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Dataset results
6 results for “Storage building”
Dataset of multi-objective optimization results for a new latent energy storage approach in buildings based on several phase change materials with different melting temperatures
<p>This dataset comprises the multi-objective optimization results obtained for a new latent energy storage approach based on several phase change materials (PCMs) with different melting temperatures in buildings. The results were obtained for a small office building in eight climate-representative locations according to the ASHRAE 169-2020 climate classification and within the WMO Region VI (Europe).</p> <p>The dataset contains:</p> <p>- The EnergyPlus baseline models employed as a case study for each climate.</p> <p>- The Pareto fronts obtained after the multi-objective optimization in each climate.</p> <p>- The EnergyPlus models for the best designs achieved on the Pareto fronts in terms of annual total load reductions.</p>
Low-energy Museum Storage Buildings: Climate, Energy Consumption and Air Quality. Data Set for Final Data Report
<p>The 43 txt-files included in this dataset relate to the report: Ryhl-Svendsen, Jensen, Bøhm, and Klenz Larsen (2012): <em>Low-energy Museum Storage Buildings: Climate, Energy Consumption and Air Quality. UMTS Research Project 2007</em>–<em>2011: Final Data Report</em>, Kgs. Lyngby: National Museum of Denmark, 122 pp.</p> <p>The document <a href="https://zenodo.org/api/files/145584b0-46b5-4341-8b02-7dfea90fa97c/00_List-of-data-files.pdf?versionId=a3e9691f-6e73-4a7b-aaab-c8ccee7c419b">00_List-of-data-files.pdf</a> contain a full list of the data files with a description of their structure and content, and is the key to how the individual data files relate to the report. </p> <p>The research project focussed on four modern museum storage facilities in Denmark, for which the indoor climate, air quality, and the energy consumption of the climate control systems was measured at several locations, typically for a period of between two and four years. The storage facilities were Museum of Southwest Jutland’s storage building in Ribe (‘Ribe’), The Shared Storage Facility at The Centre for Preservation of Cultural Heritage in Vejle (‘Vejle’), The Joint Storage Facility for museums in East Jutland/ Museum Østjylland (‘Randers’), and from The National Museum of Denmark the storage building Hall P at the Ørholm Storage Facility (‘Ørholm’). For description of the sites, monitoring campaigns, and graphed data, the report should be consulted.</p> <p>For completeness, the report is included with the dataset (<a href="https://zenodo.org/api/files/145584b0-46b5-4341-8b02-7dfea90fa97c/Report_low-energy-museum-storage-buildings.pdf?versionId=44097d39-775b-4031-9e07-6978c68912a9">Report_low-energy-museum-storage-buildings.pdf</a>).</p>
The carbon dioxide storage potential of building materials: a systematic literature review - Supplementary material
<p>Supplementary Material of the Study "The carbon dioxide storage potential of building materials: a systematic literature review". The Paper will be published in the conference proceedings of CISBAT 2023, Lausanne, Switzerland from the 13-15 September 2023.</p>
Development of strategy for combined smart ventilated window and PCM energy storage control for residential building energy saving
<p>The dataset includes the published data in the article Development of strategy for combined smart ventilated window and PCM energy storage control for residential building energy saving. For the details of the data description please refer to the paper.</p>
Techno-Economic Analysis of Battery Electricity Storage Towards Self-Sufficient Buildings.
<p>These data represent the energy demand of a building designed following the “Directive of the European Parliament on the energy performance of building” (2010/31/EU ) and that meets the “Casaclima” energy certificate. It belongs to the CasaClima A energy class (Class A for what concerns the envelope efficiency, Gold Class for what concerns the overall energy efficiency).</p> <p>Hourly electrical and thermal consumption are presented for a year for 5 different climatic conditions according to the IEA classification.</p> <p>Consumption has been modeled through Energy Plus and validated against measured data. Please refer to <a href="https://doi.org/10.1016/j.enconman.2022.115313">https://doi.org/10.1016/j.enconman.2022.115313</a> for the methodology description.</p> <p>Pleas acknowledge <a href="https://doi.org/10.1016/j.enconman.2022.115313">https://doi.org/10.1016/j.enconman.2022.115313</a> when using the data set.</p>
Supplementary materials: Environmental conditions for Danish storage buildings, reviewing 20 years of air quality surveys
<p>S1: Extended information on sites</p> <p>S2: Origin of data, list of previous studies</p> <p>S3: Method: technical details and suppliers list</p> <p>S4: Temperature, RH, TWPI and energy consumption</p> <p>S5: Formic and acetic acid concentration, summer and winter</p> <p>S6: Ozone and nitrogen dioxide measurements, and air exchange rates</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)
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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.