Laboratory Observations of Artificial Sand and Oil Agglomerates Video and Velocity Data: Sea Floor Interaction Experiment Flow Velocity

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What does this data set describe?

Title:
Laboratory Observations of Artificial Sand and Oil Agglomerates Video and Velocity Data: Sea Floor Interaction Experiment Flow Velocity
Abstract:
Weathered oil in the surf-zone after an oil spill may mix with suspended sediments to form sand and oil agglomerates (SOA). Sand and oil agglomerates may form in mats on the scale of tens of meters (m), and may break apart into pieces between 1 and 10 centimeters (cm) in diameter. These more mobile pieces are susceptible to alongshore and cross-shore transport, and lead to beach re-oiling on the time scale of months to years following a spill. The U.S. Geological Survey (USGS) conducted experiments March 10 - 13, 2014, to expand the available data on sand and oil agglomerate motion; test shear stress based incipient motion parameterizations in a controlled, laboratory setting; and directly observe SOA exhumation and burial processes. Artificial sand and oil agglomerates (aSOA) were created and deployed in a small-oscillatory flow tunnel in two sets of experiments, during which, video and velocity data were obtained. The first experiment, which was set up to help researchers investigate incipient motion, used with an immobile, rough bottom (referred to as false-floor) and the second–testing seafloor interactions–utilized with a coarse grain sand bottom (movable sand bed). Detailed information regarding the creation of the aSOA can be found in Dalyander et al. (2015). More information about the USGS laboratory experiment conducted in collaboration with the Naval Research Laboratory can be found in the associated Open File Report (OFR Number Unknown).
Supplemental_Information:
This dataset, 2017-309-DD_SFI_velocity.zip, contains tabular digital data of flow velocity collected during small-oscillatory flow tunnel laboratory experiments at the Naval Research Laboratory, Stennis Space Center, Stennis Mississippi. To ensure that SPCMSC data management protocols were followed, this survey was retroactively assigned a USGS field activity number (FAN), 2017-309-DD. Additional survey and data details are available at http://cmgds.marine.usgs.gov/fan_info.php?fan=2017-309-DD.
  1. How might this data set be cited?
    U.S. Geological Survey, 20170512, Laboratory Observations of Artificial Sand and Oil Agglomerates Video and Velocity Data: Sea Floor Interaction Experiment Flow Velocity: U.S. Geological Survey Data Release doi:10.5066/F76D5R69, U.S. Geological Survey, Coastal and Marine Geology Program, Saint Petersburg, FL.

    Online Links:

    This is part of the following larger work.

    Jenkins, Robert L. III, Dalyander, P. Soupy, Penko, Allison M., and Long, Joseph W., 2017, Laboratory Observations of Artificial Sand and Oil Agglomerates: Open-File Report 2018–1010, U.S. Geological Survey, Reston, VA.

    Online Links:

  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -89.651
    East_Bounding_Coordinate: -89.557
    North_Bounding_Coordinate: 30.395
    South_Bounding_Coordinate: 30.345
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date: 10-Mar-2014
    Ending_Date: 13-Mar-2014
    Currentness_Reference:
    ground condition
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: tabular digital data
  6. How does the data set represent geographic features?
    1. How are geographic features stored in the data set?
    2. What coordinate system is used to represent geographic features?
  7. How does the data set describe geographic features?
    2017_309_DD_SFI_velocity
    Tabular digital data text files of movable bed experiment flow velocity. (Source: U.S. Geological Survey)
    time(s)
    Vectrino velocity profiler record time of experiment. (Source: U.S. Geological Survey)
    Range of values
    Minimum:0.01940
    Maximum:808.00128
    Units:seconds
    u (m/s)
    Smoothed, along-tank water velocity as measured by Vectrino velocity profiler during experiment segment. (Source: U.S. Geological Survey)
    Range of values
    Minimum:-0.50460
    Maximum:0.47179
    Units:Meters per second (m/s)
    Entity_and_Attribute_Overview:
    The entity and attribute information provided here describes the data associated with the dataset. Please review the detailed descriptions that are provided (the individual attribute descriptions) for information on the values that appear as entries of the dataset.
    Entity_and_Attribute_Detail_Citation:
    The entity and attribute information was generated by the individual and/or agency identified as the originator of the dataset. Please review the rest of the metadata record for additional details and information.

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • U.S. Geological Survey
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    P. Soupy Dalyander
    U.S. Geological Survey
    Research Oceanographer
    600 Fourth Street South
    Saint Petersburg, Florida
    USA

    727-502-8124 (voice)
    727-502-8001 (FAX)
    sdalyander@usgs.gov

Why was the data set created?

This dataset presents observations of along-tank flow velocity during observations of sand and oil agglomerate exhumation and burial processes. Along-tank flow velocities were collected by a single Vectrino acoustic Doppler profiler during a 2014 USGS small-oscillatory flow tunnel experiment conducted at the Naval Research Laboratory (NRL), Stennis Space Center, Mississippi. The information contained within the text files is needed to capture flow velocity as aSOAs interact with a movable coarse grain sand bed under laboratory conditions. This dataset contains tabular digital data, in text files, of flow velocities in a small-oscillatory flow tunnel from the sea floor interaction experiment. Videos of tank observations, which provide additional information about aSOA incipient motion, were also collected during each experiment (see 2017_309_DD_SFI_video.zip) and are included in this data release.

How was the data set created?

  1. From what previous works were the data drawn?
  2. How were the data generated, processed, and modified?
    Date: 12-Mar-2014 (process 1 of 7)
    In March, 2014, experiments were conducted at NRL’s Sediment Dynamics Laboratory, located in Stennis, MS. Artificial sand-oil agglomerates were deployed in the small-oscillatory flow tunnel with a cross-sectional area of 25 cm by 25 cm, a test bed length of 2-m, and a 35-cm deep sediment well. Oscillating currents (simulating bottom velocities generated by waves) were driven in the tank by a flywheel with variable frequencies (20-90 rpm) and stroke lengths (22, 33, or 44 cm). For all experiments, the oscillatory current had a slight asymmetry resulting in preferential transport downstream (toward the sediment trap) in the tank. Two high-definition Canon 7D DSLR cameras were mounted outside of the tank to record movement, each with a unique, separate, field of view. Camera A was outfitted with an 18-55 mm zoom lens at a 29 mm focal length and Camera B used an 18 mm fisheye lens. The tank was also equipped with a Vectrino acoustic velocity profiler, mounted centrally. Additional information on the characteristics and design of the flow tunnel can be found in Calantoni and others (2013). Person who carried out this activity:
    Robert L. Jenkins III
    U.S. Geological Survey
    Researcher III
    600 Fourth Street South
    Saint Petersburg, FL

    727-502-8138 (voice)
    727-502-8182 (FAX)
    rljenkins@usgs.gov
    Date: 12-Mar-2014 (process 2 of 7)
    The field of view of Camera A is over lapped by the field of view of Camera B. In the field of view of both Camera A and Camera B, is a small red LED indicator light, which signals the beginning of the Vectrino record for a given experiment segment for the purpose of syncing the Vectrino velocity profile data and video records in time. Person who carried out this activity:
    Robert L. Jenkins III
    U.S. Geological Survey
    Researcher III
    600 Fourth Street South
    Saint Petersburg, FL

    727-502-8138 (voice)
    727-502-8182 (FAX)
    rljenkins@usgs.gov
    Date: 12-Mar-2014 (process 3 of 7)
    Velocities were logged by a Vectrino acoustic Doppler profiler mounted centrally within the tank. Velocity recording was manually started after the beginning of the video recording. The start of the velocity record was indicated in the video by a single blink of a red LED indicator light. 3D velocity was logged by the Vectrino software package and saved as raw binary files with file extension “.ntk”. The Vectrino acoustic velocity profiler measured 3D water velocity (m/s) of a 4 cm profile below the instrument and the distance from the instrument to the sand bed (m), using coherent Doppler processing at a frequency of 100 Hz. Person who carried out this activity:
    Robert L. Jenkins III
    U.S. Geological Survey
    Researcher III
    600 Fourth Street South
    Saint Petersburg, FL

    727-502-8138 (voice)
    727-502-8182 (FAX)
    rljenkins@usgs.gov
    Date: 12-Aug-2015 (process 4 of 7)
    Raw Vectrino data were processed in MATLAB 2015b by a script called “VectrinoII_ProcessData.m” (2011) (NRL script,) which extracted time, depth information, and 3D velocity (m/s) from raw data files. Next, velocities were processed iteratively to remove spikes in the data.
    First, velocities were passed through a MATLAB built-in one dimensional smoothing filter (filter.m) with a window size of ten.
    Second, the difference was taken between the raw and smoothed time series and the standard deviation of that difference was calculated.
    Third, points with a difference greater than three times the standard deviation were identified, and replaced with the smoothed signal value at the same time.
    The first, second, and third, steps were then repeated three times, with the previously de-spiked signal replacing the input each time, which produced final, quality controlled, de-spiked and smoothed de-spiked time series of velocities.
    
    De-spiked and smoothed de-spiked records of 3D velocity data, time, and depth information were re-saved in MATLAB readable ‘.mat’ files. De-spiked and smoothed de-spiked velocity data were treated with an additional quality control step.
    A measure of signal quality, called Correlation, was recorded by the Vectrino profiler along with the raw data. Correlation is the measure of the data correlation as returned by each of the three acoustic beams of the profiler.
    Time points with correlation less than 70% are replaced in the record with non-number (NaN) values.
    
    Quality controlled records of de-spiked and smoothed de-spiked velocity were saved in MATLAB readable ‘.mat’ files. Person who carried out this activity:
    Robert L. Jenkins III
    U.S. Geological Survey
    Researcher III
    600 Fourth Street South
    Saint Petersburg, FL

    727-502-8138 (voice)
    727-502-8182 (FAX)
    rljenkins@usgs.gov
    Date: 24-Sep-2015 (process 5 of 7)
    Time differences between video and corresponding velocity record is established by identifying the exact frame in which the Vectrino red LED indicator light blinks in the camera view. The time (in seconds) at which the Vectrino begins recording in the video record is calculated as the frame number divided by the video framerate in frames per second. The video time record is then synced to the Vectrino time to create a consistent time record for both records. Person who carried out this activity:
    Robert L. Jenkins III
    U.S. Geological Survey
    Researcher III
    600 Fourth Street South
    Saint Petersburg, FL

    727-502-8138 (voice)
    727-502-8182 (FAX)
    rljenkins@usgs.gov
    Date: 24-Sep-2015 (process 6 of 7)
    Processed flow velocity was generated by extracting the along-tank component of flow velocity from the processed Vectrino 3-dimensional flow record. Free stream velocity is taken as the 3rd bin (approximately 3mm). Person who carried out this activity:
    Robert L. Jenkins III
    U.S. Geological Survey
    Researcher III
    600 Fourth Street South
    Saint Petersburg, FL

    727-502-8138 (voice)
    727-502-8182 (FAX)
    rljenkins@usgs.gov
    Date: 30-Sep-2015 (process 7 of 7)
    The time series of flow velocity was then written to text files with data arranged in columns (including headers) using matlab built-in function “fprintf.m” Person who carried out this activity:
    Robert L. Jenkins III
    U.S. Geological Survey
    Researcher III
    600 Fourth Street South
    Saint Petersburg, FL

    727-502-8138 (voice)
    727-502-8182 (FAX)
    rljenkins@usgs.gov
  3. What similar or related data should the user be aware of?
    Soulsby, R. L., 1997, Dynamics of marine sands: A manual for practical applications: Thomas Telford Publications, London, England.

    Online Links:

    Calantoni, J., Landry, B. J., and Penko, A. M., 2013, Laboratory observations of sand ripple evolution using bimodal gran size distributions under asymmetric oscillatory flows: Journal of Coastal Research Special Issue No. 65, p. 1497-1502, Coastal Education and Research Foundation, Inc., Plymouth, United Kingdom.

    Online Links:

    Dalyander, P.S., Long, J.W., Plant, N.G., and Mclaughlin, M., 2015, Nearshore dynamics of artificial sand and oil agglomerates: Marine Pollution Bulletin v.96, p. 344-355, Elsevier, Ltd., Atlanta, GA, USA.

    Online Links:


How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?
    The Vectrino acoustic Doppler profiler used to observe the oscillatory flow tunnel flow velocities measured 3-dimensional (3D) water velocity of a 4 cm profile below the instrument with 1 mm spaced bins and the distance from the instrument to the sand bed using coherent Doppler processing at a frequency of 100 Hertz (Hz). Time series of flow velocity profiles were returned at a sampling rate of 100 Hz. The Vectrino velocity profiler was mounted centrally, with the sensor in the oscillatory flow tunnel.
  2. How accurate are the geographic locations?
    A formal accuracy assessment of the horizontal positional information in the dataset has not been conducted.
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
    Velocity data is included for all of the sea floor interaction experiment segments.
  5. How consistent are the relationships among the observations, including topology?
    All flow velocities were acquired with the same Vectrino acoustic velocity profiler.

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?
Access_Constraints: None
Use_Constraints:
Public domain data from the U.S. Government are freely redistributable with proper metadata and source attribution. Please recognize the U.S. Geological Survey as the originator of the dataset.
  1. Who distributes the data set? (Distributor 1 of 1)
    Robert L. Jenkins III
    U.S. Geological Survey
    Researcher III
    600 Fourth Street South
    Saint Petersburg, Florida
    USA

    727-502-8138 (voice)
    727-502-8182 (FAX)
    rljenkins@usgs.gov
  2. What's the catalog number I need to order this data set? The zip file, 2017_309_DD_SFI_velocity.zip, contains the following text files: velocity_data_20140312_001.mp4, velocity_data_20140312_002.mp4, velocity_data_20140312_003.mp4, velocity_data_20140312_004.mp4, velocity_data_20140312_005.mp4, velocity_data_20140312_006.mp4, velocity_data_20140312_007.mp4, velocity_data_20140313_001.mp4, velocity_data_20140313_002.mp4, velocity_data_20140313_003.mp4, velocity_data_20140313_004.mp4, velocity_data_20140313_005.mp4, velocity_data_20140313_006.mp4, velocity_data_20140313_007.mp4, velocity_data_20140313_008.mp4, velocity_data_20140313_009.mp4,
  3. What legal disclaimers am I supposed to read?
    This digital publication was prepared by an agency of the United States Government. Although these data have been processed successfully on a computer system at the U.S. Geological Survey, no warranty expressed or implied is made regarding the display or utility of the data on any other system, nor shall the act of distribution imply any such warranty. The U.S. Geological Survey shall not be held liable for improper or incorrect use of the data described and (or) contained herein. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof.
  4. How can I download or order the data?
    • Availability in digital form:
      Data format: The WinZip (version 14.0) file provides flow velocity collected during small-oscillatory flow tunnel laboratory experiments at the Naval Research Laboratory, Stennis Space Center, Stennis Mississippi and the associated metadata. in format TXT (version 1) text file Size: 3.8
      Network links: https://coastal.er.usgs.gov/data-release/doi-F76D5R69/data/2017_309_DD_SFI_velocity.zip
    • Cost to order the data: none

  5. What hardware or software do I need in order to use the data set?
    This zip file contains data available in text file format (txt). The user must have software capable of reading text file format (txt) to use these data.

Who wrote the metadata?

Dates:
Last modified: 25-Apr-2019
Metadata author:
Robert L. Jenkins III
U.S. Geological Survey
Researcher III
600 Fourth Street South
Saint Petersburg, Florida
USA

727-502-8138 (voice)
727-502-8182 (FAX)
rljenkins@usgs.gov
Metadata standard:
Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)

This page is <https://cmgds.marine.usgs.gov/catalog/spcmsc/aSOA_SFI_velocity_metadata.faq.html>
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