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129 results for “Flow simulation”
Data for: Water system simulation modeling with hydropower optimization and environmental flows: An example with Pywr
<p>This dataset was used in the CenSierraPywr model created for the project "Optimizing Hydropower Operations While Sustaining Ecosystem Functions in a Changing Climate", for the California Energy Commission. Specifically, this data is to support reproducibility of the article describing the basic methods (Rheinheimer et al., in review). The model was built in Pywr, an open-source, linear programming-based Python package for modeling basin-scale water systems in the Central Sierra Nevada, California. Here, we focus on the Stanislaus and Upper San Joaquin River basins as they have high elevation hydropower typically operated to maximize revenue. CenSierraPywr consists of daily water allocations that include both hydroeconomic drivers for hydropower and more advanced environmental flows. Piecewise linear electricity prices from simulated hourly price data are used to drive discretionary hydropower, while environmental flows include the addition of ramping rates. Hydrological inputs include runoff data at the sub-basin level, based on the historical (1950 to 2011) daily gridded (1/16 degree) runoff data generated by the Variable Infiltration Capacity (VIC) hydrologic model developed by Livneh et al. (2013), forced with observed meteorological data and bias-corrected using local gauge data. All data inputs for reproducibility of CenSierraPywr for the Stanislaus and Upper San Joaquin Rivers are included, including original and preprocessed electricity and hydrological data and management-related data specific to certain hydropower projects or facilities.</p>
Simulating flow forming/spinning of as-cast aluminum at elevated temperature: example implicit & explicit FEA
<p>This collection of files largely automates the creation and running of FEA models of rotary forming at temperature. The modelling approaches are detailed further here:</p> <p>M.J. Roy, D.M. Maijer, Analysis and modelling of a rotary forming process for cast aluminium alloy A356, Journal of Materials Processing Technology, Volume 226, 2015, Pages 188-204, ISSN 0924-0136, http://dx.doi.org/10.1016/j.jmatprotec.2015.06.036.<br> </p> <p>Briefly, the multi-stage model was developed with MATLAB 7.2 and Abaqus 11.2 and configured to run on a Linux-based system with PBS functionality, last tested on a muti-node CentOS 5 system. The main script is <strong>FFauto.m</strong>, which will write input files and user subroutines and call <strong>FFauto_Abaqus11Submit.m</strong> to run the input files or intermediate post-processing to set up the next job. More specifically:</p> <ol> <li>FFauto will write an input deck based on 2D implicit heat transfer and then run it.</li> <li>Once the analysis is complete, it will perform some cursory post processing by writing an Abaqus Python script and then submitting that.</li> <li>Based on the post-processing of the implicit analysis, it will then generate a 3D explicit forming analysis input file. Depending on the operator's input, this can include an explicit cooling step as well.</li> <li>It will then submit the 3D analysis.</li> </ol> <p>Note that steps can be skipped - that is, if the results for an implicit heat transfer calculation are available, then it will use those results to generate the explicit step(s).</p> <p>Note that the implicit user subroutine *uhard.f contains a DFLUX subroutine in addition to the UHARD subroutine. This was not employed in the published work. Leave the <em>ArtHeat</em> variable as <em>True</em> to both speed up simulation times and get similar results as published.</p> <p>Running <strong>FFauto.m</strong> is accomplished by submitting the <strong>FFauto4.pbs</strong> file.</p>
A method to determine local aerodynamic force coefficients from fiber-resolved 3D flow simulations around a staple fiber yarn: simulation data
<p>This data set contains all set-up files and necessary scripts to run the simulations performed in the publication <a href="https://doi.org/10.1007/s11044-024-09992-2" target="_blank" rel="noopener">"A method to determine local aerodynamic force coefficients from fiber-resolved 3D flow simulations around a staple fiber yarn"</a>, published in Multibody System Dynamics.</p>
Data from: A geometric VOF method for interface flow simulations
<p>This set is the original data used in the article titled "A Geometric VOF Method for Interface Flow Simulations". In this paper, a novel numerical technique designed for interface flow simulations using the Volume of Fluid (VOF) method on arbitrary unstructured meshes has been introduced. The method is called SimPLIC, which seamlessly integrates Piecewise Linear Interface Calculation (PLIC) and Simpson's rule. The main focus of the proposed method is to compute the volume of the primary phase that moves across a mesh face within a single time step. This is achieved by reconstructing the interface and assessing how the submerged face area evolves over time. Simpson's rule is employed to integrate the time evolution of this submerged face area, ensuring an accurate estimation of the volume of the transported primary phase. The method's robustness was validated by solving a spherical interface advection problem in a non-uniform three-dimensional flow across unstructured meshes with diverse cell types and dimensions. Key metrics such as volume conservation, shape retention, friction boundedness and solving efficiency were meticulously monitored and juxtaposed. Numerical outcomes underscored the precision and adequacy of the PLIC-VOF technique when complemented with Simpson's rule in advecting the interface. Furthermore, the SimPLIC method has been integrated into OpenFOAM v2312 as an unofficial extension and is now accessible to the community.</p>
Fig. 5 in Application of the physical habitat simulation for fish species to assess environmental flows in an Atlantic Forest Stream in South-eastern Brazil
Fig. 5. Average habitat suitability index –HSI– in the upper and lower reach of the riacho São Pedro, for the three fish species.
Fig. 6 in Application of the physical habitat simulation for fish species to assess environmental flows in an Atlantic Forest Stream in South-eastern Brazil
Fig. 6. Weighted usable area (WUA) in the upper and lower reach of the riacho São Pedro, for the three fish species.
Fig. 4 in Application of the physical habitat simulation for fish species to assess environmental flows in an Atlantic Forest Stream in South-eastern Brazil
Fig. 4. Habitat suitability curves for depth (m), mean water column velocity (m/s) and type of substrate for the three fish species in the riacho São Pedro. Substrate types are; 1- large boulder, 2- boulder, 3- cobble, 4- gravel, 5- fine gravel, 6- sand and 7- vegetation.
Fig. 3 in Application of the physical habitat simulation for fish species to assess environmental flows in an Atlantic Forest Stream in South-eastern Brazil
Fig. 3. Frequencies of habitat availability by classes of depth (m), mean velocity (m/s) and type of substrate (1- large boulder; 2- boulder; 3- cobble; 4- gravel; 5- fine gravel; 6- sand and 7- vegetation), obtained by direct survey in the riacho São Pedro.
Fig. 1 in Application of the physical habitat simulation for fish species to assess environmental flows in an Atlantic Forest Stream in South-eastern Brazil
Fig. 1. Map of the rio Guandu basin, with indication of the studied reach in riacho São Pedro. Solid dash = small substation of CEDAE (Water and Sewer Treatment Works of Rio de Janeiro State). WTP: Water Treatment Plant.
Fig. 2 in Application of the physical habitat simulation for fish species to assess environmental flows in an Atlantic Forest Stream in South-eastern Brazil
Fig. 2. Isometric view of the cross-sections in the two target reaches of the riacho São Pedro. Grey color indicates water; solid line indicates the contour of the cross-section (in wet areas and banks).
Time-averaged simulation results and in vivo measurements to show the impact of red blood cells on the flow field in the cortical microvasculature
<p>The dataset contains 5 files. 4 of them are time-averaged results of blood flow simulations with discrete red blood cell (RBC) tracking in realistic microvascular networks. The 5th file contains median values of RBC velocity measurements at capillary bifurcations in the somatosensory cortex of the mouse.</p> <p>Further notes on the simulation results:<br> - The realistic microvascular networks are from the mouse parietal cortex and have first been published in Blinder et al., 2013, Nature Neuroscience (<a href="https://doi.org/10.1038/nn.3426">https://doi.org/10.1038/nn.3426</a>).<br> - The numerical model to simulate blood flow in realistic microvascular networks has been described in Schmid et al., 2017, PLOS Computational Biology (<a href="https://doi.org/10.1371/journal.pcbi.1005392">https://doi.org/10.1371/journal.pcbi.1005392</a>).<br> - MVN1 and MVN2 stands for microvascular network 1 and 2, respectively.<br> - wRBCs and wpPs stands for 'with red blood cells' and 'with passive particles'. These terms describe two different numerical models: The wRBC-model accounts for all RBC related flow phenomena. The wpP neglects the phase-separation and the Fahraeus-Lindqvist effect, i.e. RBCs and flow are decoupled. Further details are available from Schmid et al. (2019, <a href="https://doi.org/10.1371/journal.pcbi.1007231">https://doi.org/10.1371/journal.pcbi.1007231</a>)</p> <p><strong>File format: </strong>pickle (Python)</p> <p><strong>Files 1 - 4 </strong>(Time-averaged simulation results):<br> Filenames: MVN1_wpPs.tar.bz2, MVN2_wpPs.tar.bz2, MVN1_wRBCs.tar.bz2, MVN2_wRBCs.tar.bz2</p> <p>Each compressed folder contains two files:<br> <br> edgesDict.pkl: dictionary with edge/vessel related data: </p> <ul> <li>flow: Flow rate in vessel [um^3/ms]</li> <li>length: Vessel length [um] (Tortuosity is considered)</li> <li>htt: Tube hematocrit in vessel [-]</li> <li>diameter: Effective vessel diameter [um]</li> <li>connectivity: Vertex indices, e.g. start and end vertex of the corresponding vessel</li> </ul> <p>verticesDict.pkl: dictionary with vertex/bifurcation related data:</p> <ul> <li>index: Index of the current vertex </li> <li>coords: Coordinates to describe the position of the vertex [um]</li> <li>pressure: Pressure at the vertex [mmHg]</li> </ul> <p> </p> <p><strong>File 5</strong> (in vivo RBC velocity measurements):<br> Filename: measurementDict.pkl</p> <p>keys:</p> <ul> <li>divergent_d1: divergent bifurcation, RBC velocity measurement in daughter vessel 1</li> <li>divergent_d2: divergent bifurcation, RBC velocity measurement in daughter vessel 2</li> <li>convergent_m1: convergent bifurcation, RBC velocity measurement in mother vessel 1</li> <li>convergent_m2: convergent bifurcation, RBC velocity measurement in mother vessel 2</li> </ul> <p><br> Data structure: list of list,<br> e.g. daughter vessel 1:<br> [[bif.1 - measure.1, bif.1 - measure.2, bif.1 - measure.3], [bif.2 - measure.1, bif.2 - measure.2, bif.2 - measure.3],...]<br> bif.: bifurcation, measure.: measurement.<br> The order of bifurcations is the same for 'divergent_d1' and 'divergent_d2' (and for 'convergent_m1' and 'convergent_m2'). </p> <p> </p>
Dataset of Paper "Novel procedure for the numerical simulation of solar water disinfection processes in flow reactors" (DOI: 10.1016/j.cej.2018.10.131)
<p>Datasets of Paper "Novel procedure for the numerical simulation of solar water disinfection processes in flow reactors".</p> <p>DOI: 10.1016/j.cej.2018.10.131</p> <p>Data of the velocity profiles at different distances from the inlet of a solar rainwater reactor.</p> <p>Data of the simulated radiation field inside of a solar rainwater reactor as a function of the location, date, time and CPC inclination.</p> <p>Data of the disinfection efficiency versus illumination time in a solar reactor under simulated and natural sunlight.</p>
FVLLMONTI Application examples: Single reconfigurable VNWFET TCAD simulation and Reference logic cell DTCO flow
<p>This data set presents two application examples collecting and highlighting some of the key components to the TCAD, compact modelling and DTCO approaches carried out as part of the FVLLMONTI project in relation to Deliverable D3.2.</p> <p>First we present an example that demonstrates the functionality of the U-shaped reconfigurable transistor, switching the device behaviour between NMOS and PMOS using the Program Gate and giving the transistor characteristics of those devices.</p> <p>Secondly, this data set gives an introduction into the FVLLMONTI DTCO approach. The provided simulation project shows a reference DTCO flow from layout to library characteristics for previously delivered physical logic cell designs. The DTCO flow provides insight into logic cell parasitics, netlist for 3rd party SPICE analysis, and KPI determination and characterization.</p> <p>Both simulation projects can be seen as template for similar setups employed to overcome the challenges and answer the detailed questions faced in investigating a newly developed semiconductor technology such as the FVLLMONTI stack.</p>
Impact of Grid Resolution on Wave-mean Flow Interactions with High Resolution Mars Global Climate Model Simulations
<p>This dataset contains NetCDF files necessary to replicate results from the 2024 paper "<em>Impact of Grid Resolution on Wave-mean Flow Interactions with High Resolution Mars Global Climate Model Simulations</em>"</p> <p>The dataset contains NetCDF files with 1 year of zonally-averaged NASA Ames Mars Global Climate Model (MGCM) fields with 5-sol binning for each of the simulations presented in the paper: </p> <ul> <li>a "low-resolution" simulation with no parameterization for gravity waves</li> <li>a "high-resolution" simulation with no parameterization for gravity waves</li> <li>a "low-resolution" simulation with parameterizations for orographic and non-orographic gravity waves</li> </ul> <p>Also included are:</p> <ul> <li>a file describing the coordinates for the MGCM's vertical grids used in the study </li> <li> atmospheric fields not provided in the other NetCDF files and necessary to replicate figures 3 and supplemental figure FS2 from the paper.</li> <li>a README.txt detailing the content of each file in the dataset</li> </ul>
Database from Large-Eddy Simulations of a Supersonic Jet Flow (Re= 1.6x10E6 , M=1.4) - Database 1 of 6
<p>Numerical Database from Large-Eddy Simulations of a Supersonic Jet Flow (Re= 1.6x10E6 , M=1.4) - Database 1 / 6<br>Authors: Diego F. Abreu, João Luiz F. Azevedo, Carlos Junqueira-Junior</p> <p>This database presents unsteady calculated data derived from large-eddy simulations (LES) of a supersonic jet flow utilizing the FLEXI solver (https://numericsresearchgroup.org/codes.html#codes_flexi). <br>The operational parameters for the jet flow include a Mach number of 1.4 and a Reynolds number of 1.58E6 referenced to the nozzle exit diameter, corresponding to a perfectly expanded supersonic condition. The pressure and temperature of the jet flow match those of the surrounding ambient conditions.</p> <p>The dataset originates from six numerical simulations employing various mesh resolutions and polynomial orders, along with different boundary conditions. These calculations were performed to investigate the impact of mesh resolution, polynomial order, and boundary conditions on LES of the supersonic jet flow in the absence of nozzle effects. The database encompasses a collection of probes and planes extracted from the 3-D domain as outlined in the attached README.md file. </p> <p>For further details regarding these probes and planes, as well as information on the numerical simulations, please refer to the supplemental-material-database.pdf file. <br>The database is divided into six parts. The present set of data is number one.</p> <p>This database is associated with the manuscript entitled "Assessment of Jet Inflow Condition on the Development of Supersonic Jet Flows". The numerical data presented herein were previously published in the work entitled "Accuracy Assessment of Discontinuous Galerkin Spectral Element Method in Simulating Supersonic Free Jets" (https://doi.org/10.1007/s40430-024-04788-z) and the Ph.D. Thesis "Study of Turbulent Supersonic Jet Flows and the Influence of Nozzle-Exit Boundary Conditions on the Jet Initial Development". </p>
Database from Large-Eddy Simulations of a Supersonic Jet Flow (Re= 1.6x10E6 , M=1.4) - Database 6 of 6
<p>Numerical Database from Large-Eddy Simulations of a Supersonic Jet Flow - Database 6 / 6<br>Authors: Diego F. Abreu, João Luiz F. Azevedo, Carlos Junqueira-Junior</p> <p>This database presents unsteady calculated data derived from large-eddy simulations (LES) of a supersonic jet flow utilizing the FLEXI solver (https://numericsresearchgroup.org/codes.html#codes_flexi). <br>The operational parameters for the jet flow include a Mach number of 1.4 and a Reynolds number of 1.58E6 referenced to the nozzle exit diameter, corresponding to a perfectly expanded supersonic condition. <br>The pressure and temperature of the jet flow match those of the surrounding ambient conditions.</p> <p>The dataset originates from six numerical simulations employing various mesh resolutions and polynomial orders, along with different boundary conditions. <br>These calculations were performed to investigate the impact of mesh resolution, polynomial order, and boundary conditions on LES of the supersonic jet flow in the absence of nozzle effects. <br>The database encompasses a collection of probes and planes extracted from the 3-D domain as outlined in the attached README.md file. <br>For further details regarding these probes and planes, as well as information on the numerical simulations, please refer to the supplemental-material-database.pdf file. <br>The database is divided into six parts. The present set of data is number six.</p> <p>This database is associated with the manuscript entitled "Assessment of Jet Inflow Condition on the Development of Supersonic Jet Flows". <br>The numerical data presented herein were previously published in the Ph.D. Thesis "Study of Turbulent Supersonic Jet flows and the Influence of Nozzle-Exit Boundary Conditions on the Jet Initial Development".</p>
Database from Large-Eddy Simulations of a Supersonic Jet Flow (Re= 1.6x10E6 , M=1.4) - Database 5 of 6
<p>Numerical Database from Large-Eddy Simulations of a Supersonic Jet Flow - Database 5 / 6 (Continuation of https://doi.org/10.5281/zenodo.13902381 database)<br>Authors: Diego F. Abreu, João Luiz F. Azevedo, Carlos Junqueira-Junior</p> <p>This database presents unsteady calculated data derived from large-eddy simulations (LES) of a supersonic jet flow utilizing the FLEXI solver (https://numericsresearchgroup.org/codes.html#codes_flexi). <br>The operational parameters for the jet flow include a Mach number of 1.4 and a Reynolds number of 1.58E6 referenced to the nozzle exit diameter, corresponding to a perfectly expanded supersonic condition. <br>The pressure and temperature of the jet flow match those of the surrounding ambient conditions.</p> <p>The dataset originates from six numerical simulations employing various mesh resolutions and polynomial orders, along with different boundary conditions. <br>These calculations were performed to investigate the impact of mesh resolution, polynomial order, and boundary conditions on LES of the supersonic jet flow in the absence of nozzle effects. <br>The database encompasses a collection of probes and planes extracted from the 3-D domain as outlined in the attached README.md file. <br>For further details regarding these probes and planes, as well as information on the numerical simulations, please refer to the supplemental-material-database.pdf file. <br>The database is divided into six parts. The present set of data is number five.</p> <p>This database is associated with the manuscript entitled "Assessment of Jet Inflow Condition on the Development of Supersonic Jet Flows". <br>The numerical data presented herein were previously published in the Ph.D. Thesis "Study of Turbulent Supersonic Jet flows and the Influence of Nozzle-Exit Boundary Conditions on the Jet Initial Development".</p>
Database from Large-Eddy Simulations of a Supersonic Jet Flow (Re= 1.6x10E6 , M=1.4) - Database 2 of 6
<p>Numerical Database from Large-Eddy Simulations of a Supersonic Jet Flow (Re= 1.6x10E6 , M=1.4) - Database 2 / 6 (Continuation of https://doi.org/10.5281/zenodo.13902381 database)<br>Authors: Diego F. Abreu, João Luiz F. Azevedo, Carlos Junqueira-Junior</p> <p>The operational parameters for the jet flow include a Mach number of 1.4 and a Reynolds number of 1.58E6 referenced to the nozzle exit diameter, corresponding to a perfectly expanded supersonic condition. The pressure and temperature of the jet flow match those of the surrounding ambient conditions.</p> <p>The dataset originates from six numerical simulations employing various mesh resolutions and polynomial orders, along with different boundary conditions. These calculations were performed to investigate the impact of mesh resolution, polynomial order, and boundary conditions on LES of the supersonic jet flow in the absence of nozzle effects. The database encompasses a collection of probes and planes extracted from the 3-D domain as outlined in the attached README.md file.</p> <p>For further details regarding these probes and planes, as well as information on the numerical simulations, please refer to the supplemental-material-database.pdf file.<br>The database is divided into six parts. The present set of data is number one.</p> <p>This database is associated with the manuscript entitled "Assessment of Jet Inflow Condition on the Development of Supersonic Jet Flows". The numerical data presented herein were previously published in the work entitled "Accuracy Assessment of Discontinuous Galerkin Spectral Element Method in Simulating Supersonic Free Jets" (https://doi.org/10.1007/s40430-024-04788-z) and the Ph.D. Thesis "Study of Turbulent Supersonic Jet Flows and the Influence of Nozzle-Exit Boundary Conditions on the Jet Initial Development".</p>
Database from Large-Eddy Simulations of a Supersonic Jet Flow (Re= 1.6x10E6 , M=1.4) - Database 4 of 6
<div> <p>Numerical Database from Large-Eddy Simulations of a Supersonic Jet Flow (Re= 1.6x10E6 , M=1.4) - Database 4 / 6 (Continuation of https://doi.org/10.5281/zenodo.13902381 database)<br>Authors: Diego F. Abreu, João Luiz F. Azevedo, Carlos Junqueira-Junior</p> <p>The operational parameters for the jet flow include a Mach number of 1.4 and a Reynolds number of 1.58E6 referenced to the nozzle exit diameter, corresponding to a perfectly expanded supersonic condition. The pressure and temperature of the jet flow match those of the surrounding ambient conditions.</p> <p>The dataset originates from six numerical simulations employing various mesh resolutions and polynomial orders, along with different boundary conditions. These calculations were performed to investigate the impact of mesh resolution, polynomial order, and boundary conditions on LES of the supersonic jet flow in the absence of nozzle effects. The database encompasses a collection of probes and planes extracted from the 3-D domain as outlined in the attached README.md file.</p> <p>For further details regarding these probes and planes, as well as information on the numerical simulations, please refer to the supplemental-material-database.pdf file.<br>The database is divided into six parts. The present set of data is number one.</p> <p>This database is associated with the manuscript entitled "Assessment of Jet Inflow Condition on the Development of Supersonic Jet Flows". The numerical data presented herein were previously published in the work entitled "Accuracy Assessment of Discontinuous Galerkin Spectral Element Method in Simulating Supersonic Free Jets" (https://doi.org/10.1007/s40430-024-04788-z) and the Ph.D. Thesis "Study of Turbulent Supersonic Jet Flows and the Influence of Nozzle-Exit Boundary Conditions on the Jet Initial Development".</p> <p> </p> </div>
Database from Large-Eddy Simulations of a Supersonic Jet Flow (Re= 1.6x10E6 , M=1.4) - Database 3 of 6
<p>Numerical Database from Large-Eddy Simulations of a Supersonic Jet Flow (Re= 1.6x10E6 , M=1.4) - Database 3 / 6 (Continuation of https://doi.org/10.5281/zenodo.13902381 database)<br>Authors: Diego F. Abreu, João Luiz F. Azevedo, Carlos Junqueira-Junior</p> <p>The operational parameters for the jet flow include a Mach number of 1.4 and a Reynolds number of 1.58E6 referenced to the nozzle exit diameter, corresponding to a perfectly expanded supersonic condition. The pressure and temperature of the jet flow match those of the surrounding ambient conditions.</p> <p>The dataset originates from six numerical simulations employing various mesh resolutions and polynomial orders, along with different boundary conditions. These calculations were performed to investigate the impact of mesh resolution, polynomial order, and boundary conditions on LES of the supersonic jet flow in the absence of nozzle effects. The database encompasses a collection of probes and planes extracted from the 3-D domain as outlined in the attached README.md file.</p> <p>For further details regarding these probes and planes, as well as information on the numerical simulations, please refer to the supplemental-material-database.pdf file.<br>The database is divided into six parts. The present set of data is number one.</p> <p>This database is associated with the manuscript entitled "Assessment of Jet Inflow Condition on the Development of Supersonic Jet Flows". The numerical data presented herein were previously published in the work entitled "Accuracy Assessment of Discontinuous Galerkin Spectral Element Method in Simulating Supersonic Free Jets" (https://doi.org/10.1007/s40430-024-04788-z) and the Ph.D. Thesis "Study of Turbulent Supersonic Jet Flows and the Influence of Nozzle-Exit Boundary Conditions on the Jet Initial Development".</p>
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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.