Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
112
datasets available to search
ShareScore release 0.8.0
Dataset results
112 results for “fluid dynamics”
NsEllipse datasets from "Multi-scale rotation-equivariant graph neural networks for unsteady Eulerian fluid dynamics"
<p>Datasets with simulations of the incompressible flow around an elliptical cylinder as described by the incompressible Navier-Stokes equations.</p> <p>These simulations were used to train and test the MuS-GNN models in the paper:<br> "Multi-scale rotation-equivariant graph neural networks for<br> unsteady Eulerian fluid dynamics" (https://doi.org/10.1063/5.0097679)</p> <p>The datasets are:<br> - train/NsEllipse<br> - test/NsEllipseLowRe<br> - test/NsEllipseHighRe<br> - test/NsEllipseThin<br> - test/NsEllipseThick<br> - test/NsEllipseNarrow<br> - test/NsEllipseWide<br> - test/NsEllipseAoA</p> <p> </p> <p>To cite these datasets, use the following reference:</p> <p>Mario Lino, Stathi Fotiadis, Anil A. Bharath, and Chris Cantwell. "Multi-scale rotation-equivariant graph neural networks for unsteady Eulerian fluid dynamics". Physics of Fluids, 34 (2022).</p> <p>@article{lino2022multi,<br> author = {Lino, Mario and Fotiadis, Stathi and Bharath, Anil A. and Cantwell, Chris},<br> title = {{Multi-scale rotation-equivariant graph neural networks for unsteady Eulerian fluid dynamics}},<br> journal = {Physics of Fluids},<br> volume = {34},<br> year = {2022},<br> url = {https://doi.org/10.1063/5.0097679},<br> }<br> </p>
Dataset with the node discretisations employed for training advection models in "Multi-scale rotation-equivariant graph neural networks for unsteady Eulerian fluid dynamics"
<p>Dataset with the node discretisations employed for training advection models in "Multi-scale rotation-equivariant graph neural networks for unsteady Eulerian fluid dynamics" (https://doi.org/10.1063/5.0097679).</p> <p>The training code is available at https://github.com/mario-linov/graphs4cfd.</p>
Pore-scale fluid dynamics resolved in pressure fluctuations at the Darcy scale
<p>Pressure data from the 5 experiments described in Spurin et al. Pore-scale fluid dynamics resolved in pressure fluctuations at the Darcy scale. <em>GRL, 2023. </em></p> <p>There are 2 data sets from the pore-scale observations with either gas or oil injected. There are 3 data sets from the core-scale observations: 1 with oil injected, and 2 with gas injected. The 2 gas experiments were conducted in the same sample, just with the flow direction reversed. </p> <p>This upload also includes the code to perform the continuous wavelet transform on the pressure data. </p>
Wave Dynamics and Fluid Stresses in Vegetated and Unvegetated Coastal Lagoons in Virginia, 2010-2011
Wave, turbulence and wind measurements were performed within a Zostra marina seagrass (eelgrass) meadow in South Bay, Virginia, USA a coastal bay within the Virginia Coast Reserve where ongoing seagrass restoration efforts are being performed, and in adjacent areas without seagrass. These datasets were published in: Hansen J.C.R. and Reidenbach M.A., 2013, Seasonal growth and senescence of a Zostera marina seagrass meadow alters wave-dominated flow and sediment suspension within a coastal bay, Estuaries and Coasts, 36, 1099-1114.
Raw data for the manuscript under the title "Mitochondrial RNA granules are fluid condensates, positioned by membrane dynamics".
<p><strong>This is the data-repository</strong> to contain all relevant raw-data used and referred to in the manuscript entitled:<br> "Mitochondrial RNA granules are fluid condensates, positioned by membrane dynamics"<br> [manuscript under revision, and thus not citable as published article]</p> <p>The repository is structured analogous to the manuscript. Find a more detailed description in the README.</p>
Dataset of paper "Predicting the size of silver nanoparticles synthesised in flow reactors: Coupling population balance models with fluid dynamic simulations"
<p>Dataset of paper "Predicting the size of silver nanoparticles synthesised in flow reactors: Coupling population balance models with fluid dynamic simulations"</p>
Comparative analysis of patient-specific aortic dissections through computational fluid dynamics suggests increased likelihood of degeneration in partially thrombosed aorta
<p>Aortic dissection is a life-threatening cardiovascular disease associated with high rates of morbidity and mortality, especially in medically under-served communities. It compromises the hemodynamics of the arteries that originate from the aorta, and its outcomes include visceral ischemia and aortic rupture in the acute phase and aneurysmatic degeneration in the chronic phase. Understanding patients’ blood flow patterns is pivotal for non-invasive evidence-based treatment as they greatly influence both the disease onset and its outcome. In this paper, we combine diagnostic imaging techniques and computational fluid dynamics to analyze the flow patterns of three aorta dissections (fully perfused, partially thrombosed, and fully thrombosed), and compare them to a healthy aorta. Besides flow kinematics, we focus on time averaged wall shear stress and oscillatory shear index that are recognized risk factors for aneurysm and rupture. Our analysis shows that partially thrombosed dissection is the most prone to false lumen degeneration. In all dissections, the arteries connected to the false lumen are generally poorly supplied with blood. Further, both true and false lumens present higher turbulence levels than the healthy aorta, and critical stagnation points. Mesh sensitivity and a thorough comparison against literature data together support the methodology robustness.</p>
Data associated to the article "Effects of fluoride salt addition to the physico-chemical properties of the MgCl2-NaCl-KCl heat transfer fluid : a molecular dynamics study"
<p>Contains input file and data used to generate the figures of the article:</p> <p>Effects of fluoride salt addition to the physico-chemical properties of the MgCl<sub>2</sub>-NaCl-KCl heat transfer fluid : a molecular dynamics study</p> <p>Weiguang Zhou, Yanping Zhang, Mathieu Salanne</p> <p>https://chemrxiv.org/engage/chemrxiv/article-details/618e903a2bf8a950c7d98e5d</p> <p>The files <em>data.inpt</em> and <em>runtime.inpt </em>are used to simulate the system using the software MetalWalls</p> <p>The files <em>MgNaKCl.txt, MgNaKClF01.txt, MgNaKClF05.txt, MgNaKClF10.txt, MgNaKClF20.txt</em> contain the computed densities, viscosities and thermal conductivities at various temperatures for several compositions (provided in the header of the files)</p>
SeisSol input files for the dynamic rupture scenarios based on the 2004 Sumatra-Andaman earthquake published in Madden et al. (2022) "The state of pore fluid pressure and 3D megathrust earthquake dynamics" JGR-Solid Earth
<p>This dataset contains the input files of the dynamic rupture scenarios from Madden, E. H., T. Ulrich and A.-A. Gabriel (2022), The State of Pore Fluid Pressure and 3-D Megathrust Earthquake Dynamics, Journal of Geophysical Research-Solid Earth, <a href="https://doi.org/10.1029/2021JB023382">https://doi.org/10.1029/2021JB023382</a>. (Earlier preprint available at: <a href="https://doi.org/10.1002/essoar.10508297.1">https://doi.org/10.1002/essoar.10508297.2</a>)</p> <p><strong>easi/yaml parameter files for the 6 scenarios studied: </strong><br> PAR_Sumatra_scen1new_gen.par, PAR_Sumatra_scen2new_gen.par, PAR_Sumatra_scen3new_gen.par, PAR_Sumatra_scen4new_gen.par, PAR_Sumatra_scen5new_gen.par, PAR_Sumatra_scen6new_gen.par</p> <p><strong>easi/yaml files setting initial on-fault friction, stress and pore fluid pressure conditions for the 6 scenarios studied: </strong>iniStress_Sumatra_scen1new.yaml, iniStress_Sumatra_scen2new.yaml, iniStress_Sumatra_scen3new.yaml, iniStress_Sumatra_scen4new.yaml, iniStress_Sumatra_scen5new.yaml, iniStress_Sumatra_scen6new.yaml<br> <br> <strong>easi/yaml file describing the rock elastic properties in all 6 scenarios:</strong> <br> matprops_Sumatra_2019_LVZ.yaml<br> <br> <strong>mesh file:</strong> <br> topo4_splays_fix9-14.1e6-28m.dtc1-v2-suma</p> <p> </p>
Data from: Computational fluid dynamics confirms drag reduction associated with trilobite queuing behaviour
<p>Queuing behaviour has been documented in marine arthropods from Cambrian to modern oceans. One possible explanation of this behaviour is drag reduction, with trilobites in the following positions hypothesized to produce less drag than those leading. In this study, we evaluate the hydrodynamics of queuing behaviour in the Devonian trilobite Trimerocephalus chopini using computational fluid mechanics. Our results show that the drag forces of the trilobites following in the queue were substantially lower than those produced by the leader (75.1% lower at 2 cm s-1). Drag reduction is positively correlated with the movement speed of the trilobites, but decreases with increasing distance from the leader. Our results support the hypothesis that the queuing behaviour of trilobites was an adaptation for reducing hydrodynamic drag. This drag reduction effect compensated for the energy cost of movement, which would have been particularly advantageous during migration.</p>
Dataset for Journal of Applied Physics 130, 124502 (2021) - Force microscopy cantilevers locally heated in a fluid: temperature fields and effects on the dynamics
<p><strong>"Fig7.fig"</strong>: Matlab figures including all the measured and treated data used to plot figure 7 of the article.</p> <p><strong>"Fig7_data.mat "</strong>: Matlab files containing the data to plot figure 7 of the article.</p> <p><strong>"Fig7_plot.m "</strong>: Matlab scripts to plot the data of the Matlab files "Fig7_data.mat"</p> <p><strong>"Fig10.fig"</strong>: Matlab figures including all the measured and treated data used to plot figure 10 of the article.</p> <p><strong>"Fig13.fig"</strong>: Matlab figures including all the measured and treated data used to plot figure 13 (in the appendix) of the article.</p> <p> </p>
Dataset for "Does fluid structure encode predictions of glassy dynamics?"
<p>This folder contains data in support of "Does fluid structure encode predictions of glassy dynamics?", T. M. Obadiya and D. M. Sussman, arXiv preprint arXiv:2211.00604, (2022). It has three subfolders (described below); all data has been stored in Python's pickle format using protocol version 4, with the pickled files structured as dictionaries.</p> <p>## "Trajectories/" folder</p> <p>Each file in this folder is the raw saved output of a molecular dynamics simulation of an 80:20 Kob-Andersen mixture. To generate the trajectories of particles in this mixture, we first equilibrated a system with random initial conditions for 5000 tau at a temperature of T=0.45. We used the final configuration of this as an initial seed for our other simulations: a snapshot was loaded as the initial configuration for our other simulations, each of which was allowed to equilibrate for 1000 tau at its target temperature. The simulations were done in an NVT ensemble with the coupling constant of the thermostat set to 10 tau. The simulations were evolved using a timestep of dt = 0.001 tau, with frames saved every 1 tau.</p> <p>Each file name contains the temperature at which the simulation was run, and all simulations are of a set of N=4096 particles. The pickle dictionary for each file contains three elements.<br> "Box_size" contains an array of three elements describing the cubic box simulation box's size along the x, y, and z axes.<br> "Particle types" has a list of 4096 integers with 0 corresponding to a particle of type A and 1 corresponding to a particle of type B.<br> "Positions" contains the particle positions for every frame in the saved trajectory.</p> <p>## "Training_data_V1/" folder</p> <p>This folder contains the training data for five training temperatures used in the above paper. The paper considered two different training sets (defined by using either phop or cumulative squared displacement as the dynamical label), and the training sets corresponding to this choice of dynamical label are in the corresponding subfolders.</p> <p>Within each subfolder, the file name indicates the temperature at which the data were obtained. The pickle dictionary for each file contains two elements.<br> "X_train_rawdata" for every particle in the training set, this contains a list of 100 local structural features (corresponding to the AA and AB local radial distribution functions described in the paper above -- all particles in the training set are particles of type A); the "rawdata" part of the name indicates that these features have not been standardized.<br> "Y_train" is the corresponding dynamical label, with 1 indicating a large value of dynamical label and a -1 indicating a small value of the dynamical label.</p> <p>## "Training_data_V2/" folder</p> <p>This folder contains similar training data for the same five training temperatures, but does not make any assumptions about how to define the local structural features. The pickle dictionaries have the same names as in the Training_data_V1, and the "Y_train" element has the same structure.</p> <p>Here, though, "X_train_rawdata" for each element contains a list of 4-vectors that correspond to the positions of all particles within 5 sigma of the particle whose dynamical label is being considered. The first 3 elements of each 4-vector give the relative separation between the target particle and its neighboring particle, and the 4th element is the particle type of the neighboring particle (0 for particles of type A, and 1 for particles of type B).<br> </p>
Merging computational fluid dynamics and machine learning to reveal animal migration strategies
Open the record for dataset details and reuse information.
Data from: Computational fluid dynamics confirms drag reduction associated with trilobite queuing behaviour
Open the record for dataset details and reuse information.
Data from: Morphology, performance and fluid dynamics of the crayfish escape response
<p>Sexual selection can result in an exaggerated morphology that constrains locomotor performance. We studied the relationship between morphology and the tail-flip escape response in male and female rusty crayfish (<em>Faxonius rusticus</em>), a species in which males have enlarged claws (chelae). We found that females had wider abdomens and longer uropods (terminal appendage of the tail fan) than males, while males possessed deeper abdomens and larger chelae, relative to total length. Chelae size was negatively associated with escape velocity, whereas longer abdomens and uropods were positively associated with escape velocity. We found no sex-specific differences in maximum force generated during the tail flip, but uropod length was strongly, positively correlated with tail-flip force in males. Particle image velocimetry (PIV) revealed that the formation of a vortex, rather than the expulsion of fluid between two closing body surfaces, generates propulsion in rusty crayfish. PIV also revealed that the pleopods (ventral abdominal appendages) contribute to the momentum generated by the tail. To our knowledge, this is the first confirmation of vortex formation in a decapod crustacean.</p>
Effect of space diffuser on flow characteristics of a centrifugal pump by computational fluid dynamic analysis
<p><span>Achieving an optimal configuration of the diffuser is indispensable for high pump performances. In this work, a numerical study on diffuser configuration is conducted for a high pump performance using a computational fluid dynamics code, and the effects of the wrap angle and the relative position of the diffuser vane to the impeller on pump performances are included. The results indicate that the modified diffuser with a suitable wrap angle may improve the pump hydraulic efficiency and the head by approximately 4% and 8%, respectively, while a suitable position of the diffuser vane can enhance the pump head by more than 4%. Meanwhile, the pressure recovery coefficient and the local Euler head of the diffuser are adopted to evaluate the diffuser performance. For a high pump performance, the local Euler head of the diffuser has a peak value at the leading edge with the change rate of zero along the meridian streamline, meaning that no blade loading at the leading edge of the diffuser guarantees a better match between the impeller and the diffuser.</span></p>
Simulation results: effects of Chiari type 1 malformation on cerebrospinal fluid dynamics during arterial pulsations and coughing
<p>The folder contains the simulation results corresponding to the computational fluid dynamics study: Effects of Chiari type 1 malformation on cerebrospinal fluid dynamics during arterial pulsations and coughing</p> <p>Data is organized in the following way with files in .csv and .xlsx format</p> <ul> <li>Cropped model: <ul> <li>output_*: flow time in seconds, pressure in the fourth ventricle (Pv), outflow in m³/s or kg/s, and pressure at plane in spinal SAS (Psas) for physical herniations and herniations created by porous zones</li> </ul> </li> <li>Full model <ul> <li>arterial_pulsations: data with all boundary conditions (arterial) except from cough</li> <li>arterial_pulsations_and_cough: data with all boundary conditions (arterial) including cough</li> <li>file content: <ul> <li>*_boundary_data: time step number, number of coupling iterations necessary per time step, flow time (s), pressure (P) and flow (Q) at outlets with interstitium (1), spinal (2), lymphatic (3) and arachnoid villi (4), first element of Jacobian (J11), flow residual, value of perturbation (dP) in Pa, converged?: 1 when converged, 0 when not, perturbation parameter, number of times the perturbation value needed to be reduced.</li> <li>*_flow: flow time in seconds, volumetric flow through aqueduct, and spinal SAS</li> <li>*_pressure_data: flow time in seconds, relative pressure compared to interstitium outlet at the fourth ventricle (v4), the spinal SAS (sas) and the lateral ventricle (lv)</li> </ul> </li> </ul> </li> </ul>
Videos of dynamic rupture in models of the 2004 Sumatra-Andaman earthquake published in Madden et al. (2022) "The state of pore fluid pressure and 3D megathrust earthquake dynamics" JGR-Solid Earth
<p>Videos of dynamic rupture from models based on the 2004 Sumatra-Andaman earthquake presented in Madden, E. H., T. Ulrich, A.-A. Gabriel (2022). The state of pore fluid pressure and 3D megathrust earthquake dynamics, Journal of Geophysical Research - Solid Earth, <a href="https://doi.org/10.1029/2021JB023382">https://doi.org/10.1029/2021JB023382</a>. (Previous preprint available at: <a href="https://doi.org/10.1002/essoar.10508297.1">https://doi.org/10.1002/essoar.10508297.2</a>.)</p> <p> </p>
Seismogenic process of fluid injection revealed by in situ dynamic CT scanning
<p>In the process of unconventional energy exploitation, large volumes of fluid are injected into low permeability reservoirs for hydraulic transformation to generate a fracture network conducive to fluid migration. Unfortunately, extensive fluid injection can induce earthquakes, endangering human lives and causing serious economic losses. Understanding the seismogenic process of fluid injection within a reservoir helps to minimize the induced earthquakes. To better monitor the deformation changes in reservoirs, we conducted in situ dynamic X-ray computed tomography (CT) during a series of experiments lasting 3 minutes for real-time identification of the location and geometry of hydraulic fractures and found that the seismogenic process of fluid injection with a wide range of frequencies is triggered by water–rock interactions.</p> <p>The data we uploaded can be divided into two main parts. The first part is the confining, axial and water injection pressures recorded during the hydraulic fracturing experiment. The second part is the CT scans of the rock sample during the hydraulic fracturing experiment.</p>
Improvements in airflow characteristics and effect on the NOSE score after septoturbinoplasty: A computational fluid dynamics analysis
<p><span>Septoturbinoplasty is a surgical procedure that can improve nasal congestion symptoms in patients with nasal septal deviation and inferior turbinate hypertrophy. However, it is unclear which physical domains of nasal airflow after septoturbinoplasty are related to symptomatic improvement. This work employs computational fluid dynamics modeling to identify the physical variables and domains associated with symptomatic improvement. Sixteen numerical models were generated using eight patients' pre- and postoperative computed tomography scans. Changes in unilateral nasal resistance, surface heat flux, relative humidity, and air temperature and their correlations with improvement in the </span><span>Nasal Obstruction Symptom Evaluation (NOSE) score were analyzed. The NOSE score significantly improved after septoturbinoplasty, from 14.4 ± 3.6 to 4.0 ± 4.2 (p < 0.001). The surgery not only increased the airflow partition </span><span>on the more obstructed side (MOS) from 31.6 ± 9.6 to 41.9 ± 4.7% (p = 0.043), but also reduced the unilateral nasal resistance in the MOS from 0.200 ± 0.095 to 0.066 ± 0.055 Pa/(mL</span><span>×</span><span>s) (p = 0.004). Improvement in the NOSE score correlated significantly with the reduction in unilateral nasal resistance in the preoperative MOS (<em>r</em>=0.81). Also, improvement in the NOSE score correlated better with the increase in surface heat flux in the preoperative MOS region from the nasal valve to the choanae (<em>r</em>=0.87) than in the vestibule area (<em>r</em>=0.63). Therefore, </span><span>unilateral nasal resistance and mucous cooling in the preoperative MOS can explain the perceived improvement in symptoms after septoturbinoplasty. Moreover, the physical domain between the nasal valve and the choanae might be more relevant to patient-reported patency than the vestibule area. </span></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.