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ShareScore release 0.9.0
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9 results for “waste heat”
Replication data for: Operating Strategies of an Industrial R717 Heat Pump Recovering Waste Heat of a Chiller
<p>This dataset contains the data of the publication:<br> Verdnik, M., Wagner, P., Rieberer, R., 2022. Operating Strategies of an Industrial R717 Heat Pump Recovering Waste Heat of a Chiller. Proc. International Congress of Refrigeration 2023, Paris, France</p>
Supplementary file to "Effect of heat treatment on microbiological safety of supermarket food waste as substrate for black soldier fly larvae (Hermetia illucens)"
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Regression Model to Predict the Higher Heating Value of Poultry Waste from Proximate Analysis.
<p>The response variable is High Heating Values (HHV), while the independent variables are Fixed Carbon (FC), Volatile Matter (VM), and Ash (A). </p>
Simulation data DC Waste Heat Reuse - Multiple DCs connected to river water / ATES system
<p>CATALYST D7.5 report - SBP-DC-TC-7 - Scenario 7</p> <p>Compilation of simulation result data on DC waste heat reuse for a DC chain, connected to river water / ATES free cooling system.</p> <p>Scenario 7: Workload federated DCs - DC Waste Heat Reuse - EleENGctrical Flexibility - IT Load Migration</p>
GEOS-Chem 2015 Speciated PM2.5 Outputs for "Impact of circular- and single-sector waste-heat reuse pathways on PM2.5-air quality, CO2 emissions, and human health in India; material exchanges more viable to achieve sustainability targets"
<p>Daily PM2.5 and species outputs from GEOS-Chem Modeling over India (0.5° x 0.625°) </p>
An efficient method for higher heating value estimation of municipal solid wastes electronic supplementary material
<p><span><span>To facilitate the disposal of municipal solid wastes (MSWs) via thermo-chemical approaches, the accurate measurement of MSWs' higher heating value (HHV) plays a key role. This study aims to forecast the HHV of MSWs using the optimized multi-variate grey model (OBGM (1, N)) due to its high accuracy under the condition of scanty data. Results show that POBGM (1, 5) with proximate analysis data is the most accurate model with the least error of 5.41% MAPE (mean absolute percentage error). This model also illustrates that ash is the most important factor affecting HHV due to its significant fraction in MSWs, followed by volatiles, fixed carbon and water contents, respectively. With prediction interval (PI) method, most of the actual data can be included by using the 95% confidence intervals.</span></span></p>
Ammonia recovery from food waste digestate using solar heat-assisted stripping-absorption
<p>The highest costs of stripping-absorption processes for ammonia recovery are related to energy (for heating and air supply) and chemical addition (for pH adjustment). In this paper, a simplified system that used no chemicals, and a renewable source of energy for heating, was tested to recover nitrogen as ammonium sulfate from food waste digestate. pH adjustment was achieved by CO<sub>2</sub> stripping, and vacuum tube solar collectors were used to provide heating. The effect of different temperatures (25 °C and 45 °C) and gas to liquid ratios (1700 and 2600) on ammonia removal and recovery were assessed. Ammonia removal efficiencies higher than 91% were achieved for all evaluated experimental conditions. The solar heater showed adequate capacity to increase the temperature of the liquid digestate by 21 °C and maintain the temperature at 45 °C throughout the experiment. Tests carried out at 45 °C achieved the highest ammonia removal efficiency (98%) at the lowest evaluated G/L ratio (1700). Better absorption efficiencies could potentially have been achieved if lower inlet airflow rates and packing material had been used in the absorption column.</p>
Output data from the optimization of an industrial waste heat recovery system
<p>Output data from the multi objective optimization of a ORC-District Heating recovery system for industrial waste heat exploitation</p> <p> </p>
An efficient method for higher heating value estimation of municipal solid wastes electronic supplementary material
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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.