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161 results for “Numerical Simulation”
The dataset of the manuscript "Numerical study of the initial condition and emission on simulating PM2.5 concentrations in Comprehensive Air Quality Model with extensions version 6.1 (CAMx v6.1): Taking Xi'an as example"
<ul> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/bcfile.rar?versionId=4909d094-5877-408e-bd4f-0c969c54e585">bcfile.rar</a>: the clean initial and boundary condition files.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/Emis_forNov.rar?versionId=0a1e8b66-5157-4819-8c03-20fb7797d8ef">Emis_forNov.rar</a> and <a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/Emis_forDec.rar?versionId=d4db00f1-ec1b-4096-973e-6a87133e4eac">Emis_forDec.rar</a>: the emission files in November and December 2016.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/tuvfile.rar?versionId=5dcf0977-e416-466e-9089-bbf0726c788d">tuvfile.rar</a> and <a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/o3mapfile.rar?versionId=9c25cae9-f00e-4ad3-b4dc-7a721f7f44d7">o3mapfile.rar</a>: the photolysis files.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/camx.cp1.rar?versionId=09ded31b-4c42-4e40-a21c-0f18877e9e41">camx.cp[1-5].rar</a>: the results of sensitivity experiments for using clean initial condition files.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/camx.r1120p1.rar?versionId=45d6e209-8e66-43ed-bc0b-dc8af5521352">camx.r1120p[1-3].rar</a>: the results of sensitivity experiments for R1120.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/camx.r1124.rar?versionId=c138e436-0416-4701-948d-ce761cf6c5cf">camx.r1124.rar</a>: the results of sensitivity experiments for R1124.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/contnuous_B12.rar?versionId=34485c43-77ac-4001-8a6d-a57b7ff821e3">contnuous_B12.rar</a>: the results of sensitivity experiments for CT12.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/contnuous_B24.rar?versionId=0f325a61-f19c-4bac-b8b4-7e229c332bf9">contnuous_B24.rar</a>: the results of sensitivity experiments for CT24.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/scripts.zip?versionId=b030444c-51a5-4673-b9d1-7e80ec42a3b9">scripts.zip</a>: all scripts covering every data processing action for all the results reported in the paper.</li> <li><a href="https://zenodo.org/api/files/cabf59e1-a955-4190-a83c-48d82efea4e6/data.zip?versionId=52917a53-fca7-4a72-ba2f-a2ce7593adc4">data.zip</a>: final data tables used to plot figures and tables.</li> </ul>
Experimental and Simulation Results of "3D Printed Biomodels for Flow Visualization in Stenotic Vessels: An Experimental and Numerical Study" - version 2
<p>This repository contains the experimental and simulation results of the article "3D Printed Biomodels for Flow Visualization in Stenotic Vessels: An Experimental and Numerical Study" by Carvalho, V., Rodrigues, N., Ribeiro, R., Costa, P., Lima, R., Teixeira, S., published in <em>Micromachines</em> <strong>11, 6</strong> (2020). https://doi.org/10.3390/mi11060549</p>
Numerical Fire Spread Simulation Based on Material Pyrolysis - An Application to the CHRISTIFIRE Phase 1 Horizontal Cable Tray Tests - Data Set
<p>This data set is a supplementary resource for the article "<a href="http://www.mdpi.com/2571-6255/3/3/33">Numerical Fire Spread Simulation Based on Material Pyrolysis - An Application to the CHRISTIFIRE Phase 1 Horizontal Cable Tray Tests</a>", published by the peer-reviewed open access journal <a href="https://www.mdpi.com/journal/fire">Fire</a>. It is part of the "<a href="https://www.researchgate.net/project/Fire-Propagation-in-Cable-Tray-Installations">Fire Propagation in Cable Tray Installations</a>" project. The provided data is only a summary of the full data produced for the article, due to its size.</p> <p>This article was previously submitted to the Fire Safety Journal and got eventually rejected.</p> <p>The information is structured into multiple *.rar archieves, which mimic the sub-directory structure created for the work. To be able to run the analysis scripts without much tweaking, extract all archieves into the same directory, with each archieve being a sub-directory in it.</p> <p>The data set is comprised of:</p> <ul> <li>The PROPTI and FDS input files used for the inverse modelling process (IMP) -- the 13* archieves.</li> <li>Full FDS simulation data of the mirco-combustion calorimeter (MCC) simulations of the best parameter sets per generation of the IMP runs, for jacket and insulator materials.</li> <li>Full FDS simulation data of the Cone Calorimeter simulations of the best parameter sets per generation of the IMP runs, for all three (25 kW/m², 50 kW/m², 75 kW/m²) incident heat flux conditions.</li> <li>FDS input files for the MT3 simulations, but full data only for the best parameter sets per IMP run (see below).</li> <li>Jupyter notebooks used for the analysis of the simulation responses including the scripts and plots generated for, and used in, the paper (RunReports).</li> <li>A general information directory, containing the FDS input file templates, experimental data used as target and Python scripts containing helper functions.</li> <li>Videos of a qualitative comparison of the SmokeView animation of the best parameter set in a cable tray simulation against a video from the experiment and an animation of the GAUGE_HEAT_FLUX development for the same simulation over the course of the simulation.</li> </ul> <p>Due to the size of the MT3 simulation data, only the FDS input files for the best parameter sets per generation are uploaded. Complete FDS simulation data is only provieded for the best perameter set of each IMP run, these are :</p> <p>IMP run, best rep.<br> --------------------------------<br> imp_13b, 110751<br> imp_13c, 121106<br> imp_13d, 137738<br> imp_13e, 97493<br> imp_13f, 91988<br> imp_13g, 86988<br> imp_13h, 17480<br> imp_13b_1, 19033<br> imp_13b_2, 25043<br> imp_13b_3b, 24149<br> imp_13b_4, 29666<br> imp_13h_1, 10685<br> imp_13h_2, 10024<br> imp_13h_3, 10109<br> imp_13i, 13253</p> <p> </p> <p>Note: The individual runs of the IMP are named differently as compared to the labeling used in the paper, as described below:</p> <p>IMP run, label in paper<br> --------------------------------</p> <p>imp_13b, T<sub>b</sub><br> imp_13c, T<sub>a</sub><br> imp_13d, T<sub>c</sub><br> imp_13e, T<sub>a,b,c</sub><br> imp_13f, T<sub>b,c</sub><br> imp_13g, T<sub>a,c</sub><br> imp_13h, T<sub>a,b,c</sub>L<sub>A,L1,HC</sub><br> imp_13b_1, T<sub>b</sub>L<sub>1</sub><br> imp_13b_2, T<sub>b</sub>P<sub>L1</sub><br> imp_13b_3b, T<sub>b</sub>P<sub>L1</sub>L<sub>1</sub><br> imp_13b_4, T<sub>b</sub>P<sub>L2,HT</sub><br> imp_13h_1, T<sub>a,b,c</sub>P<sub>A,L1,HC</sub>L<sub>1</sub><br> imp_13h_2, T<sub>a,b,c</sub>P<sub>A,L1,HC</sub>L<sub>2</sub><br> imp_13h_3, T<sub>a,b,c</sub>P<sub>A,L1,HC</sub>L<sub>3</sub><br> imp_13i, T<sub>b</sub>P<sub>A,L1,HC</sub></p> <p> </p> <p>Version 2 changes:</p> <p>Added pre-print.</p> <p> </p> <p>Version 3 changes:</p> <p>Added new files that where produced during the revision process, after the original manuscript got rejected by the Fire Safety Journal. This revision corresponds to the intitial manuscript that was submitted to the journal <a href="https://www.mdpi.com/journal/fire">Fire</a>. The respective Zip archieves are labeled with a "_Revision01".</p>
Data for paper "Effects of inflow conditions on plunge points and vertical profiles of turbidity currents on sloping flume based on 3D numerical simulation"
<p>This set of xlsx files, metadata of model results and Matlab code accompanies the manuscript "Effects of inflow conditions on plunge points and vertical profiles of turbidity currents on sloping flume based on 3D numerical simulation" by Ruoyin Zhang, Baosheng Wu, and Bangwen Zhang. This is the first release of the data.</p>
Experimental Data for "Seismic wave attenuation and dispersion due to partial fluid saturation: Direct measurements and numerical simulations based on X-Ray CT"
<p>Experimental Data from a Berea sandstone sample. Includes X-ray CT scans and mechanical response of sample.</p> <p>Abstract</p> <p>Quantitatively assessing seismic attenuation caused by fluid pressure diffusion (FPD) in partially saturated rocks is challenging because of its sensitivity to the spatial fluid distribution. To address this challenge we performed depressurisation experiments to induce the exsolution of carbon dioxide from water in a Berea sandstone sample. In a first set of experiments we used medical X-ray computed tomography (CT) to characterise the fluid distribution. At an equilibrium pressure of ~1 MPa and applying a fluid pressure decline rate of ~0.6 MPa per minute, we allowed a change in saturation of less than 1 %. The gas was heterogeneously distributed along the length of the sample, with most of the gas exsolving near the sample outlet. In a second set of experiments, at the same pressure and temperature, following a very similar exsolution protocol, we measured the frequency dependent attenuation and modulus dispersion between 0.1 and 1000 Hz using the forced oscillation method. We observed significant attenuation and dispersion in the extensional and bulk deformation modes, however not in the shear mode. Lastly, we use the fluid distribution derived from the X-ray CT as an input for numerical simulations of FPD to compute the attenuation and modulus dispersion. The numerical solutions are in close agreement with the attenuation and modulus dispersion measured in the laboratory. Our methodology allows for accurately relating attenuation and dispersion to the fluid distribution, which can be applied to improving the seismic monitoring of the subsurface.</p>
Data from: Combining micro-volume isotope analysis and numerical simulation to reproduce fish migration history
1. Tracking the movement of migratory fish is of great importance for efficient conservation, although this has been technically difficult to achieve in small fish to which artificial tags cannot be attached. 2. We show that migration history can be reproduced by combining high-resolution otolith stable oxygen isotope ratio (δ18O) analysis and numerical simulation. 3. High-precision micro-milling and micro-volume carbonate analysing systems had the remarkable capability of extracting the otolith δ18O profiles with 10–30 days resolution. Furthermore, reasonable movements were reproduced by searching the routes consistent with the otolith δ18O profile, using an individual-based model with random swimming behaviour. 4. This method will be a valuable alternative to tagging and electronic loggers for revealing migration routes in early life stages, thereby providing crucial information to understand population structures and the environmental cause of recruitment variabilities, and to validate and improve fish movement models.
Data of paper "Grid ,Hydrodynamic boundary and Uncertainty analysis of 2D-SWEs in the context of digital twins: Taking numerical simulation of river networksas an example"
<p>论文数据 “数字孪生背景下2D-SWEs的网格、水动力边界和不确定性分析:以河流网络数值模拟为例”</p>
Master's Thesis: 2D Numerical Simulations of Shallow Crustal Magma Bodies
<p>This collection of videos showcases a series of simulations conducted during my master’s thesis. The videos illustrate the evolution of temperature, water, and silica parameter fields, highlighting the internal dynamics within the systems. Key processes captured include whole-system convection, system overturn, plume formation, drip formation, and layering at the base of the systems. Additionally, two of the videos present Harker plots of the major oxides: one from the closed-system reference scenario, which contained a single magma composition, and the other from the open-system simulation, which included two magma compositions.</p>
Simulation results for "Deciphering clues regarding magma composition encoded in quartz-hosted embayments and melt inclusions through direct numerical simulations"
Open the record for dataset details and reuse information.
Dataset for "Observation and Numerical Simulation of Cold Ions Energized by EMIC Waves"
<p>* Reduced datasets for figures in the manuscript.</p>
Dataset and visualization of numerical simulations of decaying acoustic turbulence in three dimensions
<p>This dataset contains the time series and spectrum data for the 1000^3 resolution simulations featured in the paper: <em>Primordial acoustic turbulence: three-dimensional simulations and gravitational wave predictions</em> by Jani Dahl, Mark Hindmarsh, Kari Rummukainen, and David Weir. Also included are the various output files produced by the simulation code, the run files that can be used to reproduce the runs, and plots of the time series quantities, fluid snapshots, and movies of the longitudinal and transverse energy spectra.</p>
Consistent ground surface temperature records for the CMA stations over China for 1956–2022 via numerical simulation
<p>The ground surface represents the land-atmosphere interface and plays a crucial role in exchanging energy, matter, and biochemical fluxes. The ground surface temperature (T<sub>s</sub>) is hence widely investigated as an indicator to understand the thermal state of soil in a warming world. However, regular and continuous T<sub>s</sub> measurements are rare worldwide, and the early T<sub>s</sub> records were derived from snow surface measurements and are not comparable with the measurements of the modern automatic systems. In this dataset, we reconstructed the T<sub>s</sub> records of the China Meteorological Administration (CMA) for 1956–2022 by numerical simulation.</p>
Numerical results from DEM simulations
<p>The DEM code, DEPTH (https://www.jamstec.go.jp/namr/project06.html), was used to simulate the compressive behavior of hierarchical granular piles. The "zenodo_SA24.zip" file contains six folders:</p> <ol> <li>hierarchical_16 <ul> <li>F_wall_1e4_ave.txt (Fig. 19)</li> <li>fig_P_phi_16.pdf</li> </ul> </li> <li>hierarchical_32 <ul> <li>contact_angle_32.dat (Fig. 12)</li> <li>coordination_distance_32.dat (Figs. 9 and 10)</li> <li>distance_32_step_xxxx.dat (Fig. 11)</li> <li>energy_velocity_32.dat (Fig. 13(a))</li> <li>F_wall_1e4_ave.txt (Figs. 7 and 17(a))</li> <li>POV_32_stepxxxx_y.dat (Fig. 2)</li> <li>POV_32_stepxxxx_LR.png</li> </ul> </li> <li>hierarchical_64 <ul> <li>coordination_distance_64.dat (Figs. 9 and 10)</li> <li>distance_64_step_xxxx.dat</li> <li>energy_velocity_64.dat (Fig. 13(b))</li> <li>F_wall_1e4_ave.txt (Figs. 8 and 17(b))</li> <li>POV_64_stepxxxx_y.dat (Fig. S2)</li> </ul> </li> <li>single_16 <ul> <li>F_wall_1e4_single_casex.txt (Fig. 18)</li> </ul> </li> <li>single_32 <ul> <li>F_wall_1e4_single_casex.txt (Fig. 16(a))</li> </ul> </li> <li>single_64 <ul> <li>F_wall_1e4_single_casex.txt (Figs. 15(a) and 16(b))</li> <li>pair_integral_case1.txt (Fig. 15(b))</li> </ul> </li> </ol>
Numerical Electrostatic Simulations Output
<p>A .zip file containing the following:</p> <p>Simulation outputs saved as Matlab .mat files.</p> <p>Matlab .m scripts to make figures from each of the .mat files.</p>
Data for Numerical Simulation of Tornado-like Vortices Induced by Small-Scale Cyclostrophic Wind Perturbations
Open the record for dataset details and reuse information.
Numerical simulation "Numerical simulation of atmospheric Lamb waves generated by the 2022 Hunga-Tonga volcanic eruption"
<p>Numerical simulation results for the atmospheric Lamb waves generated by the Hunga-Tonga volcano explosion on January 15th 2022.</p>
Numerical data for dynamic rupture simulations of the 2016 Kumamoto earthquake
<p>Numerical data used to generate Figures in the manuscript entitled "The origin of large, long-period near-fault ground velocities during surface-breaking strike-slip earthquakes".</p>
Data supporting paper "Efficient numerical simulation of density-driven flows: Application to the 2- and 3-D Elder problem"
<p>Data supporting paper "Efficient numerical simulation of density-driven flows: Application to the 2- and 3-D Elder problem", Water Resources Research.</p>
Numerical data for dynamic rupture simulations of coseismic slickenlines on non-planar and rough faults
<p>Numerical data used to make Figures in the manuscript entitled "Dynamic simulations of coseismic slickenlines on non-planar and rough faults (Aoki et al., GJI)"</p>
Data for "Identification of Karst Spring Hydrographs Using Laboratory and Numerical Simulations Considering Combined Discrete-Continuum Approaches"
<p>This is the dataset for "Identification of Karst Spring Hydrographs Using Laboratory and Numerical Simulations Considering Combined Discrete-Continuum Approaches”.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.