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419 results for “offshoring”
Fig. A5 in Trace metal concentrations in the offshore surficial sediments of Heraklion Gulf (Crete Island, East Mediterranean Sea) Abstract
Fig. A5: Total Cu, Pb and Zn and nlhZn per transect [transects are presented from west to east, (•) the outlier value symbol and numbers refer to the isobaths].
Fig. A2 in Trace metal concentrations in the offshore surficial sediments of Heraklion Gulf (Crete Island, East Mediterranean Sea) Abstract
Fig. A2: Al and Fe (total, nlh and %nlh) per transect [transects are presented from west to east, (•)the outlier value symbol and numbers refer to the isobaths].
Fig. 8 in Trace metal concentrations in the offshore surficial sediments of Heraklion Gulf (Crete Island, East Mediterranean Sea) Abstract
Fig. 8: Map showing the sampling stations in 1989 (referred by Poulos et al., 2009) (·) and those of the present investigation (x) over the bathymetry.
Fig. 7 in Trace metal concentrations in the offshore surficial sediments of Heraklion Gulf (Crete Island, East Mediterranean Sea) Abstract
Fig. 7: Spatial distribution of non-lattice held (nlh) metals in surficial seabed sediments (a: Fe; b: Zn; c: Mn; d: Cr).
Fig. 6 in Trace metal concentrations in the offshore surficial sediments of Heraklion Gulf (Crete Island, East Mediterranean Sea) Abstract
Fig. 6: Spatial distribution of total metal content in sediments (Al distribution is not presented, as it is similar to Fe) [a: Fe; b: Zn; c: Pb; d: Mn; e: Cu; f: Cr].
Fig. 5 in Trace metal concentrations in the offshore surficial sediments of Heraklion Gulf (Crete Island, East Mediterranean Sea) Abstract
Fig. 5: (a): Carbonate content box plots grouped by percent silt+clay, b) Carbonate content box plots per transect (west to east) [(•) outlier value symbol, (*) extreme value symbol, numbers refer to the isobaths].
Fig. 4 in Trace metal concentrations in the offshore surficial sediments of Heraklion Gulf (Crete Island, East Mediterranean Sea) Abstract
Fig. 4(a): Particulate Organic Carbon (POC) values box-plot grouped by percent silt+clay; (b): Particulate Organic Carbon (POC) values box-plot per transect (from west to east) [(•) outlier value symbol, numbers refer to the isobaths].
Fig. 3 in Trace metal concentrations in the offshore surficial sediments of Heraklion Gulf (Crete Island, East Mediterranean Sea) Abstract
Fig. 3: Texture map based on grain size analysis according to Folk 1974. [gmS: gravelly muddy Sand; S: Sand; zS: silty Sand; sZ: sandy Silt; Z:Silt; C: Clay; M: Mud (=silt+clay) and hc: closure depth in red].
Fig. 2 in Trace metal concentrations in the offshore surficial sediments of Heraklion Gulf (Crete Island, East Mediterranean Sea) Abstract
Fig. 2: Determination of the offshore zone (blue zone) by means of L/4 (according to Komar, 1976) for approaching waves of different wave lengths (L). Closure depth limit (hc) is also presented (12 m isobath).
Fig. 1 in Trace metal concentrations in the offshore surficial sediments of Heraklion Gulf (Crete Island, East Mediterranean Sea) Abstract
Fig. 1: Location map showing the bathymetry (in metres), sampling stations (1-55), river/torrent mouths (from west to east: a-Almiros, b-Gazanos, c-Xiropotamos, d-Giofyros, e- Krateros, f-Vathilagkos, g-Gournianos, h-Gouvianos, i-Aposelemis, j-Sfakoryako) and the most important potential terrestrial sources of pollution (1: oil storages; 2: Electric Power Station; 3: outfall of treated waste water; 4: former outfall of untreated waste water; and 5: former Gouves military base).
Fig. 9 in Fibrocapsa japonica (Raphidophyceae) occurrence and ecological features within the phytoplankton assemblage of a cyclonic eddy, offshore the Eastern Alboran Sea
Fig. 9: A) A projection of the variables onto the factor plane, where the x-axis is PC1 and the y-axis is PC2, and B) a projection of the cases onto the factor plane, where the x-axis is PC1 and the y-axis is PC2. MAW is Modified Atlantic Water; AMI is the Atlantic Mediterranean Interface; LIW is Levantine Intermediate Water.
Fig. 6 in Fibrocapsa japonica (Raphidophyceae) occurrence and ecological features within the phytoplankton assemblage of a cyclonic eddy, offshore the Eastern Alboran Sea
Fig. 6: Pictures of F. japonica with A) and B) discharged mucous threads and the rod-shaped posterior mucocysts (indicated by the arrows) clearly visible, and C) a vegetative raspberry-like cell (top right) and two pre-cysts (indicated by the arrows). Cell diameter was generally 15-30 μm.
Fig. 5 in Fibrocapsa japonica (Raphidophyceae) occurrence and ecological features within the phytoplankton assemblage of a cyclonic eddy, offshore the Eastern Alboran Sea
Fig. 5: A) Total chlorophyll a concentration (chlorophyll a + divinyl-chlorophyll a, mg m-3) and B) Fibrocapsa japonica cell number map (x 103 cells l-1) overlapped to the isohalines (bold lines) as in Fig. 4.
Fig. 8 in Fibrocapsa japonica (Raphidophyceae) occurrence and ecological features within the phytoplankton assemblage of a cyclonic eddy, offshore the Eastern Alboran Sea
Fig. 8: A) Bacillariophyceae, and B) Prymnesiophyceae cell number map (x 103 cells l-1) overlapped to isohalines (bold lines) as in Fig. 4.
Fig. 4 in Fibrocapsa japonica (Raphidophyceae) occurrence and ecological features within the phytoplankton assemblage of a cyclonic eddy, offshore the Eastern Alboran Sea
Fig. 4: Seawater inorganic nitrogen concentration (nitrates + nitrites, μM) overlapped to the 37.0 and 37.5-isohaline (bold lines).
Fig. 3 in Fibrocapsa japonica (Raphidophyceae) occurrence and ecological features within the phytoplankton assemblage of a cyclonic eddy, offshore the Eastern Alboran Sea
Fig. 3: SeaWiFS map of surface chlorophyll a distribution in the Western Mediterranean Sea at the time of sampling: the circle encloses the cyclonic eddy. Data are integrated on 8 days (8th-15th October 2006), web source: http://reason.gsfc.nasa.gov/Giovanni.
Fig. 1 in Fibrocapsa japonica (Raphidophyceae) occurrence and ecological features within the phytoplankton assemblage of a cyclonic eddy, offshore the Eastern Alboran Sea
Fig. 1: Map showing the sampling locations in the Western Mediterranean Sea. Full symbols indicate the stations extensively analysed in the present study: M15-M19 and A1-A6. The window on top shows typical patterns of circulation of Modified Atlantic Water (MAW) in the Western Mediterranean Sea: continuous lines indicate steady paths and dashed lines outline the mesoscale currents throughout the year (modified from Millot, 1999).
Validated onshore and offshore time series for European countries (1979-2017)
<p>This repository comprises hourly time series representing the onshore and offshore wind capacity factors in every European country (EU-28 except the islands Malta and Cyprus plus Norway and Switzerland) from 1979 to 2017. The term capacity factor is defined as the ratio between the delivered power and the cumulative installed capacity. 3 letter codes (ISO-3166-3) are used to identify the countries.</p> <p>For every country, onshore wind time series are included. For some of the countries, offshore wind time series are also included. In both cases, the time series include data for the period 1979-2017. However, for every year, the installed capacity layout is kept fixed and corresponds to turbines running in 2015. By doing so the time series for different years represent the weather influenced on the wind generation and are not impacted by differences in installed capacities.</p> <p>To obtain onshore and offshore wind time series, wind velocity from Climate Forecast System Reanalysis (CFSR) dataset has been converted into electricity generation and aggregated at country level. The methodology was described in detail and validated for Denmark in <a href="https://www.sciencedirect.com/science/article/pii/S0360544215012815">Andresen <em>et al</em>., Energy 93 (2015)</a>. In the text annexed to the data files, a description of the data and parameters used to bias-correct the modelled time series for every European country is provided.</p> <p>The license for the AU REatlas wind time series dataset is: <a href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International (CC BY 4.0)</a></p> <p>When using this data please make sure you include the following citation:</p> <p><em>M. Victoria and Gorm B. Andresen, Validated onshore and offshore time series for European countries (1979-2017), RE-INVEST project (2019) </em></p> <p>More information can be requested from M. Victoria (<a href="mailto:mvp@eng.au.dk">mvp@eng.au.dk</a>) and Gorm B. Andresen (<a href="mailto:gba@eng.au.dk">gba@eng.au.dk</a>).</p> <p>These time series were generated in the framework of <a href="https://reinvestproject.eu/">RE-INVEST project</a>. A similar dataset comprising solar photovoltaic time series at national scale can be accessed through the zenodo repository <a href="https://zenodo.org/record/2613651#.XPZ00mNS8uU">10.5281/zenodo.1321809</a> and details can be found in <a href="https://onlinelibrary.wiley.com/doi/full/10.1002/pip.3126">Victoria and Andresen, Prog. In Phot.: Res and App. (2019) </a> </p> <p> </p> <p> </p>
SparBOFWEC Spar Buoy for Offshore Floating Wind Energy Conversion - Data Storage Report
<p>The present work describes the experiences gained from the design methodology and operation of a 3D physical model experiment aimed to investigate the dynamic behaviour of a spar buoy (SB) off-shore floating wind turbine (WT) under different wind and wave conditions. The physical model tests have been performed at Danish Hydraulic Institute (DHI) off-shore wave basin within the European Union-Hydralab+ Initiative, in April 2019. The floating WT model has been subjected to a combination of regular and irregular wave attacks and wind loads.</p>
Offshore wind turbine damage probability maps and hub height TC wind speeds for U.S. Atlantic and Gulf Coasts exposed to historical and future tropical cyclones
<p>Damage probability maps for offshore wind turbines exposed to tropical cyclones (TCs) under both historical and future climate scenarios along the U.S. Atlantic and Gulf Coasts are presented in this dataset. TCs are generated using <a href="../records/10392725" target="_blank" rel="noopener">The Risk Analysis Framework for Tropical Cyclones (RAFT)</a>, forced by <a href="https://pcmdi.llnl.gov/CMIP6/" target="_blank" rel="noopener">CMIP6</a> historical and future global climate simulations. Maximum wind speeds for 20- and 50-year TCs are processed through a <a href="https://www.sciencedirect.com/science/article/pii/S0960148120311423">fragility function</a> specific to offshore wind (OSW) turbines in order to estimate the probability of damage – specifically yielding and buckling – based on wind speed intensity. </p> <p><strong>Included data:</strong></p> <ul> <li><strong>TC wind speeds:</strong> Peak 10-min mean hub height (90m) TC wind speed maps</li> <li><strong>Damage states:</strong> Yielding and Buckling probability maps for OSW turbines</li> <li><strong>Geographic coverage:</strong> U.S. Atlantic and Gulf Coasts (up to 200km from the shoreline)</li> <li><strong>Time periods:</strong> Historic (1980-2014) and Future (2066-2100)</li> </ul> <p><strong>Methodology:</strong></p> <ul> <li><strong>Tropical cyclone simulation:</strong> The RAFT TC model is used to simulate storms for historical and future climates using CMIP6 environmental conditions.</li> <li><strong>TC impact metric:</strong> Wind speeds associated with 20- and 50-year return period TCs are used to estimate the aerodynamic and sea wave loading on OSW turbines.</li> <li><strong>Fragility functions:</strong> Wind speeds are input into a fragility function developed for OSW turbines, estimating the probability of yielding and buckling damage.</li> <li><strong>Damage probability maps:</strong> The results consist of eight (8) gridded damage probability maps representing the likelihoods of yielding and buckling to OSW turbines from 20- and 50-year TCs under historical and future climatic conditions.</li> </ul> <p><strong>Potential Uses:</strong></p> <ul> <li>Assessing the spatial vulnerability of OSW infrastructure to TCs</li> <li>Supporting decision-making for the design and siting of turbines</li> <li>Evaluating the impact of climate change on the risk of damage to OSW infrastructure</li> </ul> <p>For further insights into this dataset, users are encouraged to refer to the associated paper: <a href="https://www.nature.com/articles/s43247-024-01887-6">https://www.nature.com/articles/s43247-024-01887-6</a></p> <p>This dataset offers valuable insights into the potential impact of TCs on offshore wind infrastructure, aiding in risk assessment and resilience planning for the renewable energy sector.</p> <p> </p>
ScienceDex guides
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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.