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HERO WEC V1 Upgrade 2023 Laboratory Testing (processed data)
The following submission includes processed laboratory data from NREL's Hydraulic and Electric Reverse Osmosis Wave Energy Converter (HERO WEC), in the form of MATLAB workspaces. This dataset was created using NREL's Large Amplitude Motion Platform (LAMP) and collected between Aug...
Panzarella, J. et al National Renewable Energy Laboratory
Jan 01, 2024
12 Resources
0 Stars
Publicly accessible
12 Resources
0 Stars
Publicly accessible
Utah FORGE: Fault Shear Reactivation Experimental Data for Fluid Injection-Rate Controls on Seismic Moment
Included are experimental data recorded from shear experiments that specifically explore the link between fluid-injection rate and seismic moment resulting from shear reactivation of laboratory faults. Raw mechanical data from three experiments are included alongside corresponding...
Roseboom, M. et al Pennsylvania State University
Nov 07, 2023
6 Resources
0 Stars
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6 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
0 Stars
Publicly accessible
4 Resources
0 Stars
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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
Publicly accessible
9 Resources
1 Stars
Publicly accessible
Utah FORGE: Fault Reactivation Through Fluid Injection Induced Seismicity Laboratory Experiments
Included are results from shear reactivation experiments on laboratory faults pre-loaded close to failure and reactivated by the injection of fluid into the fault. The sample comprises a single-inclined-fracture (SIF) transecting a cylindrical sample of Westerly granite.
All expe...
Yu, J. et al Pennsylvania State University
Jul 01, 2023
27 Resources
0 Stars
Publicly accessible
27 Resources
0 Stars
Publicly accessible
MASK4 Test Campaign for Sandia WaveBot Device Dataset
This data and report details the findings from a wave tank test focused on production of useful work of a wave energy converter (WEC) device. The experimental system and test were specifically designed to validate models for power transmission throughout the WEC system. Additional...
Forbush, D. et al Sandia National Laboratories
Dec 25, 2023
5 Resources
0 Stars
Publicly accessible
5 Resources
0 Stars
Publicly accessible
Imperial Valley Dark Fiber Project Continuous DAS Data
The Imperial Valley Dark Fiber Project acquired Distributed Acoustic Sensing (DAS) seismic data on a ~28 km segment of dark fiber between the cities of Calipatria and Imperial in the Imperial Valley, Southern California. Dark fiber refers to unused optical fiber cables in telecomm...
Ajo-Franklin, J. et al Lawrence Berkeley National Laboratory
Nov 10, 2020
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
Admiralty Inlet Hub-Height Turbulence Measurements from June 2012
This data is from measurements at Admiralty Head, in Admiralty Inlet. The measurements were made using an IMU equipped ADV mounted on a mooring, the 'Tidal Turbulence Mooring' or 'TTM'. The inertial measurements from the IMU allows for removal of mooring motion in post processing....
Kilcher, L. National Renewable Energy Laboratory
Jun 18, 2012
7 Resources
0 Stars
Publicly accessible
7 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
Demand-Side Grid Model (dsgrid) Data from the Electrification Futures Project (EFS)
This data set contains the full-resolution and state-level data described in the linked technical report (https://www.nrel.gov/docs/fy18osti/71492.pdf). It can be accessed with the NREL-dsgrid-legacy-efs-api, available on GitHub at https://github.com/dsgrid/dsgrid-legacy-efs-api a...
Hale, E. et al National Renewable Energy Laboratory
Jul 08, 2018
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
Co-Design of Marine Energy Converters for Autonomous Underwater Vehicle Docking and Recharging Software and Data
Software and testing data from the OH Hinsdale Wave lab for DOE-funded project on Co-Design of Marine Energy Converters for Autonomous Underwater Vehicle Docking and Recharging. This project will perform foundational research and testing to accelerate the sector-wide development a...
Hollinger, G. et al Oregon State University
Oct 26, 2022
11 Resources
0 Stars
Publicly accessible
11 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
Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk
In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity producti...
Siler, D. et al United States Geological Survey
Oct 01, 2021
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
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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