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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
0 Stars
Publicly accessible
16 Resources
0 Stars
Publicly accessible
WaterTAP3 Model Results for NAWI's Baseline Analyses
Description: This folder 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 ...
Miara, A. et al National Renewable Energy Laboratory
Feb 01, 2022
10 Resources
0 Stars
Publicly accessible
10 Resources
0 Stars
Publicly accessible
Altered Rotokawa Andesite Thermal Treatment Petrophysics
Physical property data for transitory heating of altered Rotokawa andesite under saturated conditions at 20 MPa pressure. "M" samples are moderately altered, and "H" samples are highly altered. White-background columns depict pre-treatment data. Grey-background columns depict post...
Kennedy, B. National Renewable Energy Laboratory
Aug 20, 2019
1 Resources
0 Stars
In curation
1 Resources
0 Stars
In curation
Geothermal Sector Cybersecurity Vulnerability Assessment Presentation
As geothermal resource contributions to the energy sector grow, cybersecurity will be increasingly important to ensure resilient, reliable, and secure clean energy for years to come. An overview of the cybersecurity vulnerability assessment project was developed and presented at t...
Markel, T. et al National Renewable Energy Laboratory
Oct 20, 2020
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible
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
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
United States High Resolution Biomass (2008)
Biomass resource potential for the lower 48 states of the United States of America.
Estimated technical biomass resources available in the United States by county. The following feedstock categories are considered for this study: crop residues, methane emissions from manure man...
Langle, N. and Laboratory, N. National Renewable Energy Laboratory
Nov 25, 2014
3 Resources
0 Stars
In curation
3 Resources
0 Stars
In curation
Unified Field Study 3 (UFS-3)
The Unified Field Studies (UFS), established by the Algae Testbed Public-Private Partnership (ATP3), produced data on the effect of environmental and process conditions on algal growth rates and algal composition. The goal of the third Unified Field Study (UFS-3), performed June t...
Wolfrum, E. et al National Renewable Energy Laboratory
Sep 29, 2016
24 Resources
0 Stars
Publicly accessible
24 Resources
0 Stars
Publicly accessible
Unified Field Study 4 (UFS-4)
The Unified Field Studies (UFS), established by the Algae Testbed Public-Private Partnership (ATP3), produced data on the effect of environmental and process conditions on algal growth rates and algal composition. The goal of the fourth Unified Field Study (UFS-4), performed Septe...
Wolfrum, E. et al National Renewable Energy Laboratory
Sep 27, 2016
24 Resources
0 Stars
Publicly accessible
24 Resources
0 Stars
Publicly accessible
Unified Field Study 5 (UFS-5)
The Unified Field Studies (UFS), established by the Algae Testbed Public-Private Partnership (ATP3), produced data on the effect of environmental and process conditions on algal growth rates and algal composition. The goal of the fifth Unified Field Study (UFS-5), performed Decemb...
Wolfrum, E. et al National Renewable Energy Laboratory
Sep 27, 2016
24 Resources
0 Stars
Publicly accessible
24 Resources
0 Stars
Publicly accessible
Unified Field Study 6 (UFS-6)
The Unified Field Studies (UFS), established by the Algae Testbed Public-Private Partnership (ATP3), produced data on the effect of environmental and process conditions on algal growth rates and algal composition. The goal of the sixth Unified Field Study (UFS-6), performed March ...
Wolfrum, E. et al National Renewable Energy Laboratory
Oct 20, 2017
24 Resources
0 Stars
Publicly accessible
24 Resources
0 Stars
Publicly accessible
Unified Field Study 2 (UFS-2)
The Unified Field Studies (UFS), established by the Algae Testbed Public-Private Partnership (ATP3), produced data on the effect of environmental and process conditions on algal growth rates and algal composition. The goal of the second Unified Field Study (UFS-2), performed April...
Wolfrum, E. et al National Renewable Energy Laboratory
Sep 27, 2016
18 Resources
0 Stars
Publicly accessible
18 Resources
0 Stars
Publicly accessible
Unified Field Study 7 (UFS-7)
The Unified Field Studies (UFS), established by the Algae Testbed Public-Private Partnership (ATP3), produced data on the effect of environmental and process conditions on algal growth rates and algal composition. The goal of the seventh Unified Field Study (UFS-7), performed June...
Wolfrum, E. et al National Renewable Energy Laboratory
Oct 20, 2017
18 Resources
0 Stars
Publicly accessible
18 Resources
0 Stars
Publicly accessible
Unified Field Study 1 (UFS-1)
The Unified Field Studies (UFS), established by the Algae Testbed Public-Private Partnership (ATP3), produced data on the effect of environmental and process conditions on algal growth rates and algal composition. The goal of the UFS-1 experiment, performed October to December 201...
Wolfrum, E. et al National Renewable Energy Laboratory
Sep 27, 2016
16 Resources
0 Stars
Publicly accessible
16 Resources
0 Stars
Publicly accessible
Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results
Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells increasing or decreasing the fluid flow rates across the wells and drilling new wells at appropriate locations. Th...
Beckers, K. et al National Renewable Energy Laboratory
Oct 20, 2021
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible