by the length and time characteristics of a deep-water wave with wavelength 1 m. This dataset contains simulations from experiment W0N5D2 (Zero wind forcing, chirped wave packet with 5 waves in the packet signal, intermediate water depth) and forms part of an ensemble of experiments available <a href="https://doi.org/10.5281/zenodo.12797829" target="_blank" rel="noopener">here</a>. A full description of the NWT is provided in:</p> <p><a href="https://doi.org/10.1017/jfm.2023.134" target="_blank" rel="noopener">Boettger, D. G., Keating, S. R., Banner, M. L., Morison, R. P., & Barthelemy, X. (2023). An energetic signature for breaking inception in surface gravity waves. Journal of Fluid Mechanics, 959, A33.</a></p> <p><a href="https://doi.org/10.1103/PhysRevFluids.9.054803" target="_blank" rel="noopener">Boettger, D. G., Keating, S. R., Banner, M. L., Morison, R. P., & Barthelemy, X. (2024). Energetic inception of breaking in surface gravity waves under wind forcing. Physical Review Fluids, 9 (5), 054803.</a></p>
Free surface evolution from numerical wave tank simulations - Experiment W0N5D5
<p>An ensemble of two-dimensional numerical wave tank (NWT) simulations of breaking and non-breaking wave packets. The NWT uses the Gerris software package, a two-phase Navier-Stokes solver that utilises the volume-of-fluid method and explicitly models viscosity and surface tension effects. It is configured in non-dimensional coordinates scaled by the length and time characteristics of a deep-water wave with wavelength 1 m. This dataset contains simulations from experiment W0N5D5 (Zero wind forcing, chirped wave packet with 5 waves in the packet signal, deep water) and forms part of an ensemble of experiments available <a href="https://doi.org/10.5281/zenodo.12797829" target="_blank" rel="noopener">here</a>. A full description of the NWT is provided in:</p> <p><a href="https://doi.org/10.1017/jfm.2023.134" target="_blank" rel="noopener">Boettger, D. G., Keating, S. R., Banner, M. L., Morison, R. P., & Barthelemy, X. (2023). An energetic signature for breaking inception in surface gravity waves. Journal of Fluid Mechanics, 959, A33.</a></p> <p><a href="https://doi.org/10.1103/PhysRevFluids.9.054803" target="_blank" rel="noopener">Boettger, D. G., Keating, S. R., Banner, M. L., Morison, R. P., & Barthelemy, X. (2024). Energetic inception of breaking in surface gravity waves under wind forcing. Physical Review Fluids, 9 (5), 054803.</a></p>
Free surface evolution from numerical wave tank simulations - Experiment W0N9D5
<p>An ensemble of two-dimensional numerical wave tank (NWT) simulations of breaking and non-breaking wave packets. The NWT uses the Gerris software package, a two-phase Navier-Stokes solver that utilises the volume-of-fluid method and explicitly models viscosity and surface tension effects. It is configured in non-dimensional coordinates scaled by the length and time characteristics of a deep-water wave with wavelength 1 m. This dataset contains simulations from experiment W0N9D5 (Zero wind forcing, chirped wave packet with 9 waves in the packet signal, intermediate water depth) and forms part of an ensemble of experiments available <a href="https://doi.org/10.5281/zenodo.12797829" target="_blank" rel="noopener">here</a>. A full description of the NWT is provided in:</p> <p><a href="https://doi.org/10.1017/jfm.2023.134" target="_blank" rel="noopener">Boettger, D. G., Keating, S. R., Banner, M. L., Morison, R. P., & Barthelemy, X. (2023). An energetic signature for breaking inception in surface gravity waves. Journal of Fluid Mechanics, 959, A33.</a></p> <p><a href="https://doi.org/10.1103/PhysRevFluids.9.054803" target="_blank" rel="noopener">Boettger, D. G., Keating, S. R., Banner, M. L., Morison, R. P., & Barthelemy, X. (2024). Energetic inception of breaking in surface gravity waves under wind forcing. Physical Review Fluids, 9 (5), 054803.</a></p>
Free surface evolution from numerical wave tank simulations - Experiment W1N5D5
<p>An ensemble of two-dimensional numerical wave tank (NWT) simulations of breaking and non-breaking wave packets. The NWT uses the Gerris software package, a two-phase Navier-Stokes solver that utilises the volume-of-fluid method and explicitly models viscosity and surface tension effects. It is configured in non-dimensional coordinates scaled by the length and time characteristics of a deep-water wave with wavelength 1 m. This dataset contains simulations from experiment W1N5D5 (wind forcing speed equal to wave speed, chirped wave packet with 5 waves in the packet signal, deep water) and forms part of an ensemble of experiments available <a href="https://doi.org/10.5281/zenodo.12797829" target="_blank" rel="noopener">here</a>. A full description of the NWT is provided in:</p> <p><a href="https://doi.org/10.1017/jfm.2023.134" target="_blank" rel="noopener">Boettger, D. G., Keating, S. R., Banner, M. L., Morison, R. P., & Barthelemy, X. (2023). An energetic signature for breaking inception in surface gravity waves. Journal of Fluid Mechanics, 959, A33.</a></p> <p><a href="https://doi.org/10.1103/PhysRevFluids.9.054803" target="_blank" rel="noopener">Boettger, D. G., Keating, S. R., Banner, M. L., Morison, R. P., & Barthelemy, X. (2024). Energetic inception of breaking in surface gravity waves under wind forcing. Physical Review Fluids, 9 (5), 054803.</a></p>
DLR AS TEA Configuration B1 Numerical Simulation Database
<p>This database contains the results of the numerical simulations conducted in the framework of WP5.4 by DLR AS TEA. See README file for the description of the cases simulated.</p>
DLR AS TEA Configuration A1 and A2 Numerical Simulation Database
<p>This database contains the results of the numerical simulations conducted in the framework of WP5.2 by DLR AS TEA. See README file for the description of the cases simulated.</p>
Local Time Variations of Quiet Time Meridional Winds during June and December based on ICON Observations and Numerical Simulations
<p>The file named '<a href="../api/records/12139509/draft/files/geomagnetic%20index.mat/content" target="_blank" rel="noopener noreferrer">geomagnetic index</a>' includes Kp, F10.7p, By and Bz indices, AE and Dst indices. The file named '<a href="../api/records/12139509/draft/files/MWjym12.mat/content" target="_blank" rel="noopener noreferrer">MWjym06</a>', '<a href="../api/records/12139509/draft/files/MWjym12.mat/content" target="_blank" rel="noopener noreferrer">MWjym12</a>' are the meridional winds of ICON observations in June and December. The file named '<a href="../api/records/12139509/draft/files/VN_mean06.mat/content" target="_blank" rel="noopener noreferrer">VN_mean06</a>', '<a href="../api/records/12139509/draft/files/VN_mean06.mat/content" target="_blank" rel="noopener noreferrer">VN_mean12</a>' , '<a href="../api/records/12139509/draft/files/VN_mean06.mat/content" target="_blank" rel="noopener noreferrer">VNnotide_mean06</a>','<a href="../api/records/12139509/draft/files/VN_mean06.mat/content" target="_blank" rel="noopener noreferrer">VNnotide_mean12</a>' include the parameters of TIEGCM simulated meridional winds and the forcing terms with and without tides in June and December. The file named 'F107_70' is the simulation in December in F10.7=70.</p>
Deliverable 1.1.1.1 BEL-Float project | Dataset containing the results of numerical simulations (motions, forces) of the operational performance analysis - Part 9: Operational and damaged scenarios in regular waves
<p>This dataset contains the results of OpenFAST simulations performed on the DeepCwind OC4 semi-submersible combined with the 5MW NREL turbine for various wind and wave conditions. The basis of the OpenFAST input files are taken from <a href="https://github.com/OpenFAST/r-test/tree/main/glue-codes/openfast/5MW_OC4Semi_WSt_WavesWN">OpenFAST r-test GitHub repository (5MW_OC4Semi_WSt_WavesWN)</a> and adapted to simulate various wind and wave conditions. The turbulent wind field as the input to the InflowWind module is generated using <a href="https://www.nrel.gov/wind/nwtc/turbsim.html">TurbSim</a>. The simulations are performed on a modified version of OpenFAST v3.5.3 to which adaptation to the code is made to extract additional Morison drag output up to 16 cylindrical members. This adapted code is <a href="https://github.com/abkpribadi/openfast/tree/Morison_additional_output">uploaded on GitHub as a branch from a forked OpenFAST repository</a>. In total there are 1152 simulation results consists of 768 irregular waves and 384 regular waves cases. The complete dataset is divided into 9 sub-datasets to which this is part number 9. A report describing this dataset is available on the BEL-Float project website: https://www.owi-lab.be/bel-float.</p>
3D HDF5 data from numerical relativity simulations
<p>3D HDF5 data from numerical relativity simulations. Test data for visualization purposes.</p>
Dataset from "Numerical gravitational backreaction on cosmic string loops from simulation"
<p>This file contains a data table representing the average power spectrum, P_n, of Nambu-Goto cosmic strings evolved under numerical gravitational backreaction. The power spectra and the methods used to produce them are reported on in "Numerical gravitational backreaction on cosmic string loops from simulation" [to appear], by the same authors as this dataset. See Fig. 5 of that paper for a visualization.</p> <p>The file is organized in three columns:</p> <ol> <li>The fraction of evaporation, chi. The range is from 0.0 to 0.7 in steps of 0.1.</li> <li>The mode number, n. The range is from 2^0 to 2^39 in multiplicative steps of 2.</li> <li>The logarithmically binned elements of the power spectrum, nP_n. Bin edges are 2^i to 2^(i+1)-1 for i from 0 to 39.</li> </ol>
Postprocessed data for "Tracing the rain formation pathways in numerical simulations of deep convection"
<p>This dataset is associated with the journal paper "Tracing the rain formation pathways in numerical simulations of deep convection".</p> <p>There are six .npz files containing data for the 5 simulations (CTRL, CTRLrfix, K13, CTRL800, K13800)<br> and one npz file containing data for constructing the rain pdfs of simulation CTRL (Figure 6).</p> <p>This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52‐07NA27344 IM Release number LLNL-MI-843623</p>
Datasets for numerical Monte Carlo simulations of Diclofenac bio-degradation in a soil-water system
<p>This record contains files and main instructions to repeat the numerical simulations of Diclofenac bio-degradation is a soil-water system. The text file Readme.docx contains a description of the overall content of this record, which is organized in two separate folders.</p>
Numerical simulations reproduce field observations showing transient weakening during shear zone formation by diffusional hydrogen influx and H2O inflow
<p>Abstract of the corresponding paper:</p> <p>Exposures on Holsnøy island (Bergen Arcs, Norway) indicate fluid infiltration through fractures into a dry, metastable granulite, which triggered a kinetically delayed eclogitization, a transient weakening during fluid-rock interaction, and formation of shear zones that widened during shearing. It remains unclear whether the effects of grain boundary-assisted aqueous fluid inflow on the duration of granulite hydration were influenced by a diffusional hydrogen influx accompanying the fluid inflow. To better estimate the fluid infiltration efficiencies and the parameter interdependencies, a 1D numerical model of a viscous shear zone is utilized and validated using measured mineral phase abundance distributions and H<sub>2</sub>O-contents in nominally anhydrous minerals (NAMs) of the original granulite assemblage to constrain the hydration by aqueous fluid inflow and diffusional hydrogen influx, respectively. Both hydrations are described with a diffusion equation and affect the effective viscosity. Shear zone kinematics are constrained by the observed shear strain and thickness. The model fits the phase abundance and H<sub>2</sub>O-content profiles if the effective hydrogen diffusivity is approximately one order of magnitude higher than the diffusivity for aqueous fluid inflow. The observed shear zone thickness is reproduced if the viscosity ratio between dry granulite and deforming, re-equilibrating eclogite is ~10<sup>4</sup> and that between dry granulite and hydrated granulite is ~10<sup>2</sup>. The results suggest shear velocities <10<sup>-2</sup> cm/a, hydrogen diffusivities of ~10<sup>-13±1</sup> m<sup>2</sup>/s, and a shearing duration of <10 years. This study successfully links and validates field data to a shear zone model and highlights the importance of hydrogen diffusion for shear zone widening and eclogitization.</p> <p> </p> <p>The files uploaded here represents the numerical codes and dataset utilized to produce the results presented in the associated paper.<br> Find a description of the single code files ([<em>name</em>].m) in the ST1.doxc file.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.