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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
Tracking the Sun
Berkeley Lab's Tracking the Sun report series is dedicated to summarizing installed prices and other trends among grid-connected, distributed solar photovoltaic (PV) systems in the United States. The present report, the 11th edition in the series, focuses on systems installed thro...
Barbose, G. and Darghouth, N. Lawrence Berkeley National Laboratory (LBNL)
Oct 01, 2019
6 Resources
1 Stars
Curated
6 Resources
1 Stars
Curated
G2Aero Database of Airfoils Curated Airfoils
This dataset contains a curated set of 19,164 airfoil shapes from various applications and the data-driven design space of separable shape tensors (PGA space), which can be used as a parameter space for machine-learning applications focused on airfoil shapes.
We constructed the a...
Doronina, O. et al National Renewable Energy Lab NREL
Sep 24, 2024
3 Resources
0 Stars
Curated
3 Resources
0 Stars
Curated
Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files
This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir thermal energy storage site identification.
In this study, a machine-learning-assiste...
Jin, W. et al Idaho National Laboratory
Apr 15, 2022
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
Admiralty Inlet Advanced Turbulence Measurements: May 2015
This data is from measurements at Admiralty Head, in Admiralty Inlet (Puget Sound) in May of 2015. The measurements were made using Inertial Motion Unit (IMU) equipped ADVs mounted on a 'StableMoor' (Manufacturer: DeepWater Buoyancy) buoy and a Tidal Turbulence Mooring (TTM). Thes...
Kilcher, L. National Renewable Energy Laboratory
May 18, 2015
18 Resources
0 Stars
Publicly accessible
18 Resources
0 Stars
Publicly accessible
Airfoil Computational Fluid Dynamics 9k shapes, 2 AoA's
This dataset contains aerodynamic quantities including flow field values (momentum, energy, and vorticity) and summary values (coefficients of lift, drag, and momentum) for 8,996 airfoil shapes, computed using the HAM2D CFD (computational fluid dynamics) model. The airfoil shapes ...
Ramos, D. et al National Renewable Energy Laboratory (NREL)
Feb 10, 2023
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
PoroTomo Natural Laboratory Horizontal and Vertical Distributed Acoustic Sensing Data
This dataset includes links to the PoroTomo DAS data in both SEG-Y and hdf5 (via h5py and HSDS with h5pyd) formats with tutorial notebooks for use. Data are hosted on Amazon Web Services (AWS) Simple Storage Service (S3) through the Open Energy Data Initiative (OEDI). Also include...
Feigl, K. et al University of Wisconsin
Mar 29, 2016
18 Resources
0 Stars
Publicly accessible
18 Resources
0 Stars
Publicly accessible
ARPA-E Grid Optimization (GO) Competition Challenge 3
Synthetic Input Data and Team Results for the GO Competition Challenge 3 for Events 1 4 and the Sandbox, along with problem and format descriptions and code to validate data and solutions, are available here. Data for industry scenarios will not be made public.
The Grid Optimizat...
Elbert, S. et al Pacific Northwest National Laboratory
May 02, 2024
39 Resources
1 Stars
Curated
39 Resources
1 Stars
Curated
EGS Collab Experiment 1: Microseismic Monitoring
The U.S. Department of Energy's Enhanced Geothermal System (EGS) Collab project aims to improve our understanding of hydraulic stimulations in crystalline rock for enhanced geothermal energy production through execution of intensely monitored meso-scale experiments. The first expe...
Schoenball, M. et al Lawrence Berkeley National Laboratory
Jul 29, 2019
45 Resources
0 Stars
Publicly accessible
45 Resources
0 Stars
Publicly accessible