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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
Programs and Code for Geothermal Exploration Artificial Intelligence
The scripts below are used to run the Geothermal Exploration Artificial Intelligence developed within the "Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning" project. It includes all scripts for pre-processing and processing, including...
Moraga, J. Colorado School of Mines
Apr 27, 2021
11 Resources
0 Stars
Publicly accessible
11 Resources
0 Stars
Publicly accessible
NREL Eagle supercomputer jobs
High performance computing dataset with 11M+ jobs from NREL's Eagle supercomputer. These jobs were submitted to run on Eagle between Nov 2018 and Feb 2023. The data are sufficiently anonymized and do not include sensitive user or project data. HPC research community does not have ...
Duplyakin, D. and Menear, K. National Renewable Energy Laboratory
Feb 28, 2023
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
PV Rooftop Database for Puerto Rico (PVRDB-PR)
The National Renewable Energy Laboratory's (NREL) PV Rooftop Database for Puerto Rico (PVRDB-PR) is a lidar-derived, geospatially-resolved dataset of suitable roof surfaces and their PV technical potential for virtually all buildings in Puerto Rico. The dataset can be downloaded a...
Mooney, M. and Waechter, K. National Renewable Energy Laboratory (NREL)
Dec 16, 2020
5 Resources
0 Stars
Curated
5 Resources
0 Stars
Curated
Demand-Side Grid (dsgrid) TEMPO Light-Duty Vehicle Charging Profiles v2022
Simulated hourly electric vehicle charging profiles for light-duty household passenger vehicles in the contiguous United States, 2018-2050. Profiles are differentiated by scenario, county, household and vehicle types, and charging type. Data was produced in 2022 using the Transpor...
Yip, A. et al National Renewable Energy Laboratory
Aug 29, 2023
8 Resources
0 Stars
Curated
8 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
Utah FORGE Phase Native State FALCON Model Files
The submission includes FALCON input file and mesh for the an initial pressure-temperature simulation, and a second set for pressure-temperature-displacement simulation. All simulations are steady state. Data and input for the FORGE Phase 2 native state model were compiled from hi...
Podgorney, R. Idaho National Laboratory
Jun 06, 2019
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration and Development of Hidden Geothermal Resources
Geothermal exploration and production are challenging, expensive and risky. The GeoThermalCloud uses Machine Learning to predict the location of hidden geothermal resources. This submission includes a training dataset for the GeoThermalCloud neural network. Machine Learning for Di...
Ahmmed, B. Stanford University
Apr 04, 2022
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
GeoThermalCloud framework for fusion of big data and multi-physics models in Nevada and Southwest New Mexico
Our GeoThermalCloud framework is designed to process geothermal datasets using a novel toolbox for unsupervised and physics-informed machine learning called SmartTensors. More information about GeoThermalCloud can be found at the GeoThermalCloud GitHub Repository. More information...
Vesselinov, V. Los Alamos National Laboratory
Mar 29, 2021
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
Catalyst Design in Nitrate Removal
Based on the volcano plot developed by Dr. Goldsmith group (Report linked in submission), we utilized DFT (density functional theory) calculations to search for bimetallic materials in the application of catalysts in aqueous nitrate removal. The calculations are conducted via the ...
Wang, D. and Jain, A. Lawrence Berkeley National Laboratory
Dec 01, 2021
7 Resources
0 Stars
Publicly accessible
7 Resources
0 Stars
Publicly accessible
Deep Direct-Use Feasibility Study Economic Analysis using GEOPHIRES for West Virginia University
This dataset contains all the inputs used and output produced from the modified GEOPHIRES for the economic analysis of base case hybrid GDHC system, improved hybrid GDHC system with heat pump and for hot water GDHC.
Software required: Microsoft Notepad, Microsoft Excel and GEOPHI...
Garapati, N. West Virginia University
Jan 09, 2020
8 Resources
0 Stars
Publicly accessible
8 Resources
0 Stars
Publicly accessible
EGS Collab: 3D Geophysical Model Around the Sanford Underground Research Facility
This package contains data associated with a proceedings paper (linked below) submitted to the 44th Workshop on Geothermal Reservoir Engineering. The Geophysical Model text file contains density, P and S-wave seismic speeds on a 3D grid. The file has six columns and provides latit...
Chai, C. et al Lawrence Berkeley National Laboratory
Feb 06, 2019
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
Linearized Distribution Optimal Power Flow for OEDI SI
This research is to meant to demonstrate the OEDI SI use case for distributed optimal power flow (DOPF). The goal was to formulate the optimal power flow problem in the distribution system for active and reactive power setpoints of PV systems using topology information and voltage...
Sadnan, R. et al Pacific Northwest National Laboratory
Oct 03, 2023
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible
PNNL Distribution System State Estimator Docker Image
This is the docker image for Pacific Northwest National Laboratory's (PNNL) distribution system state estimator (DSSE) used for the demo of OEDI-SI platform. To support the operation of modern distribution systems, operators require real-time visibility into system states. Due to ...
Bhatti, B. et al Pacific Northwest National Laboratory
Jul 10, 2023
6 Resources
2 Stars
Curated
6 Resources
2 Stars
Curated
Error-Level-Controlled Synthetic Forecasts for Renewable Generation
Renewable energy resources, including solar and wind energy, play a significant role in sustainable energy systems. However, the inherent uncertainty and intermittency of renewable generation pose challenges to the safe and efficient operation of power systems. Recognizing the imp...
Zhang, X. et al National Renewable Energy Laboratory (NREL)
Jun 01, 2021
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible