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328 results for “Simulation results”
Raw simulation results for Second-order homogenisation of crystal plasticity and martensitic transformation
<p>This dataset contains the raw simulation results used in the article entitled "Second-order homogenisation of crystal plasticity and martensitic transformation" (under review - 2023/05/15), by Igor A. Rodrigues Lopes, Miguel Vieira de Carvalho, João A. Marques da Silva, Rui P. Cardoso Coelho and Francisco M. Andrade Pires (INEGI and Faculty of Engineering of the University of Porto, Portugal).<br> These numerical results have been generated with the in-house finite element code LINKS.</p> <p>The dataset contains the datafiles, with information about the finite element mesh, plain text files with readable results, and vtu files that allow visualising the results in Paraview.</p>
Simulation results from WRF-CMAQ with enabling aerosol-radiation interactions in eastern China for January-April 2017
<p>Simulation results from WRF-CMAQ with enabling aerosol-radiation interactions in eastern China for January-April 2017 including meteorology and air quality:</p><p>YYYYMM_wrfout.zip:</p><p>Meteorological file including wrfout_YYYY-MM-DD_00_00_00 on each day for January-April 2017, which contains these variables:</p><p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB</p><p>YYYYMM_CCTM_ACONC.zip:</p><p>Air quality file including CCTM_ACONC_v3852_YYYYMMDD.nc on each day for January-April 2017, which contains these variables:</p><p>ASO4I, ANO3I, ANH4I, ANAI, ACLI, AECI, ALVPO1I, ASVPO1I, ASVPO2I, ALVOO1I, ALVOO2I, ASVOO1I, ASVOO2I, AOTHRI, ASO4J, ANO3J, ANH4J, ANAJ, ACLJ, AECJ, AOTHRJ, AFEJ, ASIJ, ATIJ, ACAJ, AMGJ, AMNJ, AALJ, AKJ, ALVPO1J, ASVPO1J, ASVPO2J, AXYL1J, AXYL2J, AXYL3J, ATOL1J, ATOL2J, AXYL2J, AXYL3J, ATOL1J, ABNZ3J, AISO1J, AISO2J, AISO3J, ATRP1J, ATRP2J, ASQTJ, AALK1J, AALK2J, APAH1J, APAH2J, APAH3J, AORGCJ, AOLGBJ, AOLGAJ, ALVOO1J, ALVOO2J, ASVOO1J, ASVOO2J, ASVOO3J, APCSOJ, ASOIL, ACORS, ACLK, ASO4K, ANO3K, ANH4K, O3, SO2, NO2, CO, and NH3.</p><p>YYYYMM_CCTM_APMDIAG.zip:</p><p>Air quality file including CCTM_APMDIAG_v3852_YYYYMMDD.nc on each day for January-April 2017, which contains these variables:</p><p>PM25AT, PM25AC and PM25CO.</p><p>YYYYMM_CCTM_PHOTDIAG1.zip:</p><p>Air quality file including CCTM_PHOTDIAG1_v3852_YYYYMMDD.nc on each day for January-April 2017, which contains these variables:</p><p>OZONE_COLUMN, NO2_COLUMN, CO_COLUMN, SO2_COLUMN, HCHO_COLUMN, TROPO_O3_COLUMN and AOD_W550_ANGST.</p>
model results from NHWAVE simulations of lobe-and-cleft instabilities at a river plume front
<p>The dataset contains the results from NHWAVE simulations of the lobe-and-cleft instabilities at a river plume front. The data format is .mat. The postprocessing scripts are included. </p>
Input and Output simulation data of the THOR GCM for the paper Dynamical and radiative effects resulting from the deep non-hydrostatic vs deep quasi-hydrostatic equations in the global circulation model THOR with an added non-grey radiative transfer scheme
<p>The input and ouput simulation data of the THOR GCM for Dynamical and radiative effects resulting from the deep non-hydrostatic vs deep quasi-hydrostatic equations in the global circulation model THOR with an added non-grey radiative transfer scheme</p> <p>Global circulation models (GCMs) play an important role in contemporary investigations of exoplanet atmospheres. Different GCMs evolve various sets of dynamical equations which can result in obtaining different atmospheric properties between models. In this study, we investigate the effect of different dynamical equation sets on the atmospheres of hot Jupiter exoplanets. We compare GCM simulations using the quasi-primitive dynamical equations (QHD) and the deep Navier-Stokes equations (NHD) in the GCM THOR. We utilise a two-stream non-grey "picket-fence" scheme to increase the realism of the radiative transfer scheme. We perform GCM simulations covering a wide parameter range grid of system parameters in the population of exoplanets. Our results show significant differences between simulations with the NHD and QHD equation sets at lower gravity, higher rotation rates or at higher irradiation temperatures. The parameter exploration shows the relevance of choosing dynamical equation sets dependent on system and planetary properties.Climate states of hot Jupiters seemed to be more diverse than previously thought. There are exceptions to prograde superrotation. Overall, our study shows the evolution of different climate states which arise just due to different selection of Navier-Stokes equations and approximations. We show the shortcomings of approximations in GCMs made for Earth, but used for non Earth-like planets.</p>
Tailoring magnetic hysteresis of Fe-Ni additive manufactured permalloy via multiphysics-multiscale simulations: Temperature-dependent parameters, thermodynamic database, results, and utilities
<p>This dataset contains temperature-dependent parameters and thermodynamic database, supplementary data and utilities of the publication "Tailoring magnetic hysteresis of additive manufactured Fe-Ni permalloy via multiphysics-multiscale simulations of process-property relationships" (<a href="http://doi.org/10.1038/s41524-023-01058-9">Yang et al., 2023</a>).</p> <p>We performed non-isothermal phase-field simulations of SLS process of the Fe<sub>21.5</sub>Ni<sub>78.5</sub> permalloy and subsequential mesoscopic thermo-elasto-plastic calculations and nanoscopic chemical order-disorder (<span>\(\gamma/\gamma'\)</span>) transition simulations as well as micromagnetic hysteresis calculations on nanostructures. Temperature-dependent parameters are employed. We then investigate the dependence of the fusion zone size, the residual stress and plastic strain, and the magnetic hysteresis of AM-produced Fe<sub>21.5</sub>Ni<sub>78.5 </sub>on beam power and scan speed.</p> <p>This dataset contains:</p> <ul> <li><em>feni_cac.tdb</em>: Thermodynamic database of the Fe-Ni binary system based on <a href="https://doi.org/10.1016/j.intermet.2010.02.026">Cacciamani et al., 2010</a></li> <li><em>average_values.csv</em>: Average quantities for creating the contours in Fig. 6a, 6b, 7a, 7b, 8a, and Supp. Fig. 10a, 10b.</li> <li><em>mesostructures.zip</em>: Containing resampled mesostructures from SLS single scan simulations (final timestep) with associated temperature, stress, and strain evolution. Nodal values are explained in Table 1. Naming pattern is <ul> <li>SLS-TEP__<power>-<scan_speed>__.e</li> </ul> </li> <li><em>parameters.zip</em>: Containing temperature-dependent parameters for performing SLS simulations and thermo-elasto-plastic calculations with fine (1K) temperature increments. The same temperature-dependent parameters with coarse temperature increments are already listed as Supp. Table 1, 2.</li> <li><em>sampled_point_data.zip</em>: Containing mechanical quantities on sampled points and corresponding results of nanoscopic <span>\(\gamma'\)</span> phase fraction (<span>\(\Psi_{\gamma'}\)</span>) and magnetic coercivity <span>\(H_\mathrm{c}\)</span>. Naming pattern is <ul> <li>mech__<power>-<scan_speed>__.csv</li> <li>Psi__<power>-<scan_speed>__.csv</li> <li>Hc__<power>-<scan_speed>__.csv</li> </ul> </li> <li><em>utilities.zip</em>: Containing Python utilities to perform calculations of free energy density and related thermodynamic quantities, extracting parameters from <em>feni_cac.tdb. </em><br><strong>Notice: </strong><a href="https://pycalphad.org/docs/latest/">pyCALPHAD</a> (ver 0.8.4) is requested for performing the Python utilities.</li> </ul> <p>Table 1. Nodal values in an exodus file Nodal value name Symbol Meaning Unit T <span>\(T\)</span> Normalized Temperature by <span>\(T_\mathrm{M}\)</span> - c <span>\(\rho\)</span> Substance order parameter - pb <span>\(\xi\)</span> Fusion zone indicator - eps (eps_11, eps_12, eps_13, eps_22, eps_23, eps_33) <span>\({\varepsilon}\)</span> Strain - epsp (epsp_11, epsp_12, epsp_13, epsp_22, epsp_23, epsp_33) <span>\({\varepsilon}_\mathrm{pl}\)</span> Plastic Strain - peeq <span>\(p_\mathrm{e}\)</span> Accumulated plastic strain - sigma (sigma_11, sigma_12, sigma_13, sigma_22, sigma_23, sigma_33) <span>\({\sigma}\)</span> Stress MPa vonmises <span>\(\sigma_\mathrm{e}\)</span> von Mises stress MPa u (u_X, u_Y, u_Z) <span>\(\mathbf{u}\)</span> Displacement μm</p> <p> </p> <p><strong>Notice</strong>: The raw transient outputs are not cured in this dataset due to the vast file size. Please contact the authors to acquire related files/utilities.</p>
CESM/CAM simulation results for Jo et al. (2023) in GMD
<p>The dataset in this repository was used for Jo et al. (2023): "A New Simplified Parameterization of Secondary Organic Aerosol in the Community Earth System Model Version 2 (CESM2; CAM6.3)" in Geoscientific Model Development. </p> <p><a href="https://doi.org/10.5194/gmd-16-3893-2023">https://doi.org/10.5194/gmd-16-3893-2023</a></p>
Model simulation data used in "The global impact of the transport sectors on the atmospheric aerosol and the resulting climate effects under the Shared Socioeconomic Pathways (SSPs)" (Righi et al., Earth Syst. Dynam., 2023)
<p>This dataset contains the output of the EMAC global model simulations analysed and discussed in Righi et al. (<i>Earth Syst. Dynam.</i>, 2023). For details see the README.md file.</p>
InTheMED WP6 Data Archive – Tympaki, Greece: Simulation Results
<p>This data archive includes the files “InTheMED_WP6_DS_ SimulatedGWLevelTimeSeriesGreece.mat” and “InTheMED_WP6_GDS_ MapsGreece.gdb” which contain the datasets that represent the results of the simulation runs of the Tympaki numerical groundwater model. More specifically, the timeseries of the groundwater level at the observation wells and the shapefiles that are necessary for the mapping of groundwater level and pumping rates at the optimization time-step.</p>
The supplementary animations, results and the codes of the green-beard simulation study
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Simulation results for ProSSE and datafile for case study
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Variability due to climate and chemistry in observations of oxygenated Earth-analogue exoplanets: Simulations and results
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Data for: Field data and simulation results of the Seoul Halloween crowd-crush
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SWAT+ simulation result used in "Smart renewable electricity portfolios in West Africa"
<p>Shapefiles and simulation results from SWAT+ used for the paper "Smart renewable electricity portfolios in West Africa" by Sterl et al., who used it to infer the interannual variability of river flow seasonality across West Africa.</p>
Control algorithm simulation results
<p>Torque vs. Speed maps of the 200kW pure SynRel power settings </p>
MOSTWAS models, TWAS summary statistics, and simulation results for Bhattacharya and Love, 2020
<p>This compressed folder contains three sub-folders that all pertain to models and results generated with Multi-Omic Strategies for Transcriptome-Wide Association Studies (MOSTWAS):</p> <ol> <li><em>MOSTWAS_Models</em> contains compressed folders for MOSTWAS models trains on TCGA breast cancer and ROS/MAP pre-frontal cortex multi-omic data.</li> <li><em>Simulations </em>contains Simulation_Results_MOSTWAS.xlsx that provides full simulation results outlined in Bhattacharya and Love, 2020 (paper accompanying MOSTWAS).</li> <li><em>TWAS_associations</em> contains four Excel files that provide MOSTWAS and local-only TWAS associations for breast cancer-specific survival (using iCOGs GWAS summary statistics), late-onset Alzheimer's disease risk (using IGAP GWAS summary statistics), and major depressive disorder risk (using PGC GWAS and UK Biobank GWAX summary statistics).</li> </ol>
Experimental and Simulation Results of "Ultrafast Response of Harmonic Modelocked THz Laser"
<p>This repository contains the experimental and simulation results of the article "Ultrafast Response of Harmonic Modelocked THz Laser" by Wang, F., Pistore, V., Riesch, M. <em>et al.</em>, published in <em>Light Sci Appl</em> <strong>9, </strong>51 (2020). https://doi.org/10.1038/s41377-020-0288-x</p> <p> </p>
Results of "Sensitivity of Greenland ice sheet projections to spatial resolution in higher-order simulations: the AWI contribution to ISMIP6-Greenland using ISSM"
<p>This archive provides ice sheet model output produced as part of the publication:</p> <p>Rückamp, M., Goelzer, H., and Humbert, A.: Sensitivity of Greenland ice sheet projections to spatial resolution in higher-order simulations: the AWI contribution to ISMIP6-Greenland using ISSM, The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-329, in review, 2020.</p> <p>About the data:<br> The archive contains 4 tar-files for the 4 different resolutions. Each tar-file contains Matlab files for the dfferent scenarios. An examplary file structure looks as follows:</p> <p>results =</p> <p> struct with fields</p> <p>mesh_description: {'x=x_EPSG3413(m)' 'y=y_EPSG3413(m)'}<br> inputs_description: {'friction coefficient k^2 (s/m)' 'bedrock (m)'}<br> data_description: {1x13 cell}<br> mesh: [1x1 struct]<br> inputs: [1x1 struct]<br> data: [1x87 struct]<br> model_description: {'output from ISMIP6 AWI-ISSM, simulation: G4000 ctrl_proj, correspondence Martin Rueckamp (AWI): marin.rueckamp@awi.de'}<br> data_citation: {'Rückamp, M., Goelzer, H., and Humbert, A.: Results of "Sensitivity of Greenland ice sheet projections to spatial resolution in higher-order simulations: the AWI contribution to ISMIP6-Greenland using ISSM", Zenodo, https://doi.org/10.5281/zenodo.3992605, 2020.'}<br> model_citation: {'Rückamp, M., Goelzer, H., and Humbert, A.: Sensitivity of Greenland ice sheet projections to spatial resolution in higher-order simulations: the AWI contribution to ISMIP6-Greenland using ISSM, The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-329, in review, 2020.'}</p> <p>The fields results.[mesh,input,data]_description contain header information. The field results.mesh contains [x,y]-coordinates of the grid. The field results.inputs contains time-independent quantities such as bedrock. The field results.data contains results of the transient simulations, such as ice thickness or surface velocity. The fields results.[model,data]_citation contain information about data citation.</p>
Limb work and joint work minimisation reveal an energetic benefit to the elbows-back, knees-forward limb design in parasagittal quadrupeds. Supplementary material including data, simulation code and simulation results
<p>Quadrupedal animal locomotion is energetically costly. We explore two forms of mechanical work that may be relevant in imposing these physiological demands. Limb work, due to the forces and velocities between the stance foot and the centre of mass, could theoretically be zero given vertical limb forces and horizontal centre of mass path. To prevent pitching, skewed vertical force profiles would then be required, with forelimb forces high in late stance and hindlimb forces high in early stance. By contrast, joint work – the positive mechanical work performed by the limb joints – would be reduced with forces directed through the hip or shoulder joints. Measured quadruped kinetics show features consistent with compromised reduction of both forms of work, suggesting some degree of, but not perfect, inter-joint energy transfer. The elbows-back, knees-forward design reduces the joint work demand of a low limb-work, skewed, vertical force profile. This geometry allows periods of high force to be supported when the distal segment is near vertical, imposing low moments about the elbow or knee, while the shoulder or hip avoids high joint power despite high moments because the proximal segment barely rotates – translation over this period is due to rotation of the distal segment.</p>
Input files and simulation results for reactive two-phase transport calculations in a waste package with OGS6-MP-LT-Drum
<p>The folders contain the original input and output files for reactive two-phase flow calculations with OpenGeoSys6-MP-LT-drum (doi:10.5281/zenodo.4060885), as well as the GEM-Selektor V3.3 project for look-up table generation, state<br> files for Paraview, R-script and jupyter notebook files used for post-processing the simulation output, which were used for creating the results in:</p> <p>Huang, Y., Shao, H., Wieland, E. <em>et al.</em> Two-phase transport in a cemented waste package considering spatio-temporal evolution of chemical conditions. <em>npj Mater Degrad</em> <strong>5, </strong>4 (2021). https://doi.org/10.1038/s41529-021-00150-z</p>
All simulation results, figures and code regarding the manuscript: Calibrating models of cancer invasion: parameter estimation using Approximate Bayesian Computation and gradient matching
<p>We present two different methods to estimate parameters within a partial differential equation (PDE) model of cancer invasion. The model describes the spatio-temporal evolution of three variables -- tumour cell density, extracellular matrix density and matrix degrading enzyme concentration -- in a one-dimensional tissue domain. The first method is a likelihood-free approach associated with Approximate Bayesian Computation (ABC); the second is a two-stage gradient matching method based on smoothing the data with a Generalized Additive Model (GAM) and matching gradients from the GAM to those from the model. Both methods performed well on simulated data. To increase realism, additionally we tested the gradient matching scheme with simulated measurement error and found that the ability to estimate some model parameters deteriorated rapidly as measurement error increased.</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.