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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
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
BUTTER-E Energy Consumption Data for the BUTTER Empirical Deep Learning Dataset
The BUTTER-E Energy Consumption Data for the BUTTER Empirical Deep Learning Dataset adds node-level energy consumption data from watt-meters to the primary sweep of the BUTTER Empirical Deep Learning Dataset. This dataset contains energy consumption and performance data from 63,52...
Tripp, C. et al National Renewable Energy Laboratory
Dec 30, 2022
9 Resources
1 Stars
Curated
9 Resources
1 Stars
Curated
Utility-Scale Solar, 2021 Edition: Analysis of Empirical Plant-level Data from U.S. Ground-mounted PV, PV+battery, and CSP Plants (exceeding 5 MWAC)
Berkeley Labs "Utility-Scale Solar", 2021 Edition presents analysis of empirical plant-level data from the U.S. fleet of ground-mounted photovoltaic (PV), PV+battery, and concentrating solar-thermal power (CSP) plants with capacities exceeding 5 MWAC. While focused on key developm...
Bolinger, M. et al Lawrence Berkeley National Lab
Sep 30, 2021
2 Resources
0 Stars
Curated
2 Resources
0 Stars
Curated
Utility-Scale Solar, 2022 Edition: Analysis of Empirical Plant-level Data from U.S. Ground-mounted PV, PV+battery, and CSP Plants (exceeding 5 MWAC)
Berkeley Labs "Utility-Scale Solar", 2022 Edition presents analysis of empirical plant-level data from the U.S. fleet of ground-mounted photovoltaic (PV), PV+battery, and concentrating solar-thermal power (CSP) plants with capacities exceeding 5 MWAC. While focused on key developm...
Seel, J. et al Lawrence Berkeley National Lab
Sep 20, 2022
4 Resources
0 Stars
Curated
4 Resources
0 Stars
Curated
Utility-Scale Solar, 2023 Edition: Analysis of Empirical Plant-level Data from U.S. Ground-mounted PV, PV+battery, and CSP Plants (exceeding 5 MWAC)
Berkeley Labs "Utility-Scale Solar", 2023 Edition presents analysis of empirical plant-level data from the U.S. fleet of ground-mounted photovoltaic (PV), PV+battery, and concentrating solar-thermal power (CSP) plants with capacities exceeding 5 MWAC. While focused on key developm...
Seel, J. et al Lawrence Berkeley National Lab
Sep 05, 2023
5 Resources
1 Stars
Publicly accessible
5 Resources
1 Stars
Publicly accessible
M3 Wave DMP/APEX WEC Numerical Survivability Report Baseline Geometry
Summary of numerical survivability modeling method for the baseline geometry of the Delos-Reyes Morrow Pressure Device (DMP), commercialized by M3 Wave LLC as "APEX."
Roberts, J. et al M3 Wave
Aug 16, 2016
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
Utility-Scale Solar, 2024 Edition: Analysis of Empirical Plant-level Data from U.S. Ground-mounted PV, PV+battery, and CSP Plants (exceeding 5 MWAC)
Berkeley Labs "Utility-Scale Solar", 2024 Edition presents analysis of empirical plant-level data from the U.S. fleet of ground-mounted photovoltaic (PV), PV+battery, and concentrating solar-thermal power (CSP) plants with capacities exceeding 5 MWAC. While focused on key developm...
Seel, J. et al Lawrence Berkeley National Lab
Sep 27, 2024
5 Resources
0 Stars
Curated
5 Resources
0 Stars
Curated
Snake River Plain Geothermal Play Fairway Analysis Heat, Permeability, and Seal CRS Map Raster Files
Snake River Plain Play Fairway Analysis Phase 1 CRS Raster Files.
This dataset contains raster files created in ArcGIS. These raster images depict Common Risk Segment (CRS) maps for HEAT, PERMEABILITY, AND SEAL, as well as selected maps of Evidence Layers. These evidence layers c...
Shervais, J. Utah State University
Oct 09, 2015
38 Resources
0 Stars
Publicly accessible
38 Resources
0 Stars
Publicly accessible
Geomechanical Modeling for Thermal Spallation Drilling
Wells for Engineered Geothermal Systems (EGS) typically occur in conditions presenting significant challenges for conventional rotary and percussive drilling technologies: granitic rocks that reduce drilling speeds and cause substantial equipment wear. Thermal spallation drilling,...
Walsh, S. et al Lawrence Livermore National Laboratory
Aug 24, 2011
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible
Graph Theory for Analyzing Pair-wise Data: Application to Interferometric Synthetic Aperture Radar Data
Graph theory is useful for estimating time-dependent model parameters via weighted least-squares using interferometric synthetic aperture radar (InSAR) data. Plotting acquisition dates (epochs) as vertices and pair-wise interferometric combinations as edges defines an incidence gr...
Reinisch, E. University of Wisconsin
Jul 28, 2016
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible
Hybrid machine learning model to predict 3D in-situ permeability evolution
Enhanced geothermal systems (EGS) can provide a sustainable and renewable solution to the new energy transition. Its potential relies on the ability to create a reservoir and to accurately evaluate its evolving hydraulic properties to predict fluid flow and estimate ultimate therm...
Elsworth, D. and Marone, C. Pennsylvania State University
Nov 22, 2022
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible