Find research datasets worth reusing

opencc-by-4.0Dec 2022View details →

Data from: Davison et al. (2023) Vegetation structure from LiDAR explains the local richness of birds across Denmark

Environmental and biodiversity data associated with the article: Davison et al. (2023) Vegetation structure from LiDAR explains the local richness of birds across Denmark, Journal of Animal Ecology. Bird richness and abundance at points across Denmark, with matched land cover and LiDAR structural data. Bird observations are a subset of the Common Bird Monitoring programme (DOF – Birdlife Denmark) and pooled from summer counts of 2014, 15, and 16. Bird functional group assignments and environmental data are from open access data sets (see below). <table> <tbody> <tr> <td>Data source</td> <td>Reference</td> </tr> <tr> <td>Danish Common Bird Monitoring programme</td> <td>Eskildsen, D. P., Vikstrøm, T., & Jørgensen, M. F. (2021). Overvågning af de almindelige fuglearter i Danmark 1975-2020. Dansk Ornitologisk Forening.</td> </tr> <tr> <td>EcoDes-DK15 LiDAR data set of Denmark</td> <td>Assmann, J. J., Moeslund, J. E., Treier, U. A., & Normand, S. (2022). EcoDes-DK15: high-resolution ecological descriptors of vegetation and terrain derived from Denmark’s national airborne laser scanning data set. Earth System Science Data, 14(2), 823–844. https://doi.org/10.5194/essd-14-823-2022</td> </tr> <tr> <td>Pan-European land cover map of the year 2015 </td> <td>Pflugmacher, D., Rabe, A., Peters, M., & Hostert, P. (2019). Mapping pan-European land cover using Landsat spectral-temporal metrics and the European LUCAS survey. Remote Sensing of Environment, 221, 583–595. https://doi.org/10.1016/j.rse.2018.12.001</td> </tr> <tr> <td>AVONET bird traits data</td> <td>Tobias, J. A., Sheard, C., Pigot, A. L., Devenish, A. J. M., Yang, J., Neate-Clegg, M. H. C., Alioravainen, N., Weeks, T. L., Barber, R. A., Walkden, P. A., MacGregor, H. E. A., Jones, S. E. I., Vincent, C., Phillips, A. G., Marples, N. M., Montaño-Centellas, F., Leandro-Silva, V., Claramunt, S., Darski, B., … Schleunning, M. (2022). AVONET: morphological, ecological and geographical data for all birds. Ecology Letters, 25(3), 581–597. https://doi.org/10.1111/ele.13898</td> </tr> <tr> <td>Birds of the Palearctic - original source of trait data </td> <td>Cramp, S. (2006). The birds of the western Palearctic interactive. Oxford University Press and BirdGuides.</td> </tr> <tr> <td>Life-history characteristics of European birds - trait database</td> <td>Storchová, L., & Hořák, D. (2018). Life-history characteristics of European birds. Global Ecology and Biogeography, 27(4), 400–406. https://doi.org/10.1111/geb.12709</td> </tr> </tbody> </table>

NewSOC, supplementary information to WT2.5.4 "Cells with honeycomb structured oxygen electrodes": electrochemical and post-mortem data sets.

These are data set, related to participation of the IEN in project NewSOC. It includes results of the SEM-EDS analysis of the cells with hexagonal current collecting net and electrochemical performance data, both EIS and C-V characteristics. Results are grouped in zip archives, named according to cell design, “infill-net”. Compositions: LNF – LaNi0.6Fe0.4O3 (net) LSC – La0.6Sr0.4CoO3-d (infill) LSF – La0.5Sr0.5FeO3-d (infill) LSCCF – La0.6Sr0.4Co0.15Cu0.05Fe0.8O3-d (net) PCM – Pr0.5Ca0.5MnO3 (net) BSCFM – Ba0.5Sr0.5Co0.725Fe0.2Mo0.075O3-d (infill)   Data presentation. C-V characteristics: This is text files, generated by Zahner galvanostat, with self-decriptional titles. “05iv_650c_100h2+100h2o_500air.txt” –  measurement at 650°C, 100 mL/min H2 and 100 mL/min H2O on fuel side, 500 mL/min of air on air side. EIS data: EIS results were extracted from proprietary binary files, generated by Zahner galvanostat, and raw data is generally meaningless except the owners of such hardware. So, extracted EIS can be found in Excel files, used in analysis, in sheet “Experimental”. Other sheets in xlsx include some metadata (“info”), results of the equivalent circuit fit (“fit”) and some plots. Fit results might not be relevant.   SEM Post-mortem results presented as SEM images (tif or jpg files) and pdf files with results of the EDS analysis. LSC-LNF (air flow 1 L/min, current density 0.25 A/cm2) test_1_07:   03_eis20200917142808.xlsx – EIS, SOFC, 700°C, Flows L/min: F:0.2 H2; 05_eis20200917123105.xlsx – EIS, SOFC, 700°C, flows L/min: F:0.1 H2+ 0.1 H2O; 08_eis20200917123857.xlsx – EIS, SOFC, 700°C, flows L/min: F:0.1 H2+ 0.1 H2O; 10_eis20200917131537.xlsx – EIS, SOEC, 700°C, flows L/min: F:0.1 H2+ 0.1 H2O; test_1_08: 03_eis20200917125707.xlsx – EIS, SOFC, 700°C, Flows L/min: F:0.2 H2; 09_eis20200917130019.xlsx – EIS, SOEC, 700°C, flows L/min: F:0.09 H2+ 0.21 H2O; 10_eis20200917130600.xlsx – EIS, SOFC, 700°C, flows L/min: F:0.06 H2+ 0.14 H2O; 12_eis20200917130737.xlsx – EIS, SOEC, 700°C, flows L/min: F:0.12 H2+ 0.28 H2O; test_3_14: 01_eis20210517102042.xlsx– EIS, SOFC, 700°C, Flows L/min: F:0.1 H2+0.1 N2; 05_eis20210517102625.xlsx– EIS, SOFC, 700°C, flows L/min: F:0.1 H2+ 0.1 H2O; 07_eis20210517102305.xlsx– EIS, SOEC, 700°C, flows L/min: F:0.06 H2+ 0.14 H2O; SEM (post-mortem after test_1_07) ogniwo_310_2020  ****.jpg - surface   BSCMF-PCM (SOFC, air flow 0.5 L/min) test_2_14 01eis_700c_cc4a_100h2+100n2_500air_eqc20220110112836.xlsx –700°C, 0.25 A/cm2 Flows L/min: F:0.1 H2+0.1 N2 02eis_700c_cc4a_100h2+100h2o_500ai_eqc20220110112724.xlsx –700°C, 0.25 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 04eis_650c_cc3a_100h2+100h2o_500ai_eqc20220110112503.xlsx–650°C, 0.1875 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 06eis_650c_cc3a_100h2+100n2_500air_eqc20220110112332.xlsx –650°C, 0.1875 A/cm2 Flows L/min: F:0.1 H2+0.1 N2; 07eis_625c_cc3a_100h2+100n2_500air_eqc20220110112214.xlsx –625°C, 0.125 A/cm2 Flows L/min: F:0.1 H2+0.1 N2; 08eis_625c_cc3a_100h2+100h2o_500ai_eqc20220110111834.xlsx–625°C, 0.125 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; test_1_67 01_eqc20220831134628.xlsx–700°C, 0.125 A/cm2 Flows L/min: F:0.1 H2+0.1 N2 02_eqc20220831134724.xlsx - 700°C, 0.25 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 04_eqc20220831135442.xlsx–650°C, 0.0625 A/cm2 Flows L/min: F:0.1 H2+0.1 N2; 06_eqc20220831135622.xlsx - 650°C, 0.0625 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 08_eqc20220831135801.xlsx - 625°C, 0.0625 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 09_eqc20220831135933.xlsx –650°C, 0.0625 A/cm2 Flows L/min: F:0.1 H2+0.1 N2; SEM (post-mortem of the test_2_14) 493-2021-1.pdf, 493-2021-1i.pdf, 493-2021-2.pdf, 493-2021-2-2.pdf, 493-2021-2-3.pdf –cross-sections with EDS 493_2021_*_**.tif  - cross-sections   BSCMF-LSCCF (SOFC, air flow 0.5 L/min)                                test_2_08 01_eis20211104144342.xlsx - 700°C, 0.25 A/cm2 Flows L/min: F:0.1 H2+0.1 N2 03eis_700c__eis20211108102241.xlsx - 700°C, 0.25 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 04eis_700c__eis20211108102401.xlsx - 700°C, 0.25 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 08eis__eis20211110094642.xlsx - 650°C, 0.1875  A/cm2 Flows L/min: F:0.1 H2+0.1 N2 10eis__eis20211110094945.xlsx - 650°C, 0.1875 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 11eis__eis20211110101358.xlsx - 625°C, 0.125 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 13eis__eis20211110100837.xlsx- 625°C, 0.125 A/cm2 Flows L/min: F:0.1 H2+0.1 N2;                                test_2_26 04_eqc20220817114103.xlsx - 700°C, 0.25 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 06_eqc20220817121529.xlsx - 700°C, 0.25 A/cm2 Flows L/min: F:0.1 H2+0.1 N2 07_eqc20220802084119.xlsx - 650°C, 0.1875  A/cm2 Flows L/min: F:0.1 H2+0.1 08_eqc20220802084616.xlsx - 650°C, 0.1875 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 10_eqc20220802150705.xlsx - 625°C, 0.125 A/cm2 Flows L/min: F:0.1 H2+0.1 N2; 11_eqc20220802150108.xlsx - 625°C, 0.125 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; SEM (post-mortem of the test_2_26) 661_BSCMF_LSCCF_p.pdf  – cross-section with EDS 661_BSCMF_LSCCF_PM.pdf - surface with EDS 661_BSCMF_LSCCF_p_01.tif, 661_BSCMF_LSCCF_p_02.tif, 661_BSCMF_LSCCF_p_03.tif, 661_BSCMF_LSCCF_p_04.tif  -  cross-section, infill zone 661_BSCMF_LSCCF_p_05.tif, 661_BSCMF_LSCCF_p_06.tif - cross-section, net zone zone 661_BSCMF_LSCCF_PM_**.tif  - surface   LSF-LSCCF (SOFC, air flow 0.5 L/min) test_1_65 01_eqc20220816105347.xlsx - 700°C, 0. 1875 A/cm2 Flows L/min: F:0.1 H2+0.1 N2; 02_eqc20220816105941.xlsx - 700°C, 0. 1875 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 04_eqc20220816112311.xlsx - 650°C, 0. 125 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 06_eqc20220816111640.xlsx - 650°C, 0.125 A/cm2 Flows L/min: F:0.1 H2+0.1 N2; 07_eqc20220816142436.xlsx- 625°C, 0.0625 A/cm2 Flows L/min: F:0.1 H2+0.1 N2; 08_eqc20220816142842.xlsx-625°C, 0.625 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; SEM (post-mortem) 663_LSF_LSCCF_p.pdf – cross-section with EDS 663_LSF_LSCCF_PM.pdf - surface with EDS 663_LSF_LSCCF_P_GR_**.tif – cross-section of the cell 663_LSF_LSCCF_P_LSCCF_**.tif – surface of the LSCCF grid 663_LSF_LSCCF_PM_**.tif - surface of the LSF infill     LSF-PCM (SOFC, air flow 0.5 L/min) tests_1_66 01_eqc20220831133210.xlsx - 700°C, 0. 125 A/cm2 Flows L/min: F:0.1 H2+0.1 N2 02_eqc20220831133409.xlsx - 700°C, 0. 125 A/cm2 Flows L/min: F:0.1 H2+0.1 N2 03_eqc20220831133928.xlsx - 700°C, 0. 125 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 05_eqc20220831134048.xlsx - 650°C, 0.0625  A/cm2 Flows L/min: F:0.1 H2+0.1 N2; 06_eqc20220831134142.xlsx - 650°C, 0.0625 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 08_eqc20220831134237.xlsx - 625°C, 0.0625 A/cm2 Flows L/min: F:0.1 H2+0.1 H2O; 10_eqc20220831134412.xlsx - 625°C, 0.0625 A/cm2 Flows L/min: F:0.1 H2+0.1 N2; SEM (post-mortem) 658_LSF_PCM_p.pdf – cross-section with EDS 658_LSF_PCM_PM.pdf - surface with EDS 658_LSF_PCM_P_LSF_**.tif  – cross-section, infill zone 658_LSF_PCM_P_pcm_**.tif - cross-section, net zone 658_LSF_PCM_PM_**.tif - surface description.pdf - pdf version of this information.

Raw Data for the Article "Cyclopentadienone triisocyanide iron complexes: general synthesis and crystal structures of tris(2,6-dimethylphenyl isocyanide)(η4-tetraphenylcyclopentadienone)iron and tris(naphthalen-2-yl isocyanide)(η4-tetraphenylcyclopentadienone)iron acetone hemisolvate"

This data set contains the raw data (NMR, HRMS, Elemental analysis) for the article "Cyclopentadienone triisocyanide iron complexes: general synthesis and crystal structures of tris(2,6-dimethylphenyl isocyanide)(η4-tetraphenylcyclopentadienone)iron and tris(naphthalen-2-yl isocyanide)(η4-tetraphenylcyclopentadienone)iron acetone hemisolvate" published in Acta Crystallographica Section E: Crystallographic Communications, DOI: <a href="https://doi.org/10.1107/S205698902300498X">https://doi.org/10.1107/S205698902300498X</a>

DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction (Supplementary Data)

This dataset contains supplementary replication data for the paper titled "DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction". In particular, it contains a new version of our `final_raw_dips.tar.gz` protein pair representations which now contain (1) residue-level annotations for intrinsic disorder regions (IDRs) as well as (2) a copy of each protein pair representation in the HDF5 file format for programming language-agnostic read capabilities. In addition, this record also contains (3) raw MSAs (in HDF5 file format) generated for each protein pair using Jackhmmer and AlphaFold's small version of the Big Fantastic Database (BFD). Lastly, this record contains (4) PDB metadata derived for each DIPS-Plus complex using Graphein's PDBManager API as well as (5) structure-based (i.e., FoldSeek-based) training and validation splits of the dataset's complexes in the form of respective text files containing the file paths of complexes assigned to each split.

An assessment of acd_lotus for the structural dereplication of natural products using 13C NMR spectroscopy data.

A method that relies on carbon-13 nuclear magnetic resonance (NMR) spectroscopy, elaborated in earlier works of the author's research group, requires the availability of a dedicated database that establishes relationships between chemical structures, biological and chemical taxonomy, and spectroscopy. The construction of such a database, called <a href="https://doi.org/10.5281/zenodo.6621129">acd_lotus</a>, was reported earlier and its usefulness was only illustrated by <a href="https://doi.org/10.1002/cmtd.202200054">three examples</a>. This dataset provides the results of structure searches carried out starting from 58 carbon-13 NMR data sets recorded on compounds selected in the metabolomics section of BMRB, the biological magnetic resonance bank. Correction in the JSON file of ascochitine. Addition of a CSV file according to <a href="https://doi.org/10.1186/s13321-021-00520-4">Schymanski and Bolton</a> for the description of the selected compounds. Better PNG drawings for compounds 28, 38, 46, and 57. Better PNG drawing for compounds 7 and 26.

opencc-by-4.0Jul 2023View details →

Result data related to "Bersalli et al. (2024): Economic crises as critical junctures for policy and structural changes towards decarbonization – the cases of Spain and Germany"

Result data related to "Bersalli et al (2024): Economic crises as critical junctures for policy and structural changes towards decarbonization – the cases of Spain and Germany". The following files are included: <ul> <li>"Energy policy 2020-21 Germany-Spain.xlsx": Policy measures supporting clean energy during the Covid-19 pandemic in Germany and Spain. Data from <a href="http://energypolicytracker.org/">EnergyPolicyTracker.org</a>, amended by the authors.</li> <li> "factors.csv": Time series of emissions, population, GDP, energy intensity, and carbon intensity. Data derived from BP and Eurostat.</li> <li>"multiplicative-contribution-factors.csv": Time series of relative growth in the factors.</li> <li>"relative-cumulative-contribution-factors.csv": Time series of cumulative relative growth in the factors.</li> <li>"periods.csv": Relative growth in the factors during the global financial and COVID19 crises and before (pre) and after (post) the global financial crisis.</li> </ul>

opencc-by-4.0Jul 2023View details →

Molecular dynamics simulation data 1: Structure of the connexin-43 gap junction channel in a putative closed state

Molecular dynamics data for the manuscript Qi C.*, Acosta-Gutierrez S.*, Lavriha P., Othman A., Lopez-Pigozzi D., Bayraktar E., Schuster D., Picotti P., Zamboni N., Bortolozzi M., Gervasio F.L., Korkhov V.M. Structure of the connexin-43 gap junction channel in a putative closed state. eLife (2023) <a href="https://doi.org/10.7554/eLife.87616.2">https://doi.org/10.7554/eLife.87616.2</a> The dataset includes: 1. The starting coordinates, topology, MD inputs 2. Production run gromacs trajectories for the Cx43 gap junction channel

Dataset for "Adjoint Waveform Tomography for Crustal and Upper Mantle Structure the Middle East and Southwest Asia for Improved Waveform Simulations Using Openly Available Broadband Data"

This dataset contains the MESWA (Middle East and Southwest Asia) seismic model and auxiliary data used in the creation of the model (Rodgers, 2023).  MESWA is a three-dimensional model of the seismic properties of crust and upper mantle of the Middle East and Southwest Asia.  The MESWA model is provided in NetCDF format (readable by for example, xarray, Hoyer & Hamman, <a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JB022930#jgrb55516-bib-0057">2017</a>) and HDF5 format for viewing with ParaView (Ahrens et al., <a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JB022930#jgrb55516-bib-0002">2005</a>) and interaction with Salvus (Afanasiev et al., <a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JB022930#jgrb55516-bib-0001">2019</a>).    Also included are the earthquake source parameters for all 327 Global Centroid Moment Tensor events considered in this study in ASCII text format. Also included are lists of the selected 192 inversion events and 66 validation events in ASCII text format.  Lastly, we include a list of all receivers used in the creation and validation of MESWA.  This is a simple ASCII file with the event name and receiver name (composed of the network_code and station_code).   The following table provides a listing of the files in the dataset: <table> <tbody> <tr> <td> File </td> <td> Description </td> </tr> <tr> <td> MESWA.nc </td> <td> MESWA model in NetCDF format </td> </tr> <tr> <td> MESWA.h5 </td> <td> MESWA model in HDF5 format, used by Salvus </td> </tr> <tr> <td> MESWA.xmdf </td> <td> Auxiliary file for MESWA.h5, used to import model into Paraview </td> </tr> <tr> <td> events_project.csv </td> <td> Table of event source parameters for all 327 events considered in the project </td> </tr> <tr> <td> inversion_events_192.csv </td> <td> Table of 192 inversion events  (ASCII comma separated value) </td> </tr> <tr> <td> validation_events_66.csv </td> <td> Table of 66 validation events  (ASCII comma separated value) </td> </tr> <tr> <td> events_receivers_inversion.csv </td> <td> Table of waveform (event-receiver-channel) data used in the inversion (ASCII comma separated value) </td> </tr> <tr> <td> events_receivers_validation.csv </td> <td> Table of waveform (event-receiver-channel) data used in the validation (ASCII comma separated value) </td> </tr> </tbody> </table>     References Afanasiev, M, C Boehm, M van Driel, L Krischer, M Rietmann, DA May, MG Knepley, and A Fichtner (2019). Modular and flexible spectral-element waveform modelling in two and three dimensions, Geophys. J. Int., 216(3), 1675–1692, doi: 10.1093/gji/ggy469   Ahrens, J., Geveci, B., & Law, C. (2005). Paraview: An end-user tool for large data visualization. The Visualization Handbook, 717(8). <a href="https://doi.org/10.1016/b978-012387582-2/50038-1">https://doi.org/10.1016/b978-012387582-2/50038-1</a>   Hoyer, S., & Hamman, J. (2017). Xarray: N-D labeled arrays and datasets in Python. Journal of Open Research Software, 5(1). <a href="https://doi.org/10.5334/jors.148">https://doi.org/10.5334/jors.148</a>   Rodgers, A. (2023). Adjoint Waveform Tomography for Crustal and Upper Mantle Structure the Middle East and Southwest Asia for Improved Waveform Simulations Using Openly Available Broadband Data, technical report, LLNL-TR- 851939.   Acknowledgements This project was support by Lawrence Livermore National Laboratory’s Laboratory Directed Research and Development project 20-ERD-008 and the National Nuclear Security Administration.  This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-MI-852402

Björkö Wind Turbine Version 1 (45kW) high frequency Structural Health Monitoring (SHM) data

The Chalmers wind turbine has variable speed operation with a direct driven generator and a frequency converter, it also has a digital control system developed by Chalmers. The wind turbine has a rated power of 45 kW and rated speed of 75 rpm. The wooden tower is 30 m high, the blades of carbon fibres are 7.5 m long, and the turbine diameter is 15.9 m. The individually blade pitch system is electrical. The turbine is situated on the island Björkö at Skarviksvägen, 20 km west of Göteborg city. The coordinates are: 57.71818820625921, 11.683382148764485. 69 SCADA and structural vibration and loads Channels timeseries (sampled at 20 and 100 Hz) such as nacelle accelerations, tower and blades bending moments are included. Structured metadata about wind turbine characteristics, SCADA, vibration and loads channels are included as JSON files and CSV. This particular dataset consisting of high frequency sampled data, is intended for condition and structural health analysis. The data covers: <ul> <li>the measurements sampled at 100 Hz correspond to the period from 05 July 2022 to 9 June 2023</li> <li>the measurements sampled at 20 Hz correspond to the period from 05 July 2022 to 2 August 2023</li> </ul> This repository includes: Time-series data in csv format: <ul> <li>B1_CL4_20.csv (this is the data sampled at 20 Hz)</li> <li>B1_CL4_100.csv (this is the data sampled at 100 Hz)</li> </ul> Metadata: <ul> <li>Bjorko_Sensors_Specs_Metadata.csv (Sensors signals specification in csv format)</li> <li>Bjorko_modes_mapping.csv (numerical integer value representing the wind turbine controller system mode in csv format)</li> <li>Bjorko_modes_mapping.json (numerical integer value representing the wind turbine controller system mode in csv JSON format)</li> <li>Bjorko_digital_io_states_mappings.csv (Description of digital input and output states in the wind turbine controller system in csv format)</li> </ul> Media: <ul> <li>Chalmers-Wind turbine.pdf (description of the wind turbine including pictures)</li> <li>Chalmers wind turbine description 220121-short.pdf (description of the wind turbine including pictures)</li> </ul> Semantic artifacts: <ul> <li>N/A</li> </ul> Other: <ul> <li>N/A</li> </ul> Additional information is available upon request.

Aventa AV-7 ETH Zurich Research Wind Turbine SCADA and high frequency Structural Health Monitoring (SHM) data

General description of wind turbine: The ETH owned wind turbine is Aventa AV-7, manufactured by Aventa AG in Switzerland and was commissioned in December 2002. The turbine is operated via a belt-driven generator and a frequency converter with a variable speed drive. The rated power of the Aventa AV-7 is 7 kW, beginning production at a wind speed of 2 m/s and having a cut-off speed of 14 m/s. The rotor diameter is 12.8 m with 3 rotor blades, and a hub height is 18m. The maximum rotational speed of the turbine is 63 rpm. The tower is a tubular steel-reinforced concrete structure, supported on concrete foundation, while the blades are made of glassfiber with a tubular steel main-spar. The turbine is regulated via a variable-speed and variable pitch control system. Location of site: The wind turbine is located in Taggenberg, about 5 km from the city centre of Winterthur, Switzerland. This site is easily accessible by public transport and on foot with direct road access right next to the turbine. This prime location reduces the cost of site visits and allows for frequent personal monitoring of the site when test equipment is installed. The coordinates of the site are: 47°31'12.2"N 8°40'55.7"E. Control and measurement systems and signals: The turbine is regulated via a variable-speed and collective variable pitch control system. SHM Motivation: Designed and commissioned in 2002, the Aventa wind turbine in Winterthur is soon reaching its end of design lifetime. In order to assess the various techniques of predicting the remaining useful lifetime, a Structural Health Monitoring (SHM) campaign was implemented by ETH Zurich. The monitoring campaign started in 2020, and is still ongoing. In addition, the setup is used as a research platform on topics such as system identification, operational modal analysis, faults/damage detection and classification. We analyze the influence of operational and environmental conditions on the modal parameters and to further infer Performance Indicators (PIs) for assessing structural behavior in terms of deterioration processes. Data Description: The tower and nacelle have been instrumented with 11 accelerometers distributed along the length of the tower, nacelle main frame, main bearing and generator. Two full bridge strain gauges are installed on the concrete tower based measuring fore-aft and side-side strain (and can be converted to bending moments) – all acceleration and strain signals sampled at 200Hz. Temperature and humidity are measured at the tower base – 1Hz data. In additional we are collecting operational performance data (SCADA), namely: wind speed, nacelle yaw orientation, rotor RPM, power output and turbine status – SCADA signals are sampled at 10Hz. See appendix for further details of the sensors layout. The measurements/instrumentation setup, type and layout is provided in the pdf files. The data: the data is provided in zip files corresponding to four use-cases as follows: <ul> <li>Normal operation data for system identification</li> <li>Aerodynamic imbalance on one blade</li> <li>Rotor icing event</li> <li>Failure of the flexible coupling of the linear drive of the collective pitch system</li> </ul> The data for each of the four uses-cases is organized in zip files. The content of each zip file is as follows: <ul> <li>Time-series data in HDF5 format</li> <li>Metadata: <ul> <li>Turbine specification (Aventa-AV-7.json and Aventa-AV-7.yaml)</li> <li>Sensor specification (Aventa_sensors.json )</li> <li>Unstructured description of the Aventa Turbine and the installed sensors (Aventa_Sensors_Specs.xlsx)</li> </ul> </li> <li>Semantic artifacts: <ul> <li>WindIO Wind Turbine YAML schema describing turbine specifications (IEAontology_schema.yaml)</li> <li>Sensor specification JSON schema (sensors_schema.json)</li> </ul> </li> <li>Media: Pictures of leading edge roughness and a clip of wind turbine operation</li> <li>Code: Jupyter notebook containing example code to load metadata from JSON and data from HDF5 files (example.ipynb)</li> </ul> Additional data is available upon request, please contact: <ul> <li>Prof. Dr. Eleni Chatzi (chatzi@ibk.baug.ethz.ch)</li> <li>Dr. Imad Abdallah (ai@rtdt.ai , abdallah@ibk.baug.ethz.ch)</li> </ul> For further details or questions, please contact: Prof. Dr. Eleni Chatzi Chair of Structural Mechanics & Monitoring ETH Zürich <a href="http://www.chatzi.ibk.ethz.ch/">http://www.chatzi.ibk.ethz.ch/</a>

opencc-by-4.0Jul 2023View details →

Data and code associated with "Spatial wavefront shaping with a nanostructured metasurface for structured illumination microscopy"

Data and code associated with the manuscript "Spatial wavefront shaping with a nanostructured metasurface for structured illumination microscopy"

Data for: Grain structure evolution ahead of the die during friction extrusion of AA2024

Friction extrusion (FE) is a thermo-mechanical process using a rotating die to produce fully consolidated extrudates in different shapes, e.g. wires, rods and tubes. FE utilizes a non-consumable die to plastically deform material and to generate heat by friction due to the relative rotation between the die and feedstock. In this study, the FE process is applied to extrude the Al-Cu alloy AA2024 using a 90 degree scroll-featured die. The grain structure evolution induced by thermo-mechanical processing is analyzed, in particular using the electron backscatter diffraction technique. Introduction of severe plastic deformation and high temperature exposure induced by the die movement in radial and longitudinal directions relative to the materials enable grain refinement induced by dynamic recrystallization. The grain structure formation prior to deformation through the die orifice plays an essential role to obtain fully-recrystallized homogeneous wire.

opencc-by-4.0Sep 2023View details →

Diffraction data underpinning the structure of StayGold determined by X-ray crystallography (PDB code 8BXT)

Raw diffraction data underpinning the crystal structure of StayGold fluorescent protein. This is the raw data underpinning PDB entry 8BXT.

openCC (other)Jul 2017View details →

LAGOS-NE – Lake nutrient chemistry and geospatial data to measure spatial structure of ecosystem properties in a 17-state region of the U.S.

This dataset includes data for the lake water quality and geospatial variables that describe climate, hydrology, land use land cover, and lake characteristics that were used to study spatial structure in lake properties at the sub-continental scales (Lapierre et al. Quantifying spatial structure to improve understanding of the relationships between climate, landscape, and lake ecosystem properties, to be submitted to Ecology). All observations came from LAGOS-NELIMNO v. 1.054.1 and LAGOS-NEGEO v. 1.03 (LAke multi-scaled GeOSpatial and temporal database), an integrated database of lake ecosystems (Soranno et al. 2015). LAGOS-NE contains a complete census of lakes great than or equal to 4 ha with corresponding geospatial information for a 17-state region of the U.S., and a subset of the lakes has observational data on morphometry and chemistry. Approximately 54 different sources of data were compiled for the LAGOS-NELIMNO v. 1.054.1 dataset and were mostly generated by government agencies (state, federal, tribal) and universities. In this analysis, we compiled lake water quality data from the summer stratified season (June 15-September 15) in the most recent 10 years of data included in LAGOS-NELIMNO v. 1.054.1 (2002-2011). We report the median total nitrogen, total phosphorus, secchi depth, and chlorophyll values for each lake, which was calculated as the grand median of each yearly median value. We also include data for lake and landscape characteristics including variables related to lake morphometry, climate, hydrology, atmospheric deposition, land use and land cover.

Alaskan Peatland Experiment: Community structure and productivity data for 2007-2010 I - Species List

This dataset lists all vascular plants present at the Alaska Peatland Experiment identified as of fall 2010. Non vascular plant growth forms are also included, as well as the relative location for each species or growth form. Data can be sorted by species, growth form or location. Two peatland types are represented; a bog and a fen . Within the fen site a water table manipulation has been ongiong since 2005, with control, lowered and raised water table treatment plots. At the bog there is a plot established within the lowland black spruce permafrost plateau, and two plots established within collapse scars embedded within the plateau. One collapse scar formed ~ 45 years ago (old collapse) and the other formed ~ 25 years ago based upon aerial photography provided by the BCEF LTER.

Alaskan Peatland Experiment: Community structure and productivity data for 2007-2010 II - Species Abundance

This dataset contains abundance for vascular and non vascular plants at the Alaska Peatland Experiment in 2007 and 2009. Two peatland types are included, a bog site and a fen site. Within the fen site a water table manipulation has been ongiong since 2005, with control, lowered and raised water table treatment plots. Measurements collected in 2007 included quadrats passively warmed using open top chamebr (OTC), although these quadrats were not measured in 2009. Data at the bog was measured in 2009, and plots include an area established within the lowland black spruce permafrost plateau (permafrost), and two plots established within collapse scars embedded within the plateau. One collapse scar formed ~ 45 years ago (old collapse) and the other formed ~ 25 years ago based upon aerial photography provided by the BCEF LTER. The data provided in this data set can be sorted by year, site and plot, in addition to warming treatment.

Alaskan Peatland Experiment: Community structure and productivity data for 2007-2010 III - Understory Biomass

This dataset contains understory aboveground biomass data from a destructive harvest performed in 2009 at the Alaskan peatland experiment. Two peatland types are included, a bog site and a fen site. Within the fen site a water table manipulation has been ongiong since 2005, with control, lowered and raised water table treatment plots. Samples at the bog were collected in a plot established within the lowland black spruce permafrost plateau (permafrost), and two plots established within collapse scars embedded within the plateau. One collapse scar formed ~ 45 years ago (old collapse) and the other formed ~ 25 years ago based upon aerial photography provided by the BCEF LTER. The data provided in this data set can be sorted by site and plot.

Alaskan Peatland Experiment: Community structure and productivity data for 2007-2010 IV - Understory Vascular ANPP

This dataset contains net primary productivity (NPP, g/m2/yr) measurements for understory vascular components of the plant community collected at peak biomass in the summer of 2009 at the Alaskan peatland experiment. Two peatland types are included, a bog site and a fen site. Within the fen site a water table manipulation has been ongiong since 2005, with control, lowered and raised water table treatment plots. Samples at the bog were collected in a plot established within the lowland black spruce permafrost plateau (permafrost), and two plots established within collapse scars embedded within the plateau. One collapse scar formed ~ 45 years ago (old collapse) and the other formed ~ 25 years ago based upon aerial photography provided by the BCEF LTER. The data provided in this data set can be sorted by site and plot.

Alaskan Peatland Experiment: Community structure and productivity data for 2007-2010 V - Moss NPP

This dataset contains net primary productivity (NPP, g/m2/yr) for sphagnum, feather moss, brown moss and dicranum moss types estimated for 2009 and 2010 at both bog and fen sites of the Alaskan peatland experiment. Within the fen site a water table manipulation has been ongiong since 2005, with control, lowered and raised water table treatment plots. Samples at the bog were collected in a plot established within the lowland black spruce permafrost plateau (permafrost), and two plots established within collapse scars embedded within the plateau. One collapse scar formed ~ 45 years ago (old collapse) and the other formed ~ 25 years ago based upon aerial photography provided by the BCEF LTER. The data provided in this data set can be sorted by site and plot.

Alaskan Peatland Experiment: Community structure and productivity data for 2007-2010 VI - Tree Biomass and NPP

This dataset contains both tree biomass and net primary productivity for Picea mariana (living and standing dead) within the bog of the Alaskan Peatland Experiment as measured in the fall of 2010. Plot within the bog include a plot established within the lowland black spruce permafrost plateau (permafrost), and two plots established within collapse scars embedded within the plateau. One collapse scar formed ~ 45 years ago (old collapse) and the other formed ~ 25 years ago based upon aerial photography provided by the BCEF LTER. The data provided in this data set can be sorted by site and plot.