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855 results for “model system”
Modelling and Comparing Converter Architectures and Energy Harvesting ICs for Battery-Free Systems
<p>Artifacts containing measurement scripts, data sets, and simulations for the paper "Modelling and Comparing Converter Architectures and Energy Harvesting ICs for Battery-Free Systems" (currently submitted and under review).</p>
Data and Codes of A Deep Learning-Based Consistency Test for Earth System Models on Heterogeneous Many-Core Systems
<p>These are the supporting information to verify the results in the paper, including input data, model outputs, the postprocessing scripts and the source codes.</p>
Supporting Dataset for the study "A simple Approach to Represent Irrigation Water Withdrawals in Earth System Models"
<p><span><span>This archive contains the following information (8 directories):</span></span></p> <ol> <li> <p><span><span>surfex_v8.0climat : ISBA-CTRIP source code from CNRM-ESM-2 used in the study</span></span></p> </li> <li> <p><span><span>model_data : parameters used by the model and to plot the figures</span></span></p> </li> <li> <p><span><span>fig : ncl scripts to plot the figures & figures in eps</span></span></p> </li> <li> <p><span><span>discharges : simulated and observed river discharges data</span></span></p> </li> <li> <p><span><span>fluxes : simulated water fluxes plotted on the figures</span></span></p> </li> <li> <p><span><span>tws : estimated and simulated terrestrial water storage data</span></span></p> </li> <li> <p><span><span>withdrawals : imposed (impirrig) and simulated (irrig) irrigation water withdrawals</span></span></p> </li> <li> <p><span><span>wtd : simulated and estimated groundwater levels and trends</span></span></p> </li> </ol>
Simulation outputs associated with Maffre et al. "GEOCLIM7, an Earth System Model for multi-million years evolution of the geochemical cycles and climate." (submitted to GMD)
Open the record for dataset details and reuse information.
Monitoring and benchmarking Earth system model simulations with ESMValTool v2.12.0
<p>This dataset contains the EMAC model output and the ESMValTool recipes used to created the figures of</p> <p>Lauer, A., L. Bock, B. Hassler, P. Jöckel, L. Ruhe, and M. Schlund: Monitoring and benchmarking Earth system model simulations with ESMValTool v2.12.0, Geosci. Model Dev. (accepted).</p> <p>The files in <strong>emac_3hr.tar.gz</strong> contain 3-hourly data from the EMAC simulation used for figure 4 (diurnal cycles).</p> <p>The files in <strong>emac_Amon.tar.gz</strong> contain monthly mean data from the EMAC simulation used for figures 1, 2, 3, 5, 6, 7, 8 (time series, seasonal cycles, map plots, zonal mean plots, box plots, portrait diagram).</p> <p>The ESMValTool recipes used to produces these figures are contained in<strong> esmvaltool_recipes_v2.tar.gz</strong> and can be used with Earth System Model Evaluation Tool v2.12.0 available on GitHub at <a href="https://github.com/ESMValGroup/ESMValTool">https://github.com/ESMValGroup/ESMValTool</a> or on Zenodo at <a href="https://doi.org/10.5281/zenodo.3401363">https://doi.org/10.5281/zenodo.3401363</a>.</p>
Model Catalytic Studies on the Thermal Dehydrogenation of the Benzaldehyde/Cyclohexylmethanol LOHC System on Pt(111)
<p>Primary data, meta data, and corresponding lists of figures & tables are included.</p>
Bathymetric and surface digital model of the river-floodplain system corresponding to the Duero river reach between Toro and Zamora (Castilla y León).
<p>Digitally edited digital model to represent correctly and with hydraulic criteria the bridges, weirs, dips, roads and walls present in the area.</p>
Bathymetric and terrain digital model (representative of the geomorphological reference condition) of the river-floodplain system corresponding to the Douro reach between Toro and Zamora (Castilla y León).
<p>Digitally edited digital model to represent the previous geomorphological situation in the Toro-Zamora section.</p>
Data Bundle for PyPSA-Eur-Sec: A Sector-Coupled Open Optimisation Model of the European Energy System
<p>While small data files used in PyPSA-Eur-Sec are included directly in the git repository, larger ones are collected in this data bundle. The data bundle’s size is around 680 MB.</p> <p><strong>Licenses</strong></p> <p>Different licenses apply to the various components of this data bundle (mostly attribution).</p> <p>For details see <a href="https://pypsa-eur-sec.readthedocs.io/en/latest/installation.html#data-requirements">https://pypsa-eur-sec.readthedocs.io/en/latest/installation.html#data-requirements</a></p> <p><strong>Changelog 0.3.1</strong></p> <ul> <li>Fix IRENASTAT encoding</li> </ul> <p><strong>Changelog 0.3.0</strong></p> <ul> <li>Add <a href="https://pxweb.irena.org/pxweb/en/IRENASTAT">IRENASTAT</a> country-level power generation capacities.</li> </ul> <p><strong>Changelog 0.2.0</strong></p> <ul> <li>add hydrogen salt cavern storage potential (h2_salt_caverns_GWh_per_sqkm.geojson)</li> </ul> <p> </p>
Data and Codes of Characterizing Uncertainties of Earth System Modeling with Heterogeneous Many-core Architecture Computing
<p>These are the supporting information to verify the results in the paper, including input data, model outputs, the postprocessing scripts and the source codes.</p>
Diurnal rainfall response to the physiological and radiative effects of CO2 in tropical forests in the Energy Exascale Earth System Model v1
<p>Necessary outputs and scripts for recreating the figures for the journal article with the same title.</p>
Data bundle for egon-data: A transparent and reproducible data processing pipeline for energy system modeling
<p><strong>egon-data</strong> provides a transparent and reproducible open data based data processing pipeline for generating data models suitable for energy system modeling. The data is customized for the requirements of the research project <strong>eGo<sup>n</sup></strong>. The research project aims to develop tools for an open and cross-sectoral planning of transmission and distribution grids. For further information please visit the eGo<sup>n</sup> <a href="https://ego-n.org/">project website</a> or its <a href="https://github.com/openego/eGon-data">Github repository.</a></p> <p>egon-data retrieves and processes data from several different external input sources. As not all data dependencies can be downloaded automatically from external sources we provide a data bundle to be downloaded by egon-data.</p> <p>The following data sets are part of the available data bundle:</p> <ol> <li><strong>climate_zones_germany</strong> <ul> <li>Climate zones in Germany</li> <li>source: Own representation based on DWD TRY climate zones</li> <li>License: Attribution 4.0 International (CC BY 4.0)</li> </ul> </li> <li><strong>emobility</strong> <ul> <li>Data on eMobility mit_trip_data:<br> motorized individual travel - individual trips of electric vehicles (EV) generated with a modified version of simBEV v0.1.3 (https://github.com/rl-institut/simbev/tree/1f87c716d14ccc4a658b8d2b01fd12b88a4334d5). simBEV generates driving profiles for BEVs and PHEVs based upon MID data (BMVI) per RegioStaR7 region type (BBSR).</li> <li>Reiner Lemoine Institut, June 2022</li> <li>License: Attribution 4.0 International (CC BY 4.0)</li> </ul> </li> <li><strong>geothermal_potential</strong> <ul> <li>Spatial distribution of deep geothermal potentials in Germany</li> <li>source: <a href="https://doi.org/10.3390/en11020332">Assessment and Public Reporting of Geothermal Resources in Germany: Review and Outlook</a></li> <li>License: Attribution 4.0 International (CC BY 4.0)</li> </ul> </li> <li><strong>household_electricity_demand_profiles</strong> <ul> <li>Annual profiles in hourly resolution of electricity demand of private households for different household types (singles, couples, other) with varying number of elderly and children.<br> The profiles were created using a bottom-up load profile generator by Fraunhofer IEE developed in the Bachelor's thesis "Auswirkungen verschiedener Haushaltslastprofile auf PV-Batterie-Systeme" by Jonas Haack, Fachhochschule Flensburg, December 2012.<br> The columns are named as follows: "<HH_TYPE_PREFIX>a<PROFILE_ID>", e.g. P2a0000 is the first profile of a couple's household with 2 children. See publication below for the list of prefixes. Values are given in Wh.<br> A related conference paper can be obtained here: http://publica.fraunhofer.de/documents/N-374761.html</li> <li>License: Attribution 4.0 International (CC BY 4.0)</li> </ul> </li> <li><strong>household_heat_demand_profiles</strong> <ul> <li>Sample heat time series including hot water and space heating for single- and multi-familiy houses. The profiles were created using the loadprofile generator by Fraunhofer IEE developed in the Master's thesis "Synthesis of a heat and electrical load profile for single and multi-family houses used for subsequent performance tests of a multi-component energy system", Simon Ruben Drauz, RWTH Aachen University, March 2016</li> <li>License: Attribution 4.0 International (CC BY 4.0)</li> </ul> </li> <li><strong>hydrogen_storage_potential_saltstructures</strong> <ul> <li>The data are taken from figure 7.1 in Donadei, S., et al., (2020), p. 7-5..</li> <li>Source: Flach lagernde Salze, (c) BGR Hannover, 2021.<br> Datenquelle: InSpEE-Salzstrukturen, (c) BGR, Hannover, 2015. &<br> Donadei, S., Horváth, B., Horváth, P.-L., Keppliner, J., Schneider, G.-S., &<br> Zander-Schiebenhöfer, D. (2020). Teilprojekt Bewertungskriterien und<br> Potenzialabschätzung. BGR. Informationssystem Salz: Planungsgrundlagen,<br> Auswahlkriterien und Potenzialabschätzung für die Errichtung von Salzkavernen<br> zur Speicherung von Erneuerbaren Energien (Wasserstoff und Druckluft) –<br> Doppelsalinare und flach lagernde Salzschichten: InSpEE-DS. Sachbericht.<br> Hannover: BGR.</li> <li>License: The original data are licensed under the GeoNutzV, see https://sg.geodatenzentrum.de/web_public/gdz/lizenz/geonutzv.pdf</li> </ul> </li> <li><strong>industrial_sites</strong> <ul> <li>Information about industrial sites with DSM-potential in Germany from a Master's thesis by Danielle Schmidt. The data set includes own information on the coordinates of every industrial site.</li> <li>source: Schmidt, Danielle. (2019). Supplementary material to the masters thesis: NUTS-3 Regionalization of Industrial Load Shifting Potential in Germany using a Time-Resolved Model [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3613767</li> <li>License: Attribution 4.0 International (CC BY 4.0)</li> </ul> </li> <li><strong>nep2035_version2021</strong> <ul> <li>Data extracted from the German grid development plan - power</li> <li>source: Netzentwicklungsplan Strom 2035 (2021), erster Entwurf | Übertragungsnetzbetreiber (M) CC-BY-4.0</li> <li>License: Attribution 4.0 International (CC BY 4.0)</li> </ul> </li> <li><strong>pipeline_classification_gas</strong> <ul> <li>Parameters for the classification of gas pipelines</li> <li>source: Single parameters extracted from <a href="https://www.econstor.eu/bitstream/10419/173388/1/1011162628.pdf">Electricity, Heat and Gas Sector Data for Modelling the German System</a></li> <li>License: Attribution 4.0 International (CC BY 4.0)</li> </ul> </li> <li><strong>pypsa_eur_sec</strong> <ul> <li>Preliminary results from scenario generator pypsa-eur-sec</li> <li>source: own calculation using pypsa-eur-sec fork (https://github.com/openego/pypsa-eur-sec)</li> <li>License: Attribution 4.0 International (CC BY 4.0)</li> </ul> </li> <li><strong>regions_dynamic_line_rating</strong> <ul> <li>German regions suitable to model dynamic line rating</li> <li>source: Own representation based on <a href="https://www.transnetbw.de/files/pdf/netzentwicklung/netzplanungsgrundsaetze/UENB_PlGrS_Juli2020.pdf">Grundsätze für die Ausbauplanung des Deutschen Übertragungsnetze (2020)</a></li> <li>License: Attribution 4.0 International (CC BY 4.0)</li> </ul> </li> <li><strong>re_potential_areas</strong> <ul> <li>Eligible areas for wind turbines and ground-mounted PV systems.</li> <li>Reiner Lemoine Institut, January 2022</li> <li>License: Attribution 4.0 International (CC BY 4.0)</li> </ul> </li> <li><strong>WZ_definition</strong> <ul> <li>Definitions of industrial and commercial branches</li> <li>source: <a href="https://www.destatis.de/static/DE/dokumente/klassifikation-wz-2008-3100100089004.pdf">Klassifikation der Wirtschaftszweige (WZ 2008)</a></li> <li>Extract from Terms of Use: © Statistisches Bundesamt, Wiesbaden 2008 Vervielfältigung und Verbreitung, auch auszugsweise, mit Quellenangabe gestattet.</li> </ul> </li> <li><strong>zensus_households</strong> <ul> <li>Dataset describing the amount of people living by a certain types of family-types, age-classes,sex and size of household in Germany in state-resolution.</li> <li>source: Data retrieved from <a href="https://ergebnisse2011.zensus2022.de/datenbank/online">Zensus Datenbank</a> by performing these steps: <ul> <li>Search for: "1000A-2029"</li> <li>or choose topic: "Bevölkerung kompakt"</li> <li>Choose table code: "1000A-2029" with title "Personen: Alter (11 Altersklassen)/Geschlecht/Größe desprivaten Haushalts - Typ des privaten Haushalts (nach Familien/Lebensform)"</li> <li>Change setting "GEOLK1" to "Bundesländer (16)" higher resolution "Landkreise und kreisfreie Städte (412)" only accessible after registration.</li> </ul> </li> <li>Extract from Terms of Use: © Statistische Ämter des Bundes und der Länder 2021, Vervielfältigung und Verbreitung, auch auszugsweise, mit Quellennachweis gestattet.</li> </ul> </li> </ol> <p> </p>
Systemic optimization of gene electrotransfer protocol using hard-to-transfect UT-7 cell line as a model
<p><strong>Externally hosted supplementary file. </strong>Table S1: Table results of one-way ANOVA, followed by a post-hoc Tukey multiple comparison test. <em>P</em><0.05 value was considered statistically significant. Significant differences are marked in red. Table S2: Table results of one-way ANOVA, followed by a post-hoc Tukey multiple comparison test. <em>P</em><0.05 value was considered statistically significant. Significant differences are marked in red. Table S3: Table results of one-way ANOVA, followed by a post-hoc Tukey multiple comparison test. <em>P</em><0.05 value was considered statistically significant. Significant differences are marked in red.</p>
Code and data for results and figures of the manuscript "Multi-million year cycles in modelled δ13C as a response to astronomical forcing of organic matter fluxes." submitted to Earth System Dynamics
<p>This dataset contains the code of the model used in the manuscript submitted to Earth System Dynamics "Multi-million year cycles in modelled δ13C as a response to astronomical forcing of organic matter fluxes.". It also contains some model outputs and code to draw the figures.</p>
Supporting data - The Met Office operational wave forecasting system: the evolution of the Regional and Global models
<p>Supporting data for the GMD draft paper "The Met Office operational wave forecasting system: the evolution of the Regional and Global models" (© Crown copyright Met Office):</p> <p>1) idealised_sensitivity_resolution.tar.gz: idealised experiment folders with grid and model definition files needed to run the experiments; and output .nc files used in analysis. </p> <p>2) analysis_MO_waves_system.tar.gz: folders for GS512L4EUK-AN and AMM15SL2-AN runs with 2-year model-observations matchup .nc files used in figures and analysis.</p> <p>3) forecast_MO_waves_system.tar.gz: folders for GS512L4EUK-FCST and AMM15SL2-FCST runs during summer (#-s) and winter (#-w) with model-observations matchup .nc files used in figures and analysis.</p>
European power system infrastructure in the open energy system model PyPSA-Eur
<p>The image is created using the data and scripts in the European open energy system model <a href="https://github.com/PyPSA/pypsa-eur">PyPSA-Eur.</a></p>
MAgPIE model runs outputs: Climate change-driven global land-use system adaptation under CMIP6-based crop model projections
<p>Each folder contains the fulldata.gdx and the configuration files for each MAgPIE run based on the nine crop impact models and 5 gcms used in the paper.</p>
Experimental data for validation of a single-storey flexible double-skin façade system model
<p>Double skin façades are adaptive envelopes aiming at improving building energy use and comfort performance. Their adaptive principle relies on the dynamic management of the cavity’s ventilation flow and the shading device (when available). They can also be integrated with the environmental systems for heating, cooling, and ventilation. In most cases, though, the possible exploitation of the ventilation airflow is not fully enabled, as the adoption of only one or two possible airpath limits the possibility that this façade architecture offers and flexible interaction with the environmental systems is not planned. This work aims to develop, using an existing software tool for building energy simulation, a numerical model of a flexible double-skin façade module capable of fully exploiting the adaptive features of such envelope concept by switching between different cavity ventilation strategies. Leveraging on the Double Glass Facade component available in IDA ICE, a new model for a flexible double-skin façade module was developed, and its performance in replicating the thermophysical behaviours of such a dynamic system has been assessed by comparison with experimental data collected through a dedicated experimental activity using one the outdoor test cells of the TWINS facility in Torino (Italy). The accuracy of the predictions resulted in line with the performance obtained by the Double Glass Facade component to simulate conventional double-skin facades. By establishing a new archetype model to study the performance and optimal integration of a large class of double-skin façade modules, including fully flexible ones, this works demonstrated the possibility of modifying existing models in building energy simulation tools to study unconventional building envelope model solutions such as adaptive façade systems.</p>
Model configuration and input files for: "CARIB12: A Regional Community Earth System Model / Modular Ocean Model 6 Configuration of the Caribbean Sea"
<p>This collection hosts the configuration and input files to reproduce the regional CESM/MOM6 simulation in: "CARIB12: A Regional Community Earth System Model / Modular Ocean Model 6 Configuration of the Caribbean Sea". <br><br>The initial, open boundary conditions and monthly means for the sponge layers were generated from the GLORYS12V1 reanalysis: <a href="https://doi.org/10.3389/feart.2021.698876">https://doi.org/10.3389/feart.2021.698876</a></p> <p>The tidal amplitudes and phases were generated from the TPXO model: <a href="https://doi.org/10.1175/1520-0426(2002)019<0183:EIMOBO>2.0.CO;2">https://doi.org/10.1175/1520-0426(2002)019<0183:EIMOBO>2.0.CO;2 </a></p> <p>The monthly Chlorophyll-a climatology was generated from the SeaWifs mission dataset: <a href="10.5067/ORBVIEW-2/SEAWIFS/L3M/CHL/2018">10.5067/ORBVIEW-2/SEAWIFS/L3M/CHL/2018</a></p> <p>The river runoff to ocean was generated from the GloFAS dataset: <a href="https://doi.org/10.24381/cds.a4fdd6b9">https://doi.org/10.24381/cds.a4fdd6b9 </a></p> <p>The topography was generated from the Shuttle Radar Topography Mission: <a href="https://doi.org/10.1029/2019EA000658">https://doi.org/10.1029/2019EA000658</a> and smoothed with a Cressman weighted interpolation scheme.</p> <p>This collection does not include the JRA55-do atmospheric forcing dataset: <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.ocemod.2018.07.002" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.ocemod.2018.07.002</a> </p> <p>Steps to setup a regional configuration of CESM/MOM6 can be found here: <a href="https://github.com/NCAR/regional_cesm_mom6.git">https://github.com/NCAR/regional_cesm_mom6.git</a> </p> <p> </p>
Model output for: "CARIB12: A Regional Community Earth System Model / Modular Ocean Model 6 Configuration of the Caribbean Sea"
<p>This collection hosts the model output fields used in : "CARIB12: A Regional Community Earth System Model / Modular Ocean Model 6 Configuration of the Caribbean Sea". <br><br>daily_surface_fields.tar: contains daily output of sea surface salinity, surface u and v velocity components, sea-surface height and mixed layer depths. Files are split in two: 2000-01-01:2009-12-31 and 2010-01-01:2019-12-31 as specified by each filename.</p> <p>monthly_3D_tracers.tar: contains monthly mean output of temperature and salinity for the full 3D field (lat,lon,depth). Files are split in two: 2000-01-01:2009-12-31 and 2010-01-01:2019-12-31 as specified by each filename.</p> <p> </p> <p> </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.