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32 results for “Full-scale”
WILLOW - Norther: data set for the full-scale validation of model-based virtual sensing methods for an operational offshore wind turbine
<h1><em><strong>1. General description </strong></em></h1> <p>This data set contains as-build design information, as well as full-scale vibration response measurements from an operational offshore wind-turbine. The turbine is part of the Norther wind farm which is located in the Belgian North Sea<em> </em>and includes a total of 44 Vestas V164 (8.4MW) wind turbines on monopile foundations, see <a href="../api/records/11093262/draft/files/Fig1_Norther_locaction.png/content" target="_blank" rel="noopener noreferrer">Fig1_Norther_locaction.png</a>. This data set is intended to verify and validate model-based virtual sensing algorithms, using data as well as modeling information from a real turbine. </p> <h2><em><strong>1.1 Summary of the shared structural information</strong></em></h2> <p>The included information entails a detailed description of the geometric properties of the monopile and transition piece, distributed and lumped structural masses . All information shared in this record is conform the as-designed documentation. An example of the lumped masses considered in the model input files is presented in "<a href="../api/records/11093262/draft/files/Fig2_Sensor_Network.png/content" target="_blank" rel="noopener">Fig2_Sensor_Network.png"</a></p> <h2><em><strong>1.2 Summary of the shared geotechnical information</strong></em></h2> <p>Monopiles are distinguished by the significant role of soil-structure interaction. Ground reaction is most typically included in the structural model as non-linear p-y curves. Different p-y curves are available for a certain number of soils in the standards applicable to offshore structures (API RP 2GEO, 2011, and ISO 19901-4:2016(E), 2016).</p> <p>The required soil properties to define p-y curves according to the API framework are given in the soil profile provided in a separate Excel. Rather than symbols, the name of the soil properties is generally used as column header (e.g., <em>Undrained shear strength</em>). Therefore, it is straightforward to identify each soil parameter. The only soil parameter that might lead to confusion is:</p> <ul> <li><em>"epsilon50 [-]" </em>represents the vertical strain at half the maximum principal stress difference in a static undrained triaxial compression test on an undisturbed soil sample.</li> </ul> <p>It's worthy to note that estimates for the small shear strain stiffness, referred to as Gmax, are also included. Despite not being required as an input to define the API p-y curves, this parameter remains a key input for other soil reaction frameworks than the API (e.g., PISA). </p> <h2><em><strong>1.3 Summary of the shared measurement data</strong></em></h2> <p>Two sets of measurement data have been curated for validation purposes; the first interval has been collected during parked conditions, whereas the second interval has been collected during rated operational conditions. Both records have a length of 2 hours, and are subdivided into 10-minute data sets. Furthermore 1Hz SCADA data has been made available for the selected intervals. All different data sources are time synchronized and have been subjected to several internal quality checks. </p> <p>The sensor network on NRT-WTG is illustrated in in <strong>Fig. 2, </strong>whereas a description of the sensor types is presented in <strong>Tab.1.</strong> The acceleration sensors are installed in the horizontal plane, and measure tangential (Y) and orthogonal (X) to the wall, where the positive Y direction is pointing clockwise and the positive X direction is pointing inwards. All strain sensors are installed vertically and are located on the inside of the wall.</p> <table> <tbody> <tr> <td><strong>Data type </strong></td> <td><strong>Sensor type</strong></td> <td><strong>Fs (Hz)</strong></td> <td> <p><strong>Level mLAT (m)</strong></p> </td> <td><strong>Description </strong></td> </tr> <tr> <td>Acceleration (g) </td> <td>Piezo-electric acc. sensor (<strong>ACC</strong>)</td> <td>30</td> <td>15, 69, 97 </td> <td>3 Bi-directional accelerometers at different levels. LAT 15 installed at 240 degree heading; LAT 69 and 97 at 60 degree.</td> </tr> <tr> <td>Strain (micro strain)</td> <td>Resistive strain gauge (<strong>SG</strong>)</td> <td>30</td> <td>14</td> <td>6 SGs: equally spaced around the inner circumference of the can. Headings: 50, 110, 170, 230, 290, 350 degree.</td> </tr> <tr> <td>Strain (micro strain)</td> <td>Fiber-Bragg Grating strain gauge (<strong>FBG</strong>)</td> <td>100</td> <td>-17, -19</td> <td>2 FBGs per level at 165 and 255 degree respectively.</td> </tr> </tbody> </table> <p><strong>Table 1. Description of sensor types.</strong></p> <p>The FBG strain time series have been synchronized with the SG time series using using a cross-correlation based approach. Therefore the SG data has been used to genereate refrence strain time series at the headings of the FBG sensors; the FBG data is subsequently synchronized with regard to this reference time series. No synchronization of the acceleration data was needed, since these are collected using the same data aquisition system as the SG data. </p> <p>The SG strain time series have been calibrated and temperature compensated, whereas this is not the case for the FBG strain time series. The latter have a yet to be determined calibration offset. </p> <p>In conjunction to the sensor channels presented in <strong>Tab. 1</strong>, 1 Hz SCADA data is provided. A summary of the provided SCADA parameters, all sampled at 1Hz, is presented in <strong>Tab 2.</strong></p> <table> <tbody> <tr> <td><strong>Parameter</strong></td> <td><strong>Unit</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>Wind speed</td> <td>m/s</td> <td>Wind speed as recorded in the turbine SCADA</td> </tr> <tr> <td>Wind direction</td> <td>°</td> <td>Wind direction relative to North (0°) as recorded in the turbine SCADA</td> </tr> <tr> <td>Yaw angle</td> <td>°</td> <td>Yaw orientation of the nacelle relative to North (0°) as recorded in the turbine SCADA</td> </tr> <tr> <td>Pitch angle</td> <td>°</td> <td>Rotor blade pitch as recorded in the turbine SCADA</td> </tr> <tr> <td>Rotor speed</td> <td>rpm</td> <td>Rotor speed in rotations per minute as recorded in the turbine SCADA</td> </tr> <tr> <td>Power</td> <td>kW</td> <td>Active power of the turbine as recorded in the turbine SCADA</td> </tr> </tbody> </table> <p><strong>Table 2. </strong>List of provided SCADA parameters</p> <p> </p> <p>A summary of the selected intervals and relevant corresponding scada parameters is given in <strong>Tab 3</strong>.</p> <table> <tbody> <tr> <td><strong>Scenario </strong></td> <td><strong>T1 (UTC)</strong></td> <td><strong>T2 (UTC) </strong></td> <td><strong>Windspeed</strong></td> <td><strong>RPM </strong></td> <td><strong>Pitch </strong></td> </tr> <tr> <td>Parked</td> <td> <p>03/07 01:30</p> </td> <td> <p>03/07 03:30</p> </td> <td>< 4.5 m/s</td> <td>~1</td> <td>~18 °</td> </tr> <tr> <td>Rated</td> <td> <p>05/07 22:30</p> </td> <td> <p>06/07 00:30 </p> </td> <td>~15 m/s</td> <td>10.5</td> <td>8.1°</td> </tr> </tbody> </table> <p><strong>Table 3. </strong>Selected data intervals and relevant scada parameters</p> <p> </p> <h1><em><strong>2. Included in this version </strong></em></h1> <h2><em><strong>2.1 Version - 0.1.0</strong></em></h2> <ul> <li>Relevant Design information can be found in: <ul> <li>Geometry data for NRT-WTG: "WILLOW-Geometry_v4.xlsx"</li> <li>Best estimate soil profile: "WILLOW-BE_soil_profile.xlsx"</li> </ul> </li> <li>Acceleration, strain and scada data can be found in the following parquet files: <ul> <li>Measurement data for the parked case: "NRT-WTG_Parked.parquet.gz"</li> <li>Measurement data for the rated case: "NRT-WTG_Rated.parquet.gz"</li> </ul> </li> </ul> <p> </p> <h1><em><strong>3. Importing parquet files </strong></em></h1> <p>To import the measurement data into Python it is recommended to use pandas:</p> <pre>import pandas as pd<br># Read Parquet file with Pandas: relative_file_path = '<a href="../api/records/11093262/draft/files/NRT-WTG_Parked.parquet.gz/content" target="_blank" rel="noopener noreferrer">NRT-WTG_Parked.parquet.gz</a>' data = pd.read_parquet(relative_file_path ) <br><br>Once the dataframe has been imported, the users can process/re-arrange the raw data according the their needs; it should be noted that the imported dataframe contains NAN values - these are caused by the different sampling rates of the provided signals. </pre>
Local Governance in Ukraine during the full-scale Russian invasion. – Merged data from online surveys of local self-government authorities by the Congress of Local and Regional Authorities of the Council of Europe in 2022 and Kyiv School of Economics in 2024.
The dataset includes responses from two waves of online surveys targeting local self-government representatives in Ukraine, with a focus on crisis governance during the ongoing Russian war. The first wave was conducted from August 30 to September 20, 2022, by the Congress of Local and Regional Authorities of the Council of Europe, yielding 241 responses (16% of all Ukrainian local communities). The second wave was conducted by Kyiv School of Economics from January 1 to March 12, 2024, with 181 responses (14% of government-controlled municipalities). Data formats include CSV and SAV files, along with an XSL codebook for both waves. The merged dataset comprises 442 responses from small, medium, and large municipalities under varied security conditions, with a total file size of approximately 4 MB.
Data for :Nitrogen availability in digestates from full-scale biogas plants following soil application as affected by operation parameters and input feedstocks
<p>This archive contains data for the paper "Nitrogen availability in digestates from full-scale biogas plants following soil application as affected by operation parameters and input feedstocks". Obtained from a soil incubation experiment for 80 days.</p><p> </p>
High-Speed Video Recordings of Wheel-Rail Traction Enhancement Using a Full-Scale Testing Platform - Granular Material Candidates
<p>A database of 14 high-speed video recordings of rail-sanding process using a full-scale testing platform is provided in this data note. The videos are recorded for various case studies, namely different positioning of the sander nozzle aiming at the rail, nip, and wheel with various angles, and different materials used as rail-sand. The particle velocities can be extracted from these high-speed videos using particle image velocimetry software. The spread angle of the particles as they flow out of the nozzle can also be measured with the use of image processing software. The data extracted from these high-speed recording can be utilised for calibration, validation, and verification of experimental and numerical set-ups, as well as for training artificial intelligence models.</p>
Data for: Evaluation of a full-scale wastewater treatment plant with ozonation and different post-treatments using a broad range of in vitro and in vivo bioassays
<p>This repository contains research data linked to the following publication: Kienle, C., Werner, I., Fischer, S., Lüthi, C., Schifferli, A., Besselink, H., Langer, M., McArdell, C.S. and Vermeirssen, E.L.M. 2022. Evaluation of a full-scale wastewater treatment plant with ozonation and different post-treatments using a broad range of <em>in vitro</em> and <em>in vivo</em> bioassays. Water Research, 118084. https://doi.org/10.1016/j.watres.2022.118084</p> <p>Abstract: Micropollutants present in the effluent of wastewater treatment plants (WWTPs) after biological treatment are largely eliminated by effective advanced technologies such as ozonation. Discharge of contaminants into freshwater ecosystems can thus be minimized, while simultaneously protecting drinking water resources. However, ozonation can lead to reactive and potentially toxic transformation products. To remove these, the Swiss Federal Office for the Environment recommends additional "post-treatment" of ozonated WWTP effluent using sand filtration, but other treatments may be similarly effective. In this study, 48 h composite wastewater samples were collected before and after full-scale ozonation, and after post-treatments (full-scale sand filtration, pilot-scale fresh and pre-loaded granular activated carbon, and fixed and moving beds). Ecotoxicological tests were performed to quantify the changes in water quality following different treatment steps. These included standard <em>in vitro</em> bioassays for the detection of endocrine, genotoxic and mutagenic effects, as well as toxicity to green algae and bacteria, and flow-through <em>in vivo</em> bioassays using oligochaetes and early life stages of rainbow trout.</p> <p>Results show that ozonation reduced a number of ecotoxicological effects of biologically treated wastewater by 66 - 93 %: It improved growth and photosynthesis of green algae, decreased toxicity to luminescent bacteria, reduced concentrations of hormonally active contaminants and significantly changed expression of biomarker genes in rainbow trout liver. Bioassay results showed that ozonation did not produce problematic levels of reaction products overall. Small increases in toxicity observed in a few samples were reduced or eliminated by post-treatments. However, only relatively fresh granular activated carbon (analyzed at 13,000 - 20,000 bed volumes) significantly reduced effects additionally (by up to 66 %) compared to ozonation alone. Inhibition of algal photosynthesis, rainbow trout liver histopathology and biomarker gene expression proved to be sufficiently sensitive endpoints to detect the change in water quality achieved by post-treatment.</p>
High-Speed Video Recordings of Wheel-Rail Traction Enhancement Using a Full-Scale Testing Platform - Sander Position & Angle Aimed at Nip & Wheel
<p>A database of 5 high-speed video recordings of rail-sanding process using a full-scale testing platform is provided in this data note. The videos are recorded for various case studies, namely different positioning of the sander nozzle aiming at the rail, nip, and wheel with various angles, and different materials used as rail-sand. The particle velocities can be extracted from these high-speed videos using particle image velocimetry software. The spread angle of the particles as they flow out of the nozzle can also be measured with the use of image processing software. The data extracted from these high-speed recording can be utilised for calibration, validation, and verification of experimental and numerical set-ups, as well as for training artificial intelligence models.</p>
High-Speed Video Recordings of Wheel-Rail Traction Enhancement Using a Full-Scale Testing Platform - Sander Position & Angle Aimed at Rail
<p>A database of 4 high-speed video recordings of rail-sanding process using a full-scale testing platform is provided in this data note. The videos are recorded for various case studies, namely different positioning of the sander nozzle aiming at the rail, nip, and wheel with various angles, and different materials used as rail-sand. The particle velocities can be extracted from these high-speed videos using particle image velocimetry software. The spread angle of the particles as they flow out of the nozzle can also be measured with the use of image processing software. The data extracted from these high-speed recording can be utilised for calibration, validation, and verification of experimental and numerical set-ups, as well as for training artificial intelligence models.</p>
Dataset - Use of full-scale hybrid horizontal tubular photobioreactors to process agricultural runoff
<p>The data set attached consists of three excel files where the data from the article “<strong>Use of full-scale hybrid horizontal tubular photobioreactors to process agricultural runoff”</strong>, published in Biosystems Engineering (vol. 166, 4<sup>th</sup> January 2018, 138-149.), can be found.</p>
Sound pressure measurements and calculation of the cavitation volume for a full-scale 3500 TEU container vessel
<p>Supplementary material comprising measurement data and MATLAB code corresponding to the published research article.</p>
Distribution System Environmental and Sequencing Datasets for Assessing the Impacts of Lead Corrosion Control on the Microbial Ecology and Abundance of Drinking Water Associated Pathogens in a Full-Scale Drinking Water Distribution System
<p>The dataset of environmental parameters and sequence fastqs used to create figures and do analysis in the paper <strong>Assessing the Impacts of Lead Corrosion Control on the Microbial Ecology and Abundance of Drinking Water Associated Pathogens in a Full-Scale Drinking Water Distribution System </strong>submitted to Environmental Science & Technology</p>
Full-scale MBR coupled with PAC for the removal of 232 OMPs: operating conditions, conventional pollutants, concentration of OMPs, UHPLC-QTOF-MS analysis
<p>The spreadsheet contains data regarding the operation and performance of a full-scale MBR coupled with powdered activated carbon (PAC) added inside the reactor. This hybrid system is chosen to evaluate the removal of 232 organic micropollutants (OMPs) and the potential enhancement in the removal efficiencies with the addition of PAC at a concentration of 0.1 g/L and 0.2 g/L</p><ul><li>First worksheet contains minimum, maximum, and average concentrations of conventional pollutants (COD, BOD, SST, SSV, DOC, UV254, nitrogen compounds, phosphorous, <i>E. coli</i>) in the influent and effluent of the WWTP. Methodologies adopted are also reported.</li><li>Second worksheet reports the operating conditions of the full-scale MBR as well as information about the tubular UF membranes installed. Characteristics of the PAC purchased to perform the experiments regarding the removal of OMPs are also described.</li><li>Third worksheet reports minimum, maximum and average concentration of 232 OMPs in the influent and effluent during:<ol><li>The monitoring period considering only the MBR</li><li>The experimental periods where PAC is added and maintained at a concentration of 0.1g/L and 0.2g/L inside the MBR</li></ol></li><li>Fourth worksheet contains metadata regarding the UHPLC–QTOF–MS analysis performed to evaluate the occurrence of OMPs in the influent and effluent of the WWTP. Sampling, storage and sample preparation is described, followed to LC-ESI-tandem MS analysis. LOD and LOQ are reported.</li></ul>
Urban Stream Environmental and Sequencing Datasets for Exploring the Impacts of Full-Scale Distribution System Orthophosphate Corrosion Control Implementation on the Microbial Ecology of Hydrologically Connected Urban Streams
<p>The dataset of environmental parameters and sequence fastqs used to create figures and do analysis in the paper <strong>Exploring the Impacts of Full-Scale Distribution System Orthophosphate Corrosion Control Implementation on the Microbial Ecology of Hydrologically Connected Urban Streams </strong>submitted to Applied and Environmental Microbiology. </p>
Supplemental Material to Article "Validation of crack initiation model by means of cyclic full-scale blade test"
<p>This set supplements the figure data to the article "Validation of crack initiation model by means of cyclic full-scale blade test", DOI: <a href="https://doi.org/10.1088/1742-6596/2265/3/032045">https://doi.org/10.1088/1742-6596/2265/3/032045</a>.</p>
Thermal design and full-scale thermal response test on Energy Walls
<p>This folder contains a spreadsheet that includes the underlying data referred to the publication mentioned in the title.</p> <p>For each figure, the underlying data are listed in a dedicated sub-sheet.</p>
Permeable pavement hydraulic performance and clogging experiments using a full-scale urban drainage physical model
<p>This dataset contains the results from 15 tests conducted used a physical model in the Hydraulic Laboratory of the Centre for Technological Innovation in Construction and Civil Engineering (CITEEC) at the University of A Coruña (Spain) as part of the POREDRAIN project.</p> <p><br>The objective of the tests is to analyse the hydraulic performance of a porous asphalt layer of the PA-16 type and the impact of clogging on the hydrological behaviour and water quality of the effluent. The porous asphalt was used to retrofit an impervious concrete surface of a 36 m² full-scale street section physical model, which consist of a rainfall simulator placed over the street surface. The behaviour of the porous asphalt layer was assessed by adding surface sediment loads between simulated rainfall events. Stormwater flow discharges were collected from two gully pots and an outlet lateral channel. </p>
dataset for "GPU-enhanced DEM analysis of flow behaviour of irregularly shaped particles in a full-scale twin screw granulator"
<p>This dataset contains the numerical simulation data describing the conveying behaviour of shaped-particle systems. Detailed study on the conveying behaviour is presented in a journal paper entitled "GPU-enhanced DEM analysis of flow behaviour of irregularly shaped particles in a full-scale twin screw granulator". We provide all the essential data in a single excel file with the description below:</p> <p>Dataset 1- Average particle speed (Fig. 7a) and XYZ components (Fig. 7b) for: Sphere at t = 2.1 s, Cube at t = 2.85 s, Biluna at t = 3.1 s, HexP at t = 3.45 s. (Data of Fig. 7)</p> <p>Dataset 2 - XYZ coordinates of a typical particle trapped in the granulator. (Data of Fig. 9)</p> <p>Dataset 3 - Particle retention numbers for different shaped particles. (Data of Fig. 10).</p> <p>Dataset 4 - Average particle speeds for different shaped particles. (Data of Fig. 11).</p> <p>Dataset 5 - Average axial particle speeds for different shaped particles (Data of Fig. 12).</p> <p>Dataset 6 - Residence time distributions for various shaped particles. (Data of Fig. 13)</p> <p>Dataset 7 - Normalised residence time distributions for various shaped particles. (Data of Fig. 14)</p> <p>Dataset 8 - Mean residence time for various shaped particles. (Data of Fig. 15)</p> <p>Dataset 9 - The variance of RTD for different shaped particles. (Data of Fig. 16)</p> <p>Dataset 10 - Cumulative exit age distribution for various shaped particles. (Data of Fig. 17)</p> <p>Dataset 11 - Normalised cumulative exit age distribution for various shaped particles. (Data of Fig. 18)</p> <p>Dataset 12 - Evolution of the cumulative power consumption for various shaped particles. (Data of Fig.19)</p> <p>Dataset 13 - Power consumption distribution for various shaped particles. (Data of Fig.20)</p>
LiftWEC deliverable 3.6 - Part II: Dataset from numerical simulations of full-scale LiftWEC device using a high-fidelity RANS model
<p>This dataset contains the numerical simulation results for a full-scale LiftWEC device in regular and irregular wave conditions. The regular wave cases occur at static pitch and fixed rotational velocity. The parameters used for these cases are described in the corresponding *CaseParameters.csv file. These simulations were used to derive a first estimate of the maximum conversion efficiency of the rotor from wave power to shaft power. A detailed description of the employed numerical model and the case setup can be found in LiftWEC deliverable 3.6 Hydrodynamic Validation of Final Design, which was also uploaded to the LiftWEC community on zenodo. In accordance with the coordinate system definition used in the validation case, a relative phase angle of 270° degree corresponds to foil1 at 3 o'clock position while the wave crest passes over the rotor axis position. Rotation is clockwise, Rotor rotates in the direction of orbital wave particle velocities.</p> <p>The control reference case describes the first test case of a cyclorotor in irregular waves under active control of angular velocity and foil pitch. This case is also documented in deliverable D3.6. The case files can be used to recreate wave conditions and motion signal. The load-file can be used to validate the obtained tangential and radial forces on foil 1 as well as the total power output over time. More information on the control model can be found in the corresponding project deliverables D5.X.</p> <p>All loads given as values per unit span length (e.g. for forces [N/m]).</p>
Temperature measurements of full-scale wall element using Type K thermocouples to observe internal convection in loose-fill wood fiber insulation
<p>Internal convection of insulation materials is a phenomenon that occurs when a construction element is subjected to a temperature difference on either side of the element, as the temperature difference inside the insulation will facilitate an onset of air movement due to thermal buoyancy. This dataset represents the results of 11 unique experiments conducted at Aalborg University at the Department of the Built Environment, where a full-scale wall element insulated with loose-fill wood fiber insulation is investigated for internal convection. A large guarded hotbox is used to control the boundary conditions of either side of the wall element, to imitate a construction element subjected to external and internal boundary conditions, similar to a wall in a house. This dataset can be used to benchmark other insulation materials investigated at similar boundary conditions.</p> <p>The dataset is structured into steady-state experiments and dynamic experiments, where a total of 7 unique cases are conducted in steady-state conditions, and 4 unique cases are conducted in dynamic conditions. The dataset for the steady-state experiments is structured by the temperature difference that the full-scale wall element is exposed to, from the cold and hot side, while the dynamic experiments are structured by the amplitude of the temperature variation, along with if an artificial sun is used or not.</p> <p>The results for the internal convection of the loose-fill wood fiber insulation show similar results as other studies that have conducted experiments on other insulation materials.</p> <p>For more information, see doi: 10.54337/aau488363266</p>
SPIN Self-Management Feasibility Trial With Progression to Full-scale Trial (SPIN-SELF)
ClinicalTrials.gov study NCT04246528. IPD Sharing: YES. Countries: 1. Publications: 1.
Full-scale Intervention Study: Genetic Risk Communication and Wearables
ClinicalTrials.gov study NCT05524909. IPD Sharing: YES. Countries: 1. Publications: 2.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.