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WaterTAP3 Model Input Data for NAWI's Eight Source Water Baseline Analyses

This folder contains the input data for the WaterTAP3 model that was used for the eight NAWI (National Alliance for Water Innovation) source water baselines studies published in the Environmental Science and Technology special issue: Technology Baselines and Innovation Priorities ...
Miara, A. et al National Renewable Energy Laboratory
Feb 01, 2022
16 Resources
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BUTTER Empirical Deep Learning Dataset

The BUTTER Empirical Deep Learning Dataset represents an empirical study of the deep learning phenomena on dense fully connected networks, scanning across thirteen datasets, eight network shapes, fourteen depths, twenty-three network sizes (number of trainable parameters), four le...
Tripp, C. et al National Renewable Energy Laboratory
May 20, 2022
4 Resources
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WaterTAP3 Model Results for NAWI's Baseline Analyses

This dataset contains the results for the WaterTAP3 model that was used for the eight NAWI (National Alliance for Water Innovation) baseline studies published in the Environmental Science and Technology special issue: Technology Baselines and Innovation Priorities for Water Treatm...
Miara, A. et al National Renewable Energy Laboratory
Feb 01, 2022
10 Resources
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TEAMER: Tidal Energy Resource Characterization and Model Validation via the Assessment of Distributed Current Measurements from microFloat Swarms, Data and Post-Access Report

This project evaluated how high-resolution, spatially distributed field data can be used to refine and validate site-scale hydrodynamic simulations of tidal channels. Use of such spatially-distributed field observations or site-scale hydrodynamic simulations will be needed for pro...
Harrison, T. et al University of Washington (NNMREC) Applied Physics Lab
Aug 20, 2020
20 Resources
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