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Figures, plotting scripts, and data for "A fast, low-cost, and stable memory algorithm for implementing multicomponent transport in direct numerical simulations"
<p>This dataset contains the figures, as well as the necessary plotting scripts and data to reproduce them, for the article "A fast, low-cost, and stable memory algorithm for implementing multicomponent transport in direct numerical simulations" by Aaron J. Fillo, Jason Schlup, Guillaume Beardsell, Guillaume Blanquart, and Kyle E. Niemeyer (2019). In addition, the code used to generate the eigenvalues in Table 1 is included.</p> <p>The scripts were run in Matlab 2019a, though none of the versions used should be version-dependent. Furthermore, non-standard functions are included with dependencies hard-coded. We used export_fig (https://github.com/altmany/export_fig) to generate high-quality figures, and redistribute the version used here for reproducibility (export_fig was developed by Oliver J. Woodford and Yair M. Altman, and made available openly under the BSD 3-Clause License).</p> <p>The code included in this dataset is released under the BSD 3-Clause License (see LICENSE.txt for details), other than the source of export_fig, as described. The figures are shared under the Creative Commons Attribution 4.0 International License (CC BY 4.0, https://creativecommons.org/licenses/by/4.0/).</p>
Text-fig. 3. 1, 2. Ensete goldianum (LESQUEREUX) comb. nov, Holotype, USNM 494, Golden Colorado. 1. Numerous seeds on a slab. 2. Detail of seed molds and casts. 3-5 "Sagittaria" megasperma R. W. BROWN. 3. Infructescence head. USNM 167488, lectotype selected by Watt 1971. 4. Isolated fruit showing veins of wing, and longitudinally striate central body and single style, USNM 313282, 5. Additional isolated fruit, USNM 313283. Images 4, 5 light-dark inverted. Scale = 1 cm. in Revisions To Roland Brown'S North American Paleocene Flora
Text-fig. 3. 1, 2. Ensete goldianum (LESQUEREUX) comb. nov, Holotype, USNM 494, Golden Colorado. 1. Numerous seeds on a slab. 2. Detail of seed molds and casts. 3-5 "Sagittaria" megasperma R. W. BROWN. 3. Infructescence head. USNM 167488, lectotype selected by Watt 1971. 4. Isolated fruit showing veins of wing, and longitudinally striate central body and single style, USNM 313282, 5. Additional isolated fruit, USNM 313283. Images 4, 5 light-dark inverted. Scale = 1 cm.
Numerical simulations of the latest caldera-forming eruption of Okmok volcano, Alaska
<p>Raw outputs of the numerical simulations of an explosive volcanic eruption.</p> <p>The file "source.zip" includes all the source files modified compared to the default<br>MFIX 2016-1 files (www.mfix.netl.doe.gov, v.2016). It also includes an example of the input file mfix.dat (run 3). These<br>are raw file intended for enabling result reproductibility. They contain unused <br>optional variables and are not intented (and commented) to serve as tutorials. The<br>subfolder "postmfix" includes the source file for option 6 of the post processing<br>program. Some options are user-defined, and others are hard coded.</p> <p>The file "AllRuns.zip" inculde all the Okmok runs. All runs were generated with <br>MFIX 2016-1 in TFM mode. They are organized in folders corresponding to the naming<br>convention of Table 1. Some runs were generated in several sequences (e.g., 0-300 s,<br>then 300-700 s) that were stitched into a single output bundle. Other sequences were<br>kept separated.</p> <p>The files OK.RES can be openend with Paraview >5.6 and selecting the MFIXReader.</p> <p>The variables are:</p> <p>EP_g = Gas volume fraction<br>Gas Velocity = Gas velocity vector (m/s)<br>P_g = Pressure (Pa)<br>P_star = Solid pressure (Pa)<br>ROP_s_m = Solid density times particle volume fraction of solid phase m (kg/m3)<br>RRates_1 = Gas density (kg/m3)<br>RRates_2 = Gas viscosity (Pa s)<br>Solids_Velocity_x = Velocity vector of solid phase x (m/s)<br>T_g = Gas temperature (K)<br>T_s_x = Temperature of solid phase x (K)<br>Theta_m_x = Granular temperature of solid phase x (m2/s2)<br>U_g = Horizontal component of gas velocity (m/s)<br>V_g = Vertical component of gas velocity (m/s)<br>W_g = Z component of gas velocity (0 because axisymmetric domain)<br>U_s_x = Horizontal component of velocity of solid phase x (m/s)<br>V_s_x = Vertical component of velocity of solid phase x (m/s)<br>W_s_x = Z component of velocity of solid phase x (0 because axisymmetric domain)<br>X_g_x, X_s_x = unused<br>k_turb_g (not always recorded) = Turbulent kinetic energy (J/kg)<br>e_turb_g = duplicate of k_turb_g</p> <p><br>Refer to the MFIX documentation for more details on the format and on the model itself.</p> <p> </p>
Model intercomparison of medicane Ianos using ten mesoscale numerical frameworks
<p>The dataset provides numerical simulations of the high-impact medicane Ianos of September 2020. It is based on a collective effort with five mesoscale models to look for a robust response among ten numerical frameworks used in the community involved in the networking activity of the EU COST Action "MedCyclones" <a href="https://medcyclones.eu/">https://medcyclones.eu/</a></p> <p>The five mesoscale models are:</p> <ul> <li>The BOLAM hydrostatic model and the MOLOCH non-hydrostatic, fully compressible model developed at CNR-ISAC available upon request to <a href="mailto:dinamica@isac.cnr.it">dinamica@isac.cnr.it</a></li> <li>The Met Office Unified Model (MetUM) available for use under a closed licence agreement, further information at <a href="http://www.metoffice.gov.uk/research/modelling-systems/unified-model">http://www.metoffice.gov.uk/research/modelling-systems/unified-model</a></li> <li>The Meso-NH mesoscale non-hydrostatic model of the French research community freely available under CeCILL-C license agreement on <a href="http://mesonh.aero.obs-mip.fr">http://mesonh.aero.obs-mip.fr</a> with two variants included: <ul> <li>one run at Centre National de Recherches Météorologiques (MESONH-CNRM)</li> <li>one run at Laboratoire d’Aérologie (MESONH-LAERO)</li> </ul> </li> <li>The WRF (Weather Research and Forecasting) non-hydrostatic, fully compressible model freely available at <a href="https://github.com/wrf-model/WRF/releases">https://github.com/wrf-model/WRF/releases</a> with five variants included: <ul> <li>one run at the Aristotle University of Thessaloniki (WRF-AUTH)</li> <li>two run at CNR-ISAC (WRF-ISAC and WRF-ISAC-2)</li> <li>one run at the National Observatory of Athens (WRF-NOA)</li> <li>one run at the University of the Balearic Islands (WRF-UIB)</li> </ul> </li> </ul> <p>Four sets of simulations are provided:</p> <ul> <li>Control simulations obtained by initialising the models at 00 UTC on 15 September 2020 and using 6-h operational analyses from the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) as initial and lateral boundary conditions. The horizontal grid spacing is set to 10 km, which approximately matches the resolution of IFS analyses and requires parameterization of deep convection.</li> <li>A first sensitivity test obtained by initialising the models 12 h earlier at 12 UTC on 14 September 2020.</li> <li>A second sensitivity test obtained by using ECMWF Reanalysis v5 (ERA5), which provides higher frequency (hourly) but lower spatial resolution (about 30 km), as initial and lateral boundary conditions.</li> <li>A third sensitivity test obtained by setting the horizontal grid spacing to 2 km, which allows explicit representation of deep convection.</li> </ul> <p>The model output is stored every 3 h until 00 UTC 20 September 2020 and interpolated onto the same regular 0.1°×0.1° horizontal grid and pressure levels. The data files are formatted in Network Common Data Form (NetCDF) and named <strong>runs_ILBC_DDHH_RES.nc</strong> where</p> <ul> <li><strong>ILBC</strong> describes the initial and lateral boundary conditions (IFS or ERA5) </li> <li><strong>DDHH</strong> describes the initial day and hour (1500 or 1412) </li> <li><strong>RES</strong> describes the horizontal grid spacing (10 or 2 km)</li> <li>simulated infrared brightness temperatures are provided in extra files with <strong>RTTOV</strong> suffix for five of the models and variants</li> </ul>
Repository for: "Using automatic calibration to improve the physics behind complex numerical models: An example from a 3D lake model"
<p>Set of numerical experiments supporting the paper entitled "Using automatic calibration to improve the physics behind complex numerical models: An example from a 3D lake model" by Marina Amadori, Abolfazl Irani Rahaghi, Damien Bouffard and Marco Toffolon. Submitted to GMD. </p> <p>The folder contains: </p> <p>simulations: DYNO-PODS + Delft3D experiments on Lake Morat. See https://github.com/louisXW/DYNO-pods for more insights on DYNO-PODS and instructions for installation.</p> <p>scripts: extraction and plotting scripts</p> <p>source_code: modified Delft3D src as available at: https://github.com/eawag-surface-waters-research/Delft3D/tree/d3d4/research/surface_heat_transfer</p>
MSCA SHINE_Project: Numerical results of the soldification-melting of a Si-based alloy (Ultra-high temperature storage)
<p>Project 101145914 — SHINE has received funding withing the MSCA framework. The purpose of this project is to construct a generic model describing the solidification-melting process of ultra-high temperature latent heat thermal energy storage systems based on data-driven analysis and rigorous CFD models. Within the initial steps of the project a preliminary database is being created based on available results from previous UPM’s projects (Thermobat Project) as well as preliminary simulations by using a 2D CFD model. The present dataset contains information of FeSiB alloy solidification-melting close to 1250 oC inside a cylindrical container, under various heating conditions. Analysis of the present data can be also found in the manuscript entitled as ¨Numerical analysis on the state of charge of an ultra-high temperature latent heat energy storage system, SoraPaces, Rome, 2024¨</p>
Files for the numerical results shown in "Far-from-equilibrium travelling pulses in sloped semi-arid environments driven by autotoxicity effects" by Gabriele Grifò, Annalisa Iuorio, and Frits Veerman
<p>This folder contains the code used to produce Fig. 1 and Fig. 8-10 in the paper: "Far-from-equilibrium travelling pulses in sloped semi-arid environments driven by autotoxicity effects" by Gabriele Grifò, Annalisa Iuorio, and Frits Veerman. The preprint version of this paper is available at <a href="https://arxiv.org/abs/2405.1560">https://arxiv.org/abs/2405.1560</a>.</p> <p>In the subfolder "Direct_simulations", the code (to obtain Fig. 1) is based on a MATLAB routine which uses finite differences for spatial discretization with periodic boundary conditions together with MATLAB’s ode15s routine for time integration.</p> <p>The continuation procedure (to obtain Fig. 8-10) is shown in the subfolder "Continuation" based on the software AUTO to analyse the dependence of the constructed travelling pulse solutions of Eq. (3.2) with respect to three system parameters, i.e. A, D, and H. Correspondingly, in each folder 'Continuation_X' where X=A, D, H, the results can be obtained by running the file 'AUTO_script_cont_X', based on the two files 'parab_X.f90' and 'c.parab_X'.</p> <p>Selected solutions for each continuation are stored in the corresponding subfolders 'solutions_X', whereas the tables resulting from the continuation procedure in the scripts are shown in the files 'bifdiag_X.dat'. In each script file further details are provided in order to clarify how to extract the solutions used for the plots.</p>
Visualization of the numerical pose optimization with the JAMDA scoring function using the BFGS and the LSL-BFGS algorithm
<p>These videos demonstrate the behavior of two different optimization algorithms (BFGS and LSL-BFGS) during pose optimization using the JAMDA protein-ligand scoring function.</p> <p>Flachsenberg et al. (2020) (<a href="http://doi.org/10.1021/acs.jcim.0c01095" target="_blank" rel="noopener">10.1021/acs.jcim.0c01095</a>) describes the JAMDA protein-ligand scoring function and the LSL-BFGS algorithm.<br>The data for these videos stems from Experiment 5 in Flachsenberg et al. (2020). In this experiment, the crystal structure of a ligand was numerically optimized in the binding site with respect to the JAMDA scoring function to create the JAMDA-minimized crystal structure. The JAMDA-minimized crystal structure was randomly deflected to generate various starting poses for the numerical optimization.</p> <p>These videos demonstrate the behavior of two optimization algorithms (BFGS and LSL-BFGS) when optimizing one of the generated starting poses. The chosen example for the videos is a structure of ribonuclease A with a 5'-deoxy-5'-N-piperidinouridine inhibitor (PDB code 3d6q, <a href="https://doi.org/10.2210/pdb3D6Q/pdb" target="_blank" rel="noopener">10.2210/pdb3D6Q/pdb</a>, <a href="https://doi.org/10.1021/jm800724t" target="_blank" rel="noopener">10.1021/jm800724t</a>). Each of the videos shows all the intermediate steps the optimization algorithm takes until convergence.</p> <p>The main observation (that is discussed in detail in Flachsenberg et al. (2020)) is that the BFGS algorithm tends to take inappropriately large steps when clashes are present in the structure, resulting in unwanted binding mode changes. This is <em>not</em> the case for the LSL-BFGS algorithm.</p> <h3>Legend</h3> <p>For each iteration, the JAMDA score value, the RMSD to the JAMDA-minimized crystal structure (yellow), and the RMSD to the optimization's starting point (blue) are given. Furthermore, the gradient's norm (representing the main convergence criterion) is shown. In addition to the optimized ligand, also the JAMDA-minimized crystal structure (yellow) and the optimization's starting structure (blue) are shown.</p> <p><br>Each optimization algorithm is shown in two videos: In one video, the optimized ligand is colored by elements. Here, atoms with clashes (positive JAMDA scores) are marked with orange balls. In the other video, the atoms and bonds of the optimized ligand are colored by their individual JAMDA score.</p> <h3>Used Software</h3> <p>The snapshots of the optimization algorithms were rendered using PyMOL 3.0 (<a href="https://pymol.org/" target="_blank" rel="noopener">https://pymol.org/</a>) and further processed using the Pillow 10.4 Python library (<a href="https://doi.org/10.5281/zenodo.12606429" target="_blank" rel="noopener">10.5281/zenodo.12606429</a>). Videos were created from the individual snapshots using FFmpeg 7.0 (<a href="https://www.ffmpeg.org/" target="_blank" rel="noopener">https://www.ffmpeg.org/</a>).</p>
Deliverable 1.1.1.1 BEL-Float project | Dataset containing the results of numerical simulations (motions, forces) of the operational performance analysis - Part 1: Operational scenario with 6.0 m significant wave height
<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 1. A report describing this dataset is available on the BEL-Float project website: https://www.owi-lab.be/bel-float.</p> <p> </p> <p> </p> <p> </p>
Deliverable 1.1.1.1 BEL-Float project | Dataset containing the results of numerical simulations (motions, forces) of the operational performance analysis - Part 2: Operational scenario with 4.5 m significant wave height
<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 2. A report describing this dataset is available on the BEL-Float project website: https://www.owi-lab.be/bel-float.</p>
Deliverable 1.1.1.1 BEL-Float project | Dataset containing the results of numerical simulations (motions, forces) of the operational performance analysis - Part 8: Damaged scenario with 1.5 m significant wave height
<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 8. A report describing this dataset is available on the BEL-Float project website: https://www.owi-lab.be/bel-float.</p>
Deliverable 1.1.1.1 BEL-Float project | Dataset containing the results of numerical simulations (motions, forces) of the operational performance analysis - Part 7: Damaged scenario with 3.0 m significant wave height
<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 7. A report describing this dataset is available on the BEL-Float project website: https://www.owi-lab.be/bel-float.</p>
Deliverable 1.1.1.1 BEL-Float project | Dataset containing the results of numerical simulations (motions, forces) of the operational performance analysis - Part 5: Damaged scenario with 6.0 m significant wave height
<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 5. A report describing this dataset is available on the BEL-Float project website: https://www.owi-lab.be/bel-float.</p>
Deliverable 1.1.1.1 BEL-Float project | Dataset containing the results of numerical simulations (motions, forces) of the operational performance analysis - Part 6: Damaged scenario with 4.5 m significant wave height
<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 6. A report describing this dataset is available on the BEL-Float project website: https://www.owi-lab.be/bel-float.</p>
Deliverable 1.1.1.1 BEL-Float project | Dataset containing the results of numerical simulations (motions, forces) of the operational performance analysis - Part 4: Operational scenario with 1.5 m significant wave height
<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 4. A report describing this dataset is available on the BEL-Float project website: https://www.owi-lab.be/bel-float.</p>
Deliverable 1.1.1.1 BEL-Float project | Dataset containing the results of numerical simulations (motions, forces) of the operational performance analysis - Part 3: Operational scenario with 3.0 m significant wave height
<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 3. A report describing this dataset is available on the BEL-Float project website: https://www.owi-lab.be/bel-float.</p>
Linked collectors and determiners for: ' Endless forms most beautiful': taxonomic revision of the planarian Geoplana vaginuloides (Darwin, 1844) and discovery of numerous congeners (Platyhelminthes: Tricladida).
Natural history specimen data linked to collectors and determiners held within, "' Endless forms most beautiful': taxonomic revision of the planarian Geoplana vaginuloides (Darwin, 1844) and discovery of numerous congeners (Platyhelminthes: Tricladida)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/9dd11965-9958-4665-aef8-d4b9d8d458f0">https://bionomia.net/dataset/9dd11965-9958-4665-aef8-d4b9d8d458f0</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/9dd11965-9958-4665-aef8-d4b9d8d458f0">https://gbif.org/dataset/9dd11965-9958-4665-aef8-d4b9d8d458f0</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Catches of numerous insect species in Rothamsted 160W light trap at Devonport, Tasmania, 1992-2019.
Natural history specimen data linked to collectors and determiners held within, "Catches of numerous insect species in Rothamsted 160W light trap at Devonport, Tasmania, 1992-2019". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/044f96bc-3bf2-4a38-9f7c-8808ab48dbf1">https://bionomia.net/dataset/044f96bc-3bf2-4a38-9f7c-8808ab48dbf1</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/044f96bc-3bf2-4a38-9f7c-8808ab48dbf1">https://gbif.org/dataset/044f96bc-3bf2-4a38-9f7c-8808ab48dbf1</a>. Formatted as a Frictionless Data package.
Evolution of fault reactivation potential in the greater Ruhr region (Germany). Results from analytical and numerical studies.
<p>This dataset presents results of analytical-probabilistic and numerical studies on the evolution of fault reactivation potential in the greater Ruhr region in western Germany. The dataset includes shapefile of major faults in the greater Ruhr region, with their specific dip angles, strike values, slip tendencies, dilation tendencies, fracture susceptibilities, and reduced-risk dilation tendencies. The results of long-term coupled thermo-hydro-mechanical simulations on two conceptual geothermal systems based on the two most prevailing fault architectures in the greater Ruhr region are also included in the dataset. The model results are saved with the COMSOL Multiphysics software format, where the simulations were carried out.</p> <p>Please check the README files for a detailed explanation of both datasets.</p> <p>_________________________________</p> <p>Update on 06/11/2024</p> <p>New version includes only one updated fully coupled thermo-hydro-mechanical model with a NW-SE-striking fault and a finer mesh.</p>
ECOCLIMAP-SG-ML: an ensemble land cover map for numerical weather prediction
<p>This dataset contains ensemble land cover maps for numerical weather prediction at 60 m resolution over Europe. As they were<br>generated thanks to machine learning, the weights and the training data are also provided.</p>
ScienceDex guides
Understand access before you commit
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.