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National Renewable Energy Laboratory×

HERO WEC V1 Upgrades SolidWorks Models (WEC, RO System, and Submersible Pump Housing)

The attached zip files include SolidWorks pack-and-go assemblies of NREL's HERO WEC (hydraulic and electric reverse osmosis wave energy converter), the reverse osmosis (RO) assembly, and the submersible pump assembly that is used to provide flow to the RO assembly in the electric ...
Jenne, S. and Panzarella, J. National Renewable Energy Laboratory
Jan 08, 2024
4 Resources
0 Stars
Publicly accessible

HERO WEC V1.0 SolidWorks Model

The attached zip file includes a SolidWorks pack-and-go assembly of NREL's HERO WEC (hydraulic and electric reverse osmosis wave energy converter) V1.0. This model does not include all aspects of the design (i.e. RO (reverse osmosis) system, electrical enclosure, hose, cable) it o...
Jenne, S. National Renewable Energy Laboratory
Aug 12, 2022
2 Resources
0 Stars
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Workplace Charging Data

A data set gathered and maintained by NREL that tracks over 300 vehicles during the course of a 4-year period and how they behave in a workplace charging capacity. The data is further enriched by examining the effect of free charging versus paid charging. There is also a distincti...
Neuman. . et al National Renewable Energy Laboratory
Jan 04, 2022
2 Resources
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HERO WEC Bills of Materials: WEC, RO System, and Submersible Pump

This submission includes detailed Bills of Materials for the NREL-designed and built Hydraulic and Electric Reverse Osmosis Wave Energy Converter (HERO WEC), as well as the reverse osmosis assembly and submersible pump that are used in the HERO WEC. The WEC file is specific to th...
Jenne, S. and Panzarella, J. National Renewable Energy Laboratory
Jan 01, 2024
5 Resources
0 Stars
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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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