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841 results for “vibrations”
Ambient vibration test of wind turbine blade in OWI-lab's Large Climate Chamber
<p><strong>Ambient vibration test of wind turbine of wind turbine blade in OWI-lab's Large Climate Chamber</strong></p> <p>Selected data from the large scale icing experiment as conducted in OWI-lab's large climate chamber on 15/11/2022. Results were presented during Eurodyn 2023 in :"Large scale test of vibration based icing detection for wind turbines", Weijtjens et.al. </p> <p><em>Data is (summarized, more details are given below):</em></p> <p>- 24 Ten minute acceleration data files collected (MO04_acceleration_YYYYmmdd_HHMMSS.csv) <br> - Pictures during the experiment timestamped (local time: UTC+1)<br> - Temperature measurements of the climate chamber's inflow temperatures<br> - Modal parameter results for X and Z direction </p> <p>All times are in UTC unless mentioned otherwise.</p> <p><strong>Measurement concept</strong></p> <p>The measurement data is collected during an experiment as conducted as part of the <a href="https://www.sirris.be/nl/joint-project/fighting-icing">COOCK fighting icing </a> project led by Sirris. In the OWI-lab climate chamber a wind turbine blade was subjected to icing conditions. The test comprises the collection of ambient vibration data using three tri-axial accelerometers installed on the blade. During the day the blade is cooled and cold water is sprayed on the blade to simulate the growth of ice on the blade. The steps of the experiment are:</p> <pre><code>2022-11-15 10:04:00+00:00: Start cooling to -10°C 2022-11-15 11:23:00+00:00: Start spray 2022-11-15 12:13:00+00:00: Accelerate spray 2022-11-15 12:49:00+00:00: End of spray 2022-11-15 13:13:00+00:00: Start heating 2022-11-15 14:14:00+00:00: Start cooling to -10°C 2022-11-15 15:03:00+00:00: Start spray 2022-11-15 15:43:00+00:00: End of spray</code></pre> <p>For more information on the </p> <p><strong>Ten minute acceleration data</strong></p> <p>Twentyfour ten minute samples of the 3 accelerometers on the blade sampled at 250Hz. The data is two 2-hour blocks, one at night before the testing, the second 2 hour block is during the spraying.</p> <p>The 10.1m long blade was instrumented with three tri-axial MEMS accelerometers (Micromega IAC-UHRS-Ud-03, ±3g) on the suction side of the blade. In which the X-direction corresponded to the edgewise motion of the blade, the Z-direction to the flapwise direction and the Y-direction to the less relevant lengthwise motion. The three sensors were installed at approximately 1/4, 5/8 of the blade length and 130cm from the tip of the blade.</p> <p><strong>Modal parameter data</strong></p> <p>The resulting modal parameter data ( for the entire day of testing) , in both X and Z direction are provided in MO04_mpe_*_20221115.csv. The data has following shape:</p> <table> <thead> <tr> <th> </th> <th>mean_frequency</th> <th>std_frequency</th> <th>mean_damping</th> <th>std_damping</th> <th>size</th> <th>algorithm</th> <th>timestamp</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>1.649219</td> <td>0.001952</td> <td>1.128411</td> <td>0.103419</td> <td>51</td> <td>lscf</td> <td>2022-11-15 00:00:00+00:00</td> </tr> <tr> <th>1</th> <td>2.028879</td> <td>0.000927</td> <td>0.432596</td> <td>0.068354</td> <td>60</td> <td>lscf</td> <td>2022-11-15 00:00:00+00:00</td> </tr> <tr> <th>2</th> <td>2.923999</td> <td>0.009472</td> <td>2.677156</td> <td>0.615895</td> <td>19</td> <td>lscf</td> <td>2022-11-15 00:00:00+00:00</td> </tr> <tr> <th>3</th> <td>3.779268</td> <td>0.003649</td> <td>3.462347</td> <td>0.715628</td> <td>7</td> <td>lscf</td> <td>2022-11-15 00:00:00+00:00</td> </tr> <tr> <th>4</th> <td>5.786029</td> <td>0.005541</td> <td>0.539010</td> <td>0.261049</td> <td>7</td> <td>lscf</td> <td>2022-11-15 00:00:00+00:00</td> </tr> </tbody> </table> <p>In which `mean_frequency` and `std_frequency` are the cluster mean frequency, are the cluster std. frequency and cluster std. damping and the cluster size (size). The LCSF algorithm is used. The algorithm used is described in <a href="https://journals.sagepub.com/doi/abs/10.1177/1475921714556568?journalCode=shma">Source</a>.</p> <p>Note: multiple rows share one timestamp, this is because the algorithm can detect multiple modes per timestamp.</p> <p><strong>Temperature data</strong></p> <p>The inflow air temperatures are shared in a separate .csv files: ClimateChamber_20221115.csv</p> <p><strong>Pictures</strong></p> <p>Picture are collected during the test are shared. Each picture is timestamped in local time (UTC+1)</p> <p> </p>
GNSS data of ambient vibrations and artificial excitations of the Aaresteg bridge.
<p>GNSS Data:</p> <p>- Instrument: Java GrAnt-G3T antenna and Septentrio PolaRx receiver</p> <p>- sampling rate: 20 Hz</p> <p>- Bandwidth of loop filter: auto adjust</p> <p>- Date: 2021-09-27</p> <p>Location:</p> <p>Instrument was set up on the eastern railing of the Aaresteg bridge, 1.125 m height above the wooden planks. The bridge was excited by jumping, twisting, running, walking, impulse hammering and combinations thereof. </p>
Data and code associated with the paper 'Measurement-induced collective vibrational quantum coherence under spontaneous Raman scattering in a liquid'
<p>Data and code associated with the following paper <a href="https://doi.org/10.1038/s41467-023-38483-9">V. Vento, S. Tarrago-Velez et al., Nat. Commun. (2023)</a></p> <p>A thorough explanation of the experiment performed is available there.</p> <p>The name of each sub-folder and file in <strong>CS2_data_code.zip</strong> indicates the corresponding figure number ("FIG #") and the type of content ("Data", "Analysis" or "Model").</p> <p> </p>
Dataset associated with publication "Direct observation of coherence transfer and rotational-to-vibrational energy exchange in optically centrifuged CO2 super-rotors" to be published in Nature Communications
<p>This dataset contains all data to compose figures in the associated manuscript. Some of the images are presented in MatLab .mat files. If a different format is needed, please contact the corresponding author. </p>
Data for Transient 2D IR spectroscopy and multiscale simulations reveal vibrational couplings in the Cyanobacteriochrome Slr1393-g3
<p>Data used in the Manuscript Transient 2D IR spectroscopy and multiscale simulations reveal vibrational couplings in the Cyanobacteriochrome Slr1393-g3</p>
Optimization procedure of low frequency vibration energy harvester based on magnetic levitation: Datasets and scripts
<p>****** Please view the README.txt file for detailed documentation of data. ******</p> <p> </p> <p>Title: Optimization procedure of low frequency vibration energy harvester based on magnetic levitation: Datasets and scripts<br>Version: 2.0<br>Date of Release: 2023/08/23<br>Identifier: doi:10.5281/zenodo.8317223<br>Permalink: http://dx.doi.org/10.5281/zenodo.8317223</p> <p><br>Associated publication: I. Royo-Silvestre, J. J. Beato-López, C. Gómez-Polo "Optimization procedure of low frequency vibration energy harvester based on magnetic levitation", Applied Energy, Volume 360, 15 April 2024, 122778</p> <p>Link to publication: <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.apenergy.2024.122778" target="_blank" rel="noreferrer noopener"><span>https://doi.org/10.1016/j.apenergy.2024.122778</span></a></p> <p><br>Suggested citation: Please reference the associated publication above when using any datasets or materials described in the README file.</p> <p> </p> <p>Contact information: Isaac Royo Silvestre, Universidad Pública de Navarra, Pamplona, Spain., isaac.royo@unavarra.es<br>Co-authors: juanjesus.beato@unavarra.es, gpolo@unavarra.es</p> <p> </p> <p>Dates of data collection: 2023/03<br>Geographic location: Pamplona, Spain</p> <p> </p> <p>This directory contains the following datasets and scripts:</p> <p>SCRIPTS</p> <p>- harvester_op.m: Matlab script to automate the design and optimize a magnetic spring based vibration energy harvester (more information in the associated paper)</p> <p>- harvester_op_par.m: Matlab script, a version of harvester_op.m modified for parallel computing and shorter execution time in multicore computers (file added in v 2.0 of the data upload).</p> <p>DATASETS<br>- data.zip: Experimental data recorded by the datalogger as well as tabular data required to plot curves (compressed zip file) in csv format</p> <p> </p> <p>Specific documentation of each file is described in readme files.</p> <p> </p> <p>Refer to the original manuscript (see above) and the text of the Supplementary Materials published alongside this manuscript for additional information regarding the collection and generation of these data.</p>
Insights on the coupling between vibronically active molecular vibrations and lattice phonons in molecular nanomagnets
<p>Spin–lattice relaxation is a key open problem to understand the spin dynamics of single-molecule magnets and molecular spin qubits. While modelling the coupling between spin states and local vibrations allows to determine the more relevant molecular vibrations for spin relaxation, this is not sufficient to explain how energy is dissipated towards the thermal bath. Herein, we employ a simple and efficient model to examine the coupling of local vibrational modes with long-wavelength longitudinal and transverse phonons in the clock-like spin qubit [Ho(W<sub>5</sub>O<sub>18</sub>)<sub>2</sub>]<sup>9−</sup>. We find that in crystals of this polyoxometalate the vibrational mode previously found to be vibronically active at low temperature does not couple significantly to lattice phonons. This means that further intramolecular energy transfer <em>via</em> anharmonic vibrations is necessary for spin relaxation in this system. Finally, we discuss implications for the spin–phonon coupling of [Ho(W<sub>5</sub>O<sub>18</sub>)<sub>2</sub>]<sup>9−</sup> deposited on a MgO (001) substrate, offering a simple methodology that can be extrapolated to estimate the effects on spin relaxation of different surfaces, including 2D materials.</p>
Data from: Energy harvesting in a flow-induced vibrating flapper with biomimetic gaits
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Good vibrations: Remote-tactile foraging success of wading birds is positively affected by the water content of substrates they forage in
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Data from: Biomechanical properties of non-flight vibrations produced by bees
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Vibrating aggression: Spider males perform an unusual assessment strategy during contest displays
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Data and code from: Life under leaves: Substrate-borne vibrations provide a window into the behavior and ecology of two miniaturized geckos
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Intermolecular Vibrational Energy Transfer Enabled by Microcavity Strong Light-Matter Coupling
<p>The datasets are for the work by UCSD Xiong lab and Yuen lab, where light-matter strong coupling enables selective liquid-phase intermolecular energy transfer which is virtually absent in nature.</p>
Fine-Grained Activities of Daily Living Data with Structural Vibration and Electrical Load Sensing
<p>Fine-grained non-intrusive monitoring of activities of daily living (ADL) enables various smart building applications, including ADL pattern assessments for older adults at risk for loss of safety or independence. We utilize structural vibration sensing and electrical load sensing to acquire multiple fine-grained kitchen activities under a lab structure setting.</p> <p>Each file contains the following values:<br> -RawData: time series of data for each channel (vibration on the table, vibration on the floor, load)<br> -Label: manually fine-grained labels of events<br> -Table: detected events start/stop index for vibration sensor on the table<br> -Floor: detected events start/stop index for vibration sensor on the floor<br> -Load: detected events start/stop index for load sensor<br> <br> Label notation:<br> 1 -- operating the kettle<br> 2 -- kettle on<br> 3 -- operating the microwave<br> 4 -- microwave on<br> 5 -- put things on the stove<br> 6 -- operating with stove<br> 7 -- stove on<br> 8 -- operating vacuum<br> 9 -- sweep floor<br> 10 -- walking/step<br> 11 -- miscellaneous<br> 12 -- synchronization signal (knock on the floor)<br> 13 -- vacant<br> 14 -- microwave door open</p>
Data and Code from Pritchard & Vallejo-Marin (2020) "Floral vibrations by buzz-pollinating bees achieve higher frequency, velocity and acceleration than flight and defence vibrations"
<p>Data and Code from Pritchard & Vallejo-Marin (2020) "Floral vibrations by buzz-pollinating bees achieve higher frequency, velocity and acceleration than flight and defence vibrations" Journal of Experimental Biology. doi: 10.1242/jeb.220541</p>
Dataset and Data analysis "Multimodal vibrational studies of drug uptake in vitro: Is the whole greater than the sum of their parts?"
<p>Data Analysis for the publication 10.1002/jbio.202000264.</p> <p>It is divided in three different folders describing three different part of the data analysis:</p> <p><strong>A. DATA TREATMENT RAMAN (Folder 1)</strong></p> <p><em>1. Import data using the Import_Raman script.<br> 2. Plot Spectra and integrate DOX band<br> Figure 1A<br> Figure 1B<br> 3. PCA<br> Figure 1D<br> Figure 1C<br> SM 1<br> 4. PLS<br> Figure 1F<br> Figure 1E</em></p> <p><strong>B. ANALYSIS OF IR DATA AND MULTIMODAL IR-RAMAN OF DOX UPTAKE (Folder 2)</strong></p> <p><em>1 Load Data IR<br> 2 Exploratory Analysis IR<br> Figure 2A<br> 3 PCA <br> SM 2<br> 4. Partial Least Squares vs time<br> Figure 2C<br> Figure 2B<br> 5. Partial Least Squares vs Raman Signal<br> Figure 2E<br> Figure 2D<br> 6. Make Averages and clean up Data for DATA Fusion<br> IR<br> Raman<br> 7. 2DCORR<br> Figure 3B<br> 8. MCR_ALS WITH DATA FUSION<br> Fitting of the concentration of Raman using the method in [9].<br> MCR-ALS<br> Figures 4 A, B and C</em></p> <p> </p> <p><strong>C. SIMULATION (Folder 3)</strong></p> <p><em>1. Load Raman DATA<br> 2. Simulate Raman DAta<br> 3. Load and simulate IR Data<br> 4. 2D corr<br> Figure 3A</em></p> <p> </p> <p>. Each folder contains a .mlx with the data analysis performed. Figures numbering corresponds to the one found in the article.</p>
Data from: Entangling the vibrational modes of two massive ferromagnetic spheres using cavity magnomechanics
<p>Source data for Figures 2 and 3.</p>
Data Set "Benchmarking of Vibrational Exciton Models Against Quantum-Chemical Localized-Mode Calculations"
<p>This data set accompanies the publication "Benchmarking of Vibrational Exciton Models Against Quantum-Chemical Localized-Mode Calculations" <br>by Anna M. van Bodegraven, Kevin Focke, Mario Wolter, and Christoph R. Jacob <br>(TU Braunschweig, Germany) </p> <p>It contains the following files:</p> <p><br>Directory '01_AIM':</p> <p> - input (structure.pdb, topol.top and *_input.txt) and results (*.log and<br> Hamiltonian/AtomPos/Dipole/Parameters.txt) from frequency calculations<br> with the Amide-I-maps (AIM) program for six polypeptide test cases<br> (1gpB_310, ala_310, ala_hairpin, ala_helix, ala_strand, and trpzip), <br> each in vacuo or water with three different maps (Jansen, Skinner, <br> Tokmakoff) for 11 snapshots based on a MD run.<br> To rerun the calculations, you will have to change the paths in <br> the *_input.txt files (topfile, trjfile, sourcedir) accordingly<br> <br>Directory '02_SNF':</p> <p> - results (*.dat, *.out, coord and control) from frequency calculations <br> using Turbomole, SNF, and LocVib for six polypeptide test cases<br> (1gpB_310, ala_310, ala_hairpin, ala_helix, ala_strand, and trpzip) <br> each in vacuo or water for snapshots based on an MD run.<br> <br>Directory '03_NMA':</p> <p> - coordinates and results from pyADF for NMA molecules each alligned <br> with a peptide bond from the six polypeptide test cases<br> (1gpB_310, ala_310, ala_hairpin, ala_helix, ala_strand, and trpzip) <br> each in water for 11 snapshots based on a MD run and input <br> (*_input.txt) and results (*.log and Hamiltonian/AtomPos/Dipole/Parameters.txt) <br> from calculations with the Amide-I-maps (AIM) program<br> <br>Directory '04_Handling_Data':</p> <p> - contains all used notebooks to extract the data, plot the figures <br> and calculate the errors<br> - RMSD_Error_vacuo/water.ipynb is used to calculate the overall shifts <br> and generates a map-dependent mean value to shift the frequencies of AIM<br> - Frequencies.ipynb and Couplings.ipynb are used to plot the figures <br> - RMSD_values_vacuo/water.ipynb show the calculations for the statistical <br> analysis<br> To use the notebooks, start with the Dictionary_setup_for_data_for_paper.ipynb <br> to set up the main dictionary from the calculated data</p>
Ultrafast Vibrational Control of Organohalide Perovskite Optoelectronic Devices Using Vibrationally Promoted Electronic Resonance
<p>2D PC/PL-VIPER Maps, and results of molecular dynamics simulations for the above titled paper</p>
Supporting Data for: A Multimer Embedding Approach for Molecular Crystals up to Harmonic Vibrational Properties
<p>Accurate calculations of molecular crystals are crucial for drug design and crystal engineering. However, periodic high-level density functional calculations using hybrid functionals are often prohibitively expensive for relevant systems. These expensive periodic calculations can be circumvented by the usage of embedding methods in which for instance the periodic calculation is only performed at a lower-cost level and then monomer energies and dimer interactions are replaced by those of the higher-level method. Herein, we extend upon such a multimer embedding approach to enable energy corrections for trimer interactions and the calculation of harmonic vibrational properties up to the dimer level. We evaluate this approach for the X23 benchmark set of molecular crystals by approximating a periodic hybrid density functional (PBE0+MBD) by embedding multimers into less expensive calculations using a generalized-gradient approximation (GGA) functional (PBE+MBD). We show that trimer interactions are crucial for accurately approximating lattice energies within 1 kJ/mol and might also be needed for further improvement of lattice constants and hence cell volumes. Finally, vibrational properties are already very well captured at the monomer and dimer level, making it possible to approximate vibrational free energies at room temperature within 1 kJ/mol.</p><p>This supporting dataset includes results of PBE0+MBD, PBE+MBD, and multimer embedding calculations for the X23 set of molecular crystals. See the included README.md file for more details. The related preprint can be found at <a href="https://doi.org/10.48550/arXiv.2209.02687">https://doi.org/10.48550/arXiv.2209.02687</a>.</p>
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