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50 results for “numerical experiments”
Free surface evolution from numerical wave tank simulations - Experiment W6N5D5
<p>An ensemble of two-dimensional numerical wave tank (NWT) simulations of breaking and non-breaking wave packets. The NWT uses the Gerris software package, a two-phase Navier-Stokes solver that utilises the volume-of-fluid method and explicitly models viscosity and surface tension effects. It is configured in non-dimensional coordinates scaled by the length and time characteristics of a deep-water wave with wavelength 1 m. This dataset contains simulations from experiment W6N5D5 (wind forcing speed equal to 6 times the wave speed, chirped wave packet with 5 waves in the packet signal, deep water) and forms part of an ensemble of experiments available <a href="https://doi.org/10.5281/zenodo.12797829" target="_blank" rel="noopener">here</a>. A full description of the NWT is provided in:</p> <p><a href="https://doi.org/10.1017/jfm.2023.134" target="_blank" rel="noopener">Boettger, D. G., Keating, S. R., Banner, M. L., Morison, R. P., & Barthelemy, X. (2023). An energetic signature for breaking inception in surface gravity waves. Journal of Fluid Mechanics, 959, A33.</a></p> <p><a href="https://doi.org/10.1103/PhysRevFluids.9.054803" target="_blank" rel="noopener">Boettger, D. G., Keating, S. R., Banner, M. L., Morison, R. P., & Barthelemy, X. (2024). Energetic inception of breaking in surface gravity waves under wind forcing. Physical Review Fluids, 9 (5), 054803.</a></p>
Free surface evolution from numerical wave tank simulations - Experiment W0N5D2
<p>An ensemble of two-dimensional numerical wave tank (NWT) simulations of breaking and non-breaking wave packets. The NWT uses the Gerris software package, a two-phase Navier-Stokes solver that utilises the volume-of-fluid method and explicitly models viscosity and surface tension effects. It is configured in non-dimensional coordinates scaled by the length and time characteristics of a deep-water wave with wavelength 1 m. This dataset contains simulations from experiment W0N5D2 (Zero wind forcing, chirped wave packet with 5 waves in the packet signal, intermediate water depth) and forms part of an ensemble of experiments available <a href="https://doi.org/10.5281/zenodo.12797829" target="_blank" rel="noopener">here</a>. A full description of the NWT is provided in:</p> <p><a href="https://doi.org/10.1017/jfm.2023.134" target="_blank" rel="noopener">Boettger, D. G., Keating, S. R., Banner, M. L., Morison, R. P., & Barthelemy, X. (2023). An energetic signature for breaking inception in surface gravity waves. Journal of Fluid Mechanics, 959, A33.</a></p> <p><a href="https://doi.org/10.1103/PhysRevFluids.9.054803" target="_blank" rel="noopener">Boettger, D. G., Keating, S. R., Banner, M. L., Morison, R. P., & Barthelemy, X. (2024). Energetic inception of breaking in surface gravity waves under wind forcing. Physical Review Fluids, 9 (5), 054803.</a></p>
Free surface evolution from numerical wave tank simulations - Experiment W0N5D5
<p>An ensemble of two-dimensional numerical wave tank (NWT) simulations of breaking and non-breaking wave packets. The NWT uses the Gerris software package, a two-phase Navier-Stokes solver that utilises the volume-of-fluid method and explicitly models viscosity and surface tension effects. It is configured in non-dimensional coordinates scaled by the length and time characteristics of a deep-water wave with wavelength 1 m. This dataset contains simulations from experiment W0N5D5 (Zero wind forcing, chirped wave packet with 5 waves in the packet signal, deep water) and forms part of an ensemble of experiments available <a href="https://doi.org/10.5281/zenodo.12797829" target="_blank" rel="noopener">here</a>. A full description of the NWT is provided in:</p> <p><a href="https://doi.org/10.1017/jfm.2023.134" target="_blank" rel="noopener">Boettger, D. G., Keating, S. R., Banner, M. L., Morison, R. P., & Barthelemy, X. (2023). An energetic signature for breaking inception in surface gravity waves. Journal of Fluid Mechanics, 959, A33.</a></p> <p><a href="https://doi.org/10.1103/PhysRevFluids.9.054803" target="_blank" rel="noopener">Boettger, D. G., Keating, S. R., Banner, M. L., Morison, R. P., & Barthelemy, X. (2024). Energetic inception of breaking in surface gravity waves under wind forcing. Physical Review Fluids, 9 (5), 054803.</a></p>
Free surface evolution from numerical wave tank simulations - Experiment W0N9D5
<p>An ensemble of two-dimensional numerical wave tank (NWT) simulations of breaking and non-breaking wave packets. The NWT uses the Gerris software package, a two-phase Navier-Stokes solver that utilises the volume-of-fluid method and explicitly models viscosity and surface tension effects. It is configured in non-dimensional coordinates scaled by the length and time characteristics of a deep-water wave with wavelength 1 m. This dataset contains simulations from experiment W0N9D5 (Zero wind forcing, chirped wave packet with 9 waves in the packet signal, intermediate water depth) and forms part of an ensemble of experiments available <a href="https://doi.org/10.5281/zenodo.12797829" target="_blank" rel="noopener">here</a>. A full description of the NWT is provided in:</p> <p><a href="https://doi.org/10.1017/jfm.2023.134" target="_blank" rel="noopener">Boettger, D. G., Keating, S. R., Banner, M. L., Morison, R. P., & Barthelemy, X. (2023). An energetic signature for breaking inception in surface gravity waves. Journal of Fluid Mechanics, 959, A33.</a></p> <p><a href="https://doi.org/10.1103/PhysRevFluids.9.054803" target="_blank" rel="noopener">Boettger, D. G., Keating, S. R., Banner, M. L., Morison, R. P., & Barthelemy, X. (2024). Energetic inception of breaking in surface gravity waves under wind forcing. Physical Review Fluids, 9 (5), 054803.</a></p>
Free surface evolution from numerical wave tank simulations - Experiment W1N5D5
<p>An ensemble of two-dimensional numerical wave tank (NWT) simulations of breaking and non-breaking wave packets. The NWT uses the Gerris software package, a two-phase Navier-Stokes solver that utilises the volume-of-fluid method and explicitly models viscosity and surface tension effects. It is configured in non-dimensional coordinates scaled by the length and time characteristics of a deep-water wave with wavelength 1 m. This dataset contains simulations from experiment W1N5D5 (wind forcing speed equal to wave speed, chirped wave packet with 5 waves in the packet signal, deep water) and forms part of an ensemble of experiments available <a href="https://doi.org/10.5281/zenodo.12797829" target="_blank" rel="noopener">here</a>. A full description of the NWT is provided in:</p> <p><a href="https://doi.org/10.1017/jfm.2023.134" target="_blank" rel="noopener">Boettger, D. G., Keating, S. R., Banner, M. L., Morison, R. P., & Barthelemy, X. (2023). An energetic signature for breaking inception in surface gravity waves. Journal of Fluid Mechanics, 959, A33.</a></p> <p><a href="https://doi.org/10.1103/PhysRevFluids.9.054803" target="_blank" rel="noopener">Boettger, D. G., Keating, S. R., Banner, M. L., Morison, R. P., & Barthelemy, X. (2024). Energetic inception of breaking in surface gravity waves under wind forcing. Physical Review Fluids, 9 (5), 054803.</a></p>
Numerical experiments on granulation-generated two-fluid waves and flows in a solar magnetic carpet
<p>An animation showing log(Ti) overlaid by magnetic field lines which correspond to a magnetic carpet.</p> <p>The jets shown on the movie are generated by the solar granulation, which leads to reconnection of magnetic field lines and thermal energy release in the photosphere and the chromosphere.</p>
Numerical Experiments Bayessian Illumination
<p><strong>Numerical Experiments for Bayesian Illumination</strong></p> <p>This file contains the numerical experiments conducted for the manuscript titled “Bayesian Illumination: Inference and Quality-Diversity Accelerate Generative Molecular Models.” The experiments provide comprehensive benchmarking and validation of the Bayesian Illumination algorithm, which integrates Bayesian optimization with quality-diversity methods to improve molecular discovery.</p> <p>The data includes:</p> <ul> <li>Descriptor-Based Rediscovery: Results from a novel benchmark where molecules are rediscovered based on conformer samples and descriptor-based representations (USRCAT and Zernike descriptors).</li> <li>Efficient Organic Photovoltaics: Performance metrics from multiple tasks, including maximising HOMO-LUMO gap values, minimising LUMO energy<br>values, maximising the molecular dipole moment and maximising a combined efficiency score).</li> <li>Docking-Based Tasks: Outputs from docking-based optimizations, including stringent structural and physicochemical filtering to ensure realistic molecular designs. This also includes synthetic accessibility-adjusted docking scores.</li> </ul> <p>This file serves as a supplement to the manuscript, providing the raw data and detailed performance metrics to support the reproducibility of the findings.</p> <p> </p> <p> </p> <p> </p>
Dataset: Numerical experiments on the sensitivity of Chesapeake Bay N2O cycles to climate warming and nutrient reductions and the associated code and input files
<p>A three-dimensional numerical model of the Chesapeake Bay (East Coast of the United States) was used to simulate the N<sub>2</sub>O cycle. The model is an implementation of the Regional Ocean Modeling System (ROMS, <a href="https://www.myroms.org/" target="_new" rel="noopener">https://www.myroms.org/</a>) with modules for sediment resuspension (Warner et al. 2008) and biogeochemistry (St-Laurent et al. 2020), with the latest addition of N<sub>2</sub>O as a separate state variable. It simulates hydrodynamics and biogeochemistry with a horizontal resolution of approximately 1.8 km and 20 topography-following vertical levels. Physical forcings include the ERA5 reanalysis (3-hourly) and tidal constituents from Szpilka et al. (2016).</p> <p>The dataset includes four primary numerical experiments designed to highlight the sensitivity of the Chesapeake Bay N<sub>2</sub>O cycle to climate warming and terrestrial nutrient management. The reference run was conducted for the year 2016, which represents a normal streamflow year. Three sensitivity experiments retained the same model forcings as in the reference run, except for one of the following combinations:</p> <ol> <li>Decreased atmospheric N<sub>2</sub>O concentrations, decreased atmospheric temperature, and increased riverine nitrate and organic nitrogen concentrations to 1986 levels (<strong>Test1986</strong>).</li> <li>Decreased atmospheric N<sub>2</sub>O concentrations and increased riverine nitrate and organic nitrogen concentrations to 1986 levels (<strong>Test1986warming</strong>).</li> <li>Increased atmospheric N<sub>2</sub>O concentrations, increased atmospheric temperature, and decreased riverine nitrate and organic nitrogen concentrations to 2050 levels (<strong>Test2050</strong>).</li> </ol> <p>The file <code>Results_for_plot.zip</code> includes model outputs used to generate figures, including monthly Bay-wide N<sub>2</sub>O distribution and the daily N<sub>2</sub>O budget integrated over the Bay. In addition to the model outputs, this archive contains the computer code (<code>ROMS_Code.zip</code>) and the input files necessary to reproduce the model results (<code>input_files.zip</code>). The total size of the dataset is approximately 5 GB.</p> <p>References:</p> <p>Scavia, D., Kelly, E. L. A., & Hagy, J. D. (2006). A simple model for forecasting the effects of nitrogen loads on Chesapeake Bay hypoxia. <em>Estuaries and Coasts</em>, 29(4), 674–684. <a href="https://doi.org/10.1007/bf02784292">https://doi.org/10.1007/bf02784292</a></p> <p>St-Laurent, P., Friedrichs, M. A. M., Najjar, R. G., Shadwick, E. H., Tian, H., & Yao, Y. (2020). Relative impacts of global changes and regional watershed changes on the inorganic carbon balance of the Chesapeake Bay. <em>Biogeosciences</em>, 17(14), 3779–3796. <a href="https://doi.org/10.5194/bg-17-3779-2020">https://doi.org/10.5194/bg-17-3779-2020</a></p> <p>Warner, J. C., Sherwood, C. R., Signell, R. P., Harris, C. K., & Arango, H. G. (2008). Development of a three-dimensional, regional, coupled wave, current, and sediment-transport model. <em>Computers & Geosciences</em>, 34(10), 1284–1306. <a href="https://doi.org/10.1016/j.cageo.2008.02.012">https://doi.org/10.1016/j.cageo.2008.02.012</a></p>
Summary of results from numerical experiments described in research paper "A New Simheuristic Approach for Stochastic Runway Scheduling"
<p>This file provides a summary of results from the numerical experiments described in our research paper, "A New Simheuristic Approach for Stochastic Runway Scheduling".</p>
Effect of urban heat island mitigation strategies on precipitation and temperature in Montreal, Canada: case studies - Data from numerical experiments
<p>Surface data from the numerical experiments for the paper : "Effect of urban heat island mitigation strategies on precipitation and temperature in Montreal, Canada: case studies", submitted in PLOS Climate. </p> <p>The data is in NetCDF, structure as follow: 1 file per initialization date that contains the model outputs for the surface variables (air temperature, dew-point, relative humidity) and 1 file per initialization date that contains the accumulated precipitation. </p>
Investigating the velocity of magmatic intrusions and its relation with rock fracture toughness: insights from laboratory experiments and numerical models
<p>This repository provides compressed folders containing the velocity profiles recorded during our oil-filled crack propagation experiments and the code used to simulate those experiments. In particular, the files in compressed folders <strong>10ml</strong>, <strong>30ml</strong>, <strong>50ml</strong> and <strong>others_ml</strong> contain two columns corresponding to the tracked cracks' depth [m] and velocity [m/s]. The two folders <strong>DYKE-CODE_constant-Ef</strong> and <strong>DYKE-CODE_variable-Ef</strong> contain the Fortran90 code, the input and output files, and all the scripts needed to reproduce the simulations and the plots displayed in Figure 3 and Figure 4 of the article <em>"</em>Investigating the velocity of magmatic intrusions and its relation with rock fracture toughness: insights from laboratory experiments and numerical models<em>"</em><strong><em> </em></strong> by A. Gaete, F. Maccaferri, S. Furst, and V. Pinel.</p>
Mechanical data of rotary shear experiments, temperature measurements, and temperature numerical models for the manuscript: "Mechanical energy dissipation during seismic dynamic weakening in calcite-bearing faults"
<p>All data included in this data repository is ancillary to the manuscript "Energy dissipation during dynamic weakening in calcite-bearing fault rocks", submitted to Journal of Geophysical Research: Solid Earth. </p><p>The data consists in time series of high velocity friction experiments run with SHIVA (INGV, Rome), time series acquired from a two-color pyrometer (UC3M), the synchronization of the two, and numerical models. The data format is .mat, proprietary to Matlab, but they can be easily accessed with Python (see <a href="https://docs.scipy.org/doc/scipy/reference/generated/scipy.io.loadmat.html">link</a>). Each .mat contains vector of the measured variables when opened from Matlab, or dictionaries when opened using the scipy.loadmat() function. </p><p>SHIVA and PYRO red data (calibrated data), fin data (synchronized data), and shivaRED vect data (numerical model data) are included in this data repository in separate folders. Numerical models are grouped in subfolder by type of model (the relation fin data to model is 1:n). We included the scripts to convert SHIVA raw data into SHIVA red data (<a href="https://github.com/aretu/shivaUNIX">link to shivaUNIX</a>), SHIVA and PYRO red data into fin data (/scripts/syncing2021.m), to obtain numerical models from fin data (<a href="https://github.com/aretu/shivaRED">link to shivaRED</a>), and to plot data (/scripts/making plots.ipynb).</p>
Urban Ventilation Planning and Its Associated Benefits based on Numerical Experiments : A case study in Beijing, China
<p>dataset for Figures 1-7</p>
Integrated Full-Scale Physical Experiments and Numerical Modeling of the Performance and Rehabilitation of Highway Embankments
<p>Corresponding data set for Tran-SET Project No. 18GTLSU06. Abstract of the final report is stated below for reference:</p> <p>"The study aimed to fundamentally understand how soil strength and hydraulic properties are impacted by recurring cycles of wetting and drying induced by climate variability, with the practical implication of forecasting the stability of highway embankment slopes. The review of literature on the effects of long-term cyclic wetting-drying phases on hydro-mechanical properties of clayey soils suggests that only a few cycles of wetting and drying can impact the strength and hydraulic conductivity, where the latter can increase several orders of magnitude. Laboratory model-scale experiments of Louisiana and Texas soils are still ongoing and will relate the laboratory test results to weathering cycles by accounting for parameters such as rainfall intensity and duration, evapotranspiration, temperature, and relative humidity. The objective of the laboratory testing was to determine the strength and unsaturated soil properties of samples collected from laboratory model-scale experiments and to investigate the subsequent changes in the hydro-mechanical properties of those clayey soils. For example, shrinkage test results provided a measure of the propensity and extent of strength loss incurred by a soil specimen when exposed to weathering cycles. Numerical modeling of highway embankments with material properties and test results obtained from lab testing were used to predict the factor of safety for an embankment in Texas."</p>
Appendix The benchmark values are used in numerical experiments.
<p>Appendix The benchmark values are used in numerical experiments.</p>
Numerical Simulations of Laboratory-Scale, Hypervelocity-Impact Experiments for Asteroid-Deflection Code Validation
Open the record for dataset details and reuse information.
Earth Radiation Budget Experiment (ERBE) S-4GN (Nonscanner) Wide Field of View Numerical Filter (NF) 5.0 degree Regional Averages
ERBE_S4GN_WFOV_NF_1 is the Earth Radiation Budget Experiment (ERBE) S-4GN (Nons-canner) Wide Field of View Numerical Filter (NF) 5.0 degree Regional Averages data product. Data collection for this product is complete.ERBE was a multi-satellite system designed to measure the Earth's radiation budget. The ERBE instruments flew on a mid-inclination National Aeronautics and Space Administration (NASA) Earth Radiation Budget Satellite (ERBS) and two sun-synchronous National Oceanic and Atmospheric Administration (NOAA) satellites (NOAA-9 and NOAA-10). Each carried both a scanner and a non-scanner instrument package. The ERBE S-4G product contained the same time and space averages of all the individual estimates of radiant flux at the top-of-the-atmosphere for one month and one spacecraft or combination of spacecraft as the S-4N product. The difference between the two products was that S-4N is arranged by region, with all parameters for a region grouped together, while S-4GN presented gridded data, with all regions for a given parameter grouped together. The S-4GN data set consisted of non-scanner data processed without scene identification information from the scanner and with the numerical filter cross track enhancement.
Earth Radiation Budget Experiment (ERBE) S-4GN (Nonscanner) Wide Field of View Numerical Filter 5 deg. nested 10 deg. Regional Averages
ERBE_S4GN_WFV_NF_N10_1 is the Earth Radiation Budget Experiment (ERBE) S-4GN (Non-scanner) Wide Field of View Numerical Filter 5 deg. nested 10 deg. Regional Averages data set, which is in Hierarchical Data Format (HDF). Data collection for this data set is complete.ERBE was a multi-satellite system designed to measure the Earth's radiation budget. The ERBE instruments flew on a mid-inclination National Aeronautics and Space Administration (NASA) Earth Radiation Budget Satellite (ERBS) and two sun-synchronous National Oceanic and Atmospheric Administration (NOAA) satellites (NOAA-9 and NOAA-10). Each carried both a scanner and a non-scanner instrument package. The ERBE S-4G product contained the same time and space averages of all the individual estimates of radiant flux at the top-of-the-atmosphere (TOA) for one month and one spacecraft or combination of spacecraft as the S-4N product. The difference between the two products was that S-4N was arranged by region, with all parameters for a region grouped together, while S-4GN presented gridded data, with all regions for a given parameter grouped together. The S-4GN data set consisted of non-scanner data processed without scene identification information from the scanner and with the numerical filter cross track enhancement.
Earth Radiation Budget Experiment (ERBE) S-10N (Nonscanner-only) Wide Field of View (WFOV) Numerical Filter (NF) Radiant Flux and Albedo Edition 2 in Native Format
ERBE_S10N_WFOV_NF_Edition2 is the Earth Radiation Budget Experiment (ERBE) S-10N (Nonscanner-only) Wide Field of View (WFOV) Numerical Filter (NF) Radiant Flux and Albedo Edition 2 in Native Format data product. Data collection for this product is complete.The reprocessed ERBE S10N_WFOV ERBS Edition2 data product contains temporally and spatially averaged shortwave (SW) and longwave (LW) top-of-the-atmosphere (TOA) fluxes derived from one month of Earth Radiation Budget Experiment non-scanning wide field-of-view instruments aboard the Earth Radiation Budget Satellite. Instantaneous TOA fluxes from the ERBE/ERBS S7 product were spatially averaged on a 5° and 10° equal-angle grid using numerical filter and shape factor techniques, respectively. ERBE scanner-independent temporal interpolation algorithms were applied to produce daily, monthly-hourly, and monthly mean fluxes from the instantaneous gridded data. The S10N_WFOV files contain both temporally averaged and instantaneous gridded mean values of TOA total-sky LW flux, total-sky SW flux, and total-sky albedo for each 5° and 10° region observed during the month. The major differences between Edition2 and the original release are in the monthly mean fluxes with (1) the incorporation of stochastic quality assurance algorithms for filtering out monthly-mean data with excessive temporal sample errors and (2) a self-consistent usage of the WFOV data in selecting scene-dependent directional models for temporal interpolation of the ERBE WFOV instantaneous gridded data.
Earth Radiation Budget Experiment (ERBE) S-4GN (Nonscanner) Wide Field of View Numerical Filter (NF) Zonal and Global Averages
ERBE_S4GN_WFOV_NF_ZG data set contains Earth Radiation Budget Experiment (ERBE) S-4GN (Nonscanner-only) Wide Field of View Numerical Filter (NF) 5.0 and 10.0 degree Zonal and Global Averages in Hierarchical Data Format.The Earth Radiation Budget Experiment (ERBE) is a multi-satellite system designed to measure the Earth's radiation budget. The ERBE instruments fly on a mid-inclination National Aeronautics and Space Administration (NASA) Earth Radiation Budget Satellite (ERBS) and two sun-synchronous National Oceanic and Atmospheric Administration (NOAA) satellites (NOAA-9 and NOAA-10). Each carries both a scanner and a nonscanner instrument package.The ERBE S-4G product contains the same time and space averages of all the individual estimates of radiant flux at the top-of-the-atmosphere for one month and one spacecraft or combination of spacecraft as the S-4N product. The difference between the two products is that S-4N is arranged by region, with all parameters for a region grouped together, while S-4GN presents gridded data, with all regions for a given parameter grouped together.The S-4GN data set consists of nonscanner data processed without scene identification information from the scanner and with the numerical filter cross track enhancement.
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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)
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DANDI Archive for NWB datasets
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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.