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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
G-Function Library for Modeling Vertical Bore Ground Heat Exchanger
This library contains g-functions (thermal response functions) for standard, regularly spaced vertical borehole ground heat exchangers. In total, it contains 34, 321 configurations. To permit interpolation, each configuration has g-functions for heights of 24, 48, 96, 192, and 384...
Spitler, J. et al Oak Ridge National Laboratory
Jun 30, 2021
10 Resources
0 Stars
Publicly accessible
10 Resources
0 Stars
Publicly accessible
Early Market Opportunity MHK Energy Site Identification Wave and Tidal Resources
This data was compiled for the 'Early Market Opportunity Hot Spot Identification' project. The data and scripts included were used in the 'MHK Energy Site Identification and Ranking Methodology' Reports (see resources below). The Python scripts will generate a set of results--base...
Kilcher, L. National Renewable Energy Laboratory
Apr 01, 2016
7 Resources
0 Stars
Publicly accessible
7 Resources
0 Stars
Publicly accessible
Sample IEEE123 Bus system for OEDI SI
Time series load and PV data from an IEEE123 bus system. An example electrical system, named the OEDI SI feeder, is used to test the workflow in a co-simulation. The system used is the IEEE123 test system, which is a well studied test system (see link below to IEEE PES Test Feeder...
Elgindy, T. and Balasubramaniam, K. National Renewable Energy Laboratory
Sep 01, 2022
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
Proved Natural Gas Reserves: 2010
CIA: World Factbook assessment of proved reserves
of natural gas in cubic meters (cu m). Proved reserves are those
quantities of natural gas, which, by analysis of geological and
engineering data, can be estimated with a high degree of confidence to
be commercially recov...
Weers, J. and (CIA), C. National Renewable Energy Laboratory
Dec 31, 2009
3 Resources
0 Stars
In curation
3 Resources
0 Stars
In curation
Proved Oil Reserves: 2010
CIA: World Factbook assessment of proved reserves of crude oil in barrels
(bbl). Proved reserves are those quantities of petroleum which, by
analysis of geological and engineering data, can be estimated with a
high degree of confidence to be commercially recoverable from a ...
Weers, J. and (CIA), C. National Renewable Energy Laboratory
Dec 31, 2009
3 Resources
0 Stars
In curation
3 Resources
0 Stars
In curation
Rare Earth Geochemistry of Rock Core form WY Reservoirs
These data include major, minor, trace and rare earth element concentration of geologic formations in Wyoming oil and gas fields.
*Note Link below contains updated version of spreadsheet (6/14/2017)
Quillinan, S. et al University of Wyoming
Oct 01, 2016
2 Resources
0 Stars
Publicly accessible
2 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
Admiralty Inlet Advanced Turbulence Measurements: June 2014
This data is from measurements at Admiralty Head, in Admiralty Inlet (Puget Sound) in June of 2014. The measurements were made using Inertial Motion Unit (IMU) equipped ADVs mounted on Tidal Turbulence Mooring's (TTMs). The TTM positions the ADV head above the seafloor to make mid...
Kilcher, L. National Renewable Energy Laboratory
Jun 30, 2014
26 Resources
0 Stars
Publicly accessible
26 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
Publicly accessible