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Admiralty Inlet Advanced Turbulence Measurements: Final Data and Code ArchiveSource

Data and code that is not already in a public location that is used in Kilcher, Thomson, Harding, and Nylund (2017) "Turbulence Measurements from Compliant Moorings - Part II: Motion Correction" doi: 10.1175/JTECH-D-16-0213.1. The links point to Python source code used in the publication. All other files are source data used in the publication.

0
No licence known
Tags:
ADVAdmiralty InletDOLfYNDeepWater BuoyancyHydrokineticIMUMHKMarineMatlabNRELNortek VectorPNNLPuget SoundStableMoorTTMTidal Turbulence MooringUniversity of WashingtonVECWashingtonWater Velocitybenchbuoybuoy observationscodecorrectioncurrentdataenergyhigh-precisionin situ oceanicinertial motioninstrumentationlab datameasurementmonitoringmooringpowerprocessed dataprocessingpythonpython source coderesourcesensorsensorssourcetesttidal turbulancetorpedoturbulence
Formats:
matVECwprvec821
National Renewable Energy Laboratory (NREL)over 1 year ago
Admiralty Inlet Advanced Turbulence Measurements: June 2014Source

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-depth turbulence measurements. The inertial measurements from the IMU allows for removal of mooring motion in post processing. The mooring motion has been removed from the stream-wise and vertical velocity signals (u, w). The lateral (v) velocity has some 'persistent motion contamination' due to mooring sway. Each ttm was deployed with two ADVs. The 'top' ADV head was positioned 0.5m above the 'bottom' ADV head. The TTMs were placed in 58m of water. The position of the TTMs were: ttm01 : (48.1525, -122.6867) ttm01b : (48.15256666, -122.68678333) ttm02b : (48.152783333, -122.686316666) Deployments TTM01b and TTM02b occurred simultaneously and were spaced approximately 50m apart in the cross-stream direction. Units ----- - Velocity data (_u, urot, uacc) is in m/s. - Acceleration (Accel) data is in m/s^2. - Angular rate (AngRt) data is in rad/s. - The components of all vectors are in 'ENU' orientation. That is, the first index is True East, the second is True North, and the third is Up (vertical). - All other quantities are in the units defined in the Nortek Manual. Motion correction and rotation into the ENU earth reference frame was performed using the Python-based open source DOLfYN library (http://lkilcher.github.io/dolfyn/). Details on motion correction can be found there. Additional details on TTM measurements at this site can be found in the included Marine Energy Technology Symposium paper.

0
No licence known
Tags:
ADVAdmiralty InletDOLfYNDeepWater BuoyancyHydrokineticIMUMHKMarineMatlabNRELNortek VectorPNNLPuget SoundPythonTTMTidal Turbulence MooringTurbulenceUniversity of WashingtonVECaccelerationangular ratebuoycodedataeffectivenessenergyfield testmeasurementpowerpre-processedprocessed dataraw dataresourcesafetyvector fileswater velocity
Formats:
pyvecCSVh5matPDF
National Renewable Energy Laboratory (NREL)over 1 year ago
Admiralty Inlet Advanced Turbulence Measurements: May 2015Source

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). These platforms position ADV heads above the seafloor to make mid-depth turbulence measurements. The inertial measurements from the IMU allows for removal of mooring motion in post processing. The mooring and buoy motion has been removed from the stream-wise and vertical velocity signals (u, w). The lateral (v) velocity has some 'persistent motion contamination' due to mooring sway. The TTM was deployed with one ADV, it's position was: 48 09.145', -122 41.209' The StableMoor was deployed twice, the first time it was deployed in 'wing-mode' with two ADVs ('Port' and 'Star') at: 48 09.166', -122 41.173' The second StableMoor deployment was in 'Nose' mode with one ADV at: 48 09.166', -122 41.174' Units ----- - Velocity data (_u, urot, uacc) is in m/s. - Acceleration (Accel) data is in m/s^2. - Angular rate (AngRt) data is in rad/s. - The components of all vectors are in 'ENU' orientation. That is, the first index is True East, the second is True North, and the third is Up (vertical). - All other quantities are in the units defined in the Nortek Manual. Motion correction and rotation into the ENU earth reference frame was performed using the Python-based open source DOLfYN library (http://lkilcher.github.io/dolfyn/). Details on motion correction can be found there. Additional details on TTM measurements at this site can be found in the included Marine Energy Technology Symposium paper.

0
No licence known
Tags:
ADVAdmiralty InletDOLfYNDeepWater BuoyancyHydrokineticIMUMHKMarineMatlabNRELNortek VectorPNNLPuget SoundPythonStableMoorTTMTidal Turbulence MooringTurbulenceUniversity of WashingtonVECaccelerationangular ratebuoycodedataeffectivenessenergyfield testmeasurementmeasurementsmid-depth turbulenceoceanpowerpre-processedprocessed dataraw dataresourcesafetytechnologyvector fileswater velocity
Formats:
pyVECCSVh5matPDF
National Renewable Energy Laboratory (NREL)over 1 year ago
BOBr Processed Breaking Wave Data, Agate Beach, ORSource

This data was recorded by the BOBr (Buoy to Observe Breaking) off the coast of Newport, OR at Agate Beach in the surf zone. The data was recorded by a 9dof inertial measurement unit and consists of a timestamp, quaternion orientation, acceleration vector, rotation vector, and magnetic vector. The acceleration, rotation, and magnetic vectors have all been corrected back to a North East Down reference frame.

0
No licence known
Tags:
Agate BeachBOBrHydrokineticMHKMarineNewportORaccelerationbreakingbuoycharacterizationdataenergyfree-driftgroundground datamagnetic field vectorsmeasurementoregonorientationpowerprocessed dataquaternionresourcerotationsurfsurf zonewavewaves
Formats:
TXTHTML
National Renewable Energy Laboratory (NREL)over 1 year ago
Distributed Acoustic Sensing (DAS) of Strain at Earth Tide Frequencies: Laboratory TestsSource

The solid Earth strains in response to the gravitational pull from the Moon, Sun, and other planetary bodies. Measuring the flexure of geologic material in response to these Earth tides provides information about the geomechanical properties of rock and sediment. Such measurements are particularly useful for understanding dilation of faults and fractures in competent rock. A new approach to measuring earth tides using fiber optic distributed acoustic sensing (DAS) is presented here. DAS was originally designed to record acoustic vibration through the measurement of dynamic strain on a fiber optic cable. Here, laboratory experiments demonstrate that oscillating strain can be measured with DAS in the microHertz frequency range, corresponding to half-day (M2) lunar tidal cycles. Although the magnitude of strain measured in the laboratory is larger than what would be expected due to earth tides, a clear signal at half-day period was extracted from the data. With the increased signal-to-noise expected from quiet field applications and improvements to DAS using engineered fiber, earth tides could potentially be measured in deep boreholes with DAS. Because of the distributed nature of the sensor (0.25 m measurement interval over kilometers), fractures could be simultaneously located and evaluated. Such measurements would provide valuable information regarding the placement and stiffness of open fractures in bedrock. Characterization of bedrock fractures is an important goal for multiple subsurface operations such as petroleum extraction, geothermal energy recovery, and geologic carbon sequestration.

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No licence known
Tags:
DASEGSLab TestsMatlabcharacterizationdistributed acoustic sensingearth tideenergyfiber optics sensorsfracturegeomechanicsgeothermalhydrauliclow frequency strainmeasurementstimulation strain
Formats:
matHTML
National Renewable Energy Laboratory (NREL)over 1 year ago
Earth Observations of Water Resources E-Book

This e-book is a quick primer on earth observation of water resources and has been developed jointly by the World Bank and NASA. It provides a basic introduction to hydrologic processes and the types of in-situ and earth observation monitoring approaches to gain a global perspective to help address problems in the real world such as floods, droughts, cyclones, and forecasting for agriculture and water-related disease management applications. It provides a primer for accessing useful NASA data, modeling tools, related interactive viewers and useful links in this regard, that showcase interactive maps to visualize precipitation and even groundwater data and trends and near-real time flood potential from space. This e-book provides an illustrative overview of the use of increasingly powerful free data from satellites that can be critical for monitoring and managing watersheds and aquifers around the world.

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Creative Commons Attribution
Tags:
globalmeasurementrainfallremote sensingrunoffwater resources
Formats:
HTML
World Bankover 1 year ago
Filenames of Data from the Distributed Acoustic Sensing Experiment at Garner Valley, CaliforniaSource

In September 2013, an experiment using Distributed Acoustic Sensing (DAS) was conducted at Garner Valley, a test site of the University of California Santa Barbara (Lancelle et al., 2014). This submission lists all file names from Distributed Acoustic Sensing (DAS) data collected as part of PoroTomo Subtask 3.2. These file names represent data that is sampled at 1000 samples per second in segy format. The data is currently stored at University of Wisconsin Madison.

0
No licence known
Tags:
DASEGSPoroTomodirectivitydistributed acoustic sensingfiber-opticsfilenamesgeothermalground motionmeasurementsensitivity
Formats:
TXTHTML
National Renewable Energy Laboratory (NREL)over 1 year ago
HydroSheds

HydroSHEDS (Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales) provides hydrographic information in a consistent and comprehensive format for regional and global-scale applications. HydroSHEDS offers a suite of geo-referenced data sets in raster and vector format, including stream networks, watershed boundaries, drainage directions, and ancillary data layers such as flow accumulations, distances, and river topology information. Recently available data derived from HydroSHEDS include comprehensive layers of major basins and smaller sub-basins (~100-2,500 km2) across the globe. These data layers are available to support watershed analyses, hydrological modeling, and freshwater conservation planning at a quality, resolution, and extent that had previously been unachievable in many parts of the world. Data includes Void-Filled elevation, Hydrologically conditioned elevation, drainage directions, flow accumulation, river network, basin outlines, HydroBASINS License information: https://www.hydrosheds.org/page/license

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Other (Attribution)
Tags:
accumulationglobalmeasurementrainfallrasterremote sensingrunoffvectorwater resourceswatershed
Formats:
SHP
WWFover 1 year ago
Improved Microseismicity Detection During Newberry EGS StimulationsSource

Effective enhanced geothermal systems (EGS) require optimal fracture networks for efficient heat transfer between hot rock and fluid. Microseismic mapping is a key tool used to infer the subsurface fracture geometry. Traditional earthquake detection and location techniques are often employed to identify microearthquakes in geothermal regions. However, most commonly used algorithms may miss events if the seismic signal of an earthquake is small relative to the background noise level or if a microearthquake occurs within the coda of a larger event. Consequently, we have developed a set of algorithms that provide improved microearthquake detection. Our objective is to investigate the microseismicity at the DOE Newberry EGS site to better image the active regions of the underground fracture network during and immediately after the EGS stimulation. Detection of more microearthquakes during EGS stimulations will allow for better seismic delineation of the active regions of the underground fracture system. This improved knowledge of the reservoir network will improve our understanding of subsurface conditions, and allow improvement of the stimulation strategy that will optimize heat extraction and maximize economic return.

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No licence known
Tags:
EGSNGDS Content ModelNewberryUSGIN Content Modeldetectionfracturegeothermalhydrualicinduced seismicitymeasurementmicroearthquakemicroseismicitymonitoringreservoirseismicitystimulation
Formats:
XLS
National Renewable Energy Laboratory (NREL)over 1 year ago
Utah FORGE Report on the Thermal Properties of Wells 16A(78)-32 & 58-32 GraniteSource

This is a report from Metarock Laboratories on the thermal properties of Utah FORGE wells 16A(78)-32 & 58-32 granite. The report includes pictures of core samples, core details for the samples (where the sample was taken and the size of the sample), sample thermal expansion test results, radial velocity measurements, and hydrostatic test results.

0
No licence known
Tags:
EGSMetarock reportUtah FORGEUtah FORGE granite thermal propertiesWell 16A78-32Well 16A78-32 graniteWell 16A78-32 granite thermal propertiesWell 58-32Well 58-32 graniteWell 58-32 granite thermal propertiescore datacore samplegeothermalgranitegranite thermal propertieshydrostaticmeasurementradial velocityreportrock thermal propertiessampletesttestingteststhermal expansion
Formats:
PDF
National Renewable Energy Laboratory (NREL)over 1 year ago