Laboratory Observations of Variable Size and Shape Particles-Artificial Sand and Oil Agglomerates: June 2017 Video Data

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Frequently anticipated questions:

What does this data set describe?

Title:
Laboratory Observations of Variable Size and Shape Particles-Artificial Sand and Oil Agglomerates: June 2017 Video Data
Abstract:
Following marine oil spills, weathered oil can mix with sediment in the surf zone and settle to the seafloor to form mats up to hundreds of meters long. Wave action fragments these mats into 1- to 10-centimeter (cm) diameter sand and oil agglomerates (SOAs). SOAs can persist for years, becoming buried in or exhumed from the seafloor and/or transported cross-shore and alongshore (Dalyander and others, 2015). These fragments are angular near the source mat and become increasingly rounded as they are transported. To quantify SOA motion, the USGS conducted experiments in November 2016 (field activity number (FAN) 2016-364-DD) and June 2017 (FAN 2017-329-FA) using various size, shape, and density artificial sand and oil agglomerates (aSOAs). Video and velocity data were collected under a range of hydrodynamic forcing in the Small-Oscillatory Flow Tunnel at the U.S. Naval Research Laboratory (NRL) located in Stennis, Mississippi. Between November 14 and 18, 2016, laboratory studies were conducted on spherical- and patty-shaped particles on a roughened flat-bed. Two types of particles were used, one consisting of paraffin wax and sand while the other was machine fabricated out of aluminum and coated in sand. Between June 5 and 8, 2017, laboratory studies were conducted on spherical, patty, ellipsoidal, and angular-ellipsoidal particles using paraffin wax and sand, aluminum, and three-dimensional (3D) printed plastic particles.
Supplemental_Information:
These datasets (2017-329-FA_2017*.zip) contain MPEG-4 (.mp4) video files of particle motion and flow velocity collected during small-oscillatory flow tunnel laboratory experiments at NRL, Stennis Space Center, Mississippi. To ensure that St. Petersburg Coastal and Marine Science Center data management protocols were followed, this survey was assigned a USGS FAN, 2017-329-FA. Additional survey and data details are available at, https://cmgds.marine.usgs.gov/fan_info.php?fan=2017-329-FA.
  1. How might this data set be cited?
    U.S. Geological Survey, Nelson, Timothy R., Dalyander, P. Soupy, Frank, Donya P., Penko, Allison M., Braithwaite, Edward F. III, and Calantoni, Joseph, 20211029, Laboratory Observations of Variable Size and Shape Particles-Artificial Sand and Oil Agglomerates: June 2017 Video Data:.

    This is part of the following larger work.

    Nelson, Timothy R., Dalyander, P. Soupy, Frank, Donya P., Penko, Allison M., Braithwaite, Edward F. III, and Calantoni, Joseph, 20211029, Laboratory Observations of Variable Size and Shape Particles: Artificial Sand and Oil Agglomerates: U.S. Geological Survey data release doi:10.5066/P9Z2XFRJ, U.S. Geological Survey - St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida.

    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: 05-Jun-2017
    Ending_Date: 08-Jun-2017
    Currentness_Reference:
    ground condition
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: Video
  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?
    2017-329_FA_20170605_PT1.zip, 2017-329_FA_20170605_PT2.zip, 2017-329_FA_20170605_PT3.zip, 2017-329_FA_20170606_PT1.zip, 2017-329_FA_20170606_PT2.zip, 2017-329_FA_20170606_PT3.zip, 2017-329_FA_20170606_PT4.zip, 2017-329_FA_20170607_PT1.zip, 2017-329_FA_20170607_PT2.zip, 2017-329_FA_20170607_PT3.zip, 2017-329_FA_20170608_PT1.zip, 2017-329_FA_20170608_PT2.zip, 2017-329_FA_20170608_PT3.zip.
    Individual video files, in .mp4 format, are included in the 14 .zip files listed above, see 2017-329-FA_Data_Table.csv for additional details. Each file contains interpretive video products of sea floor interaction experiments video data with graphical representations of flow velocity. (Source: U.S. Geological Survey)
    Experiment Time (s)
    Video record time of experiment run; this variable is displayed along the horizontal axis of the animated, bottom-panel graphic. (Source: U.S. Geological Survey)
    Range of values
    Minimum:0
    Maximum:766.6666
    Units:seconds
    Video Footage
    Video observations of experiment run. (Source: U.S. Geological Survey) Recorded footage of the experiment is included in each .mp4 file; the video is positioned in the top panel.
    Water Velocity (m/s)
    Smoothed, blue line representing along-tank water velocity as measured by the Vectrino velocity profiler, in m/s, during the experiment segment. (Source: U.S. Geological Survey) Record of water velocity, which coincides with video record time period is positioned in the bottom panel along the vertical axis.
    Current Time in Video
    An orange dot observed in the animated, bottom-panel graphic, indicates the instantaneous velocity that coincides with the current conditions presented in the [top panel] video footage. (Source: U.S. Geological Survey) Indicates the instantaneous video time and adjusted water velocity, which coincide with the current conditions presented in the video footage. This attribute does not represent the Vectrino record time and instances where no water velocity data is present (these are visible as blank areas near the beginning and end of the experiment timeline) indicates periods of either poor data quality or the Vectrino was not recording.
    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 were 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
    • Timothy R. Nelson
    • P. Soupy Dalyander
    • Donya P. Frank
    • Allison M. Penko
    • Edward F. Braithwaite III
    • Joseph Calantoni
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    Timothy R. Nelson
    Cherokee Nation Systems Solutions/U.S. Geological Survey
    Researcher VII
    600 Fourth Street South
    Saint Petersburg, Florida
    USA

    727-502-8098 (voice)
    727-502-8002 (FAX)
    trnelson@usgs.gov

Why was the data set created?

This dataset presents along-tank flow velocity and video observations, in MPEG-4 (.mp4) format, of aSOA particle motion captured with five cameras in June 2017. Along-tank flow velocities were collected by a single Vectrino acoustic Doppler profiler located centrally in the small-oscillatory flow tunnel housed at the NRL, Stennis Space Center, Mississippi. The videos provide information about the flow conditions present during various phases of particle mobility (incipient, rocking, and rolling/overturning). Each video file contains a unique name consisting of the experiment run number and trial, which is related to the corresponding video. Video containing the same particles on the same day are archived together in a zip file. Additional experimental settings are located in 2017-329-FA_Data_Table.csv and Data_Dictionary.csv.

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: 05-Jun-2017 (process 1 of 10)
    In June 2017, experiments were conducted at NRL's Sediment Dynamics Laboratory, located in Stennis, MS. Particles with spherical, patty, ellipsoidal, and angular-ellipsoidal shapes representing aSOAs were deployed in the small-oscillatory flow tunnel with a cross-sectional area of 25 cm by 25 cm and a test bed length of 2-meters (m). Oscillating currents (simulating bottom velocities generated by waves) were driven in the tank by a flywheel with variable frequencies (5-90 rotations per minute) and stroke lengths (22, 33, or 44 cm). Five cameras (two Canon 7D DSLR and three GoPro Hero3+ were mounted outside the tank to record particle movement, in HD, at 29.97 fps and 1920x1080 pixel resolution. Camera A (Canon 7D) was outfitted with an 18-55 mm zoom lens at a 29 mm focal length and Camera B (Canon 7D) used an 18 mm fisheye lens. The GoPros (GP01, GP02, and GP03) were outfitted with the default fisheye lens. Recording was triggered with a hardwired camera switchfor Cameras A and B, while the GoPro Apple iOS application was used to wirelessly trigger the three GoPro cameras. A Nortec Vectrino Doppler current profiler was installed, centrally, within the flow tunnel with the sensor submerged in the water. Detailed information of the Small-Oscillatory Flow Tunnel can be found in Calantoni and others (2013). Person who carried out this activity:
    Timothy R. Nelson
    Cherokee Nation Systems Solutions/U.S. Geological Survey
    Researcher VII
    600 4th St. S
    Saint Petersburg, FL
    USA

    727-502-8098 (voice)
    727-502-8182 (FAX)
    trnelson@usgs.gov
    Date: 05-Jun-2017 (process 2 of 10)
    Videos were captured by the five HD cameras. Video recording was started remotely, prior to the flow tunnel fly-wheel motor being turned on and prior to the Vectrino Profiler being started. On some occurrences, recording and/or the Vectrino were restarted, due to video length limitations or errors. For these instances, the fly-wheel motor was not stopped and recording began with the motor continuing to run. Person who carried out this activity:
    Timothy R. Nelson
    Cherokee Nation Systems Solutions/U.S. Geological Survey
    Researcher VII
    600 Fourth Street South
    Saint Petersburg, Florida
    USA

    727-502-8098 (voice)
    727-502-8001 (FAX)
    trnelson@usgs.gov
    Date: 05-Jun-2017 (process 3 of 10)
    Velocities were logged by a Vectrino acoustic Doppler profiler centrally-mounted within the tank. Velocity recording was remotely started from a connected computer 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, which was in the field of view of all cameras. 3D velocity was logged by the Vectrino software package and saved as raw binary files with file extension ".ntk" and a MATLAB version 2018b-readable format ".mat". The Vectrino acoustic velocity profiler measured the 3D water velocity (meters per second, m/s) of a 3.5 cm profile below the instrument, with 1-mm spaced bins and a sampling rate of 100 Hz. Person who carried out this activity:
    Timothy R. Nelson
    Cherokee Nation Systems Solutions/U.S. Geological Survey
    Researcher VII
    600 Fourth Street South
    Saint Petersburg, Florida
    USA

    727-502-8098 (voice)
    727-502-8001 (FAX)
    trnelson@usgs.gov
    Date: 05-Jun-2017 (process 4 of 10)
    Raw Vectrino data were processed in MATLAB by a script called "VectrinoII_ProcessData_2017.m" (modified NRL script), which extracted time, depth information, 3D velocity (m/s), and temperature from the ".mat" data files created by the Vectrino software. Noise and data spikes were removed from the 3D velocity data using two methods. First, the raw time-series data were compared to a smoothed time-series that was calculated by using an evenly-weighted convolution filter with a window size of 10. A standard deviation was calculated from the difference between the raw and smoothed time-series. Any raw sample with a difference greater than three standard deviations was replaced with the smoothed value. A new smoothed time-series was then calculated from the de-spiked time-series. This process was repeated two additional times using the de-spiked time-series in place of the raw data. Next, any sample recorded with a correlation (a measure of signal quality calculated by the Vectrino profiler software) less than 70% were replaced in the record with non-number (NaN) values. Quality controlled records of de-spiked and smoothed de-spiked velocity, temperature, distance from transducer, distance from bed, and sample time were saved in MATLAB readable ".mat" files. Person who carried out this activity:
    Timothy R. Nelson
    Cherokee Nation Systems Solutions/U.S. Geological Survey
    Researcher VII
    600 Fourth Street South
    Saint Petersburg, Florida
    USA

    727-502-8098 (voice)
    727-502-8001 (FAX)
    trnelson@usgs.gov
    Date: 05-Jun-2017 (process 5 of 10)
    Raw video frames were converted to individual individual Joint Photographic Experts Group (JPEG) image files utilizing MATLAB's built-in function, "VideoReader". Each frame of the raw video was read into MATLAB and saved as a unique, numbered and ordered JPEG image. The frames for Camera A and Camera B were rotated 180 degrees, since the cameras were mounted upside-down. The series of JPEG images were saved automatically to a unique directory named for the experiment date and run number identifier. The video frame rate was saved into a separate ".mat" file and saved into the same folder as the video image sequence. Person who carried out this activity:
    Timothy R. Nelson
    Cherokee Nation Systems Solutions/U.S. Geological Survey
    Researcher VII
    600 Fourth Street South
    Saint Petersburg, Florida
    USA

    727-502-8098 (voice)
    727-502-8001 (FAX)
    trnelson@usgs.gov
    Date: 16-Jun-2017 (process 6 of 10)
    Time differences between the video and corresponding velocity record were established by identifying the exact frame in which the Vectrino's red LED indicator light blinked in the camera's view. This instance was first estimated automatically by creating a unique digital mask around the LED for each camera. Since the cameras were fixed, the mask remained the same for every video. When a red flash was identified in the masked frame, that frame was saved to a ".mat" file unique to the experiment run. Once an estimated frame was found for all videos, the corresponding frames for each camera and each run were viewed to visually verify a red flash was captured. For instances were no flash was detected or an incorrect frame was picked, the correct frame was identified manually and the ".mat" file was updated. The time (in seconds) at which the Vectrino began recording in the video record was calculated as the frame number divided by the video frame rate. The start frame for the Vectrino in each video file is provided in 2017-329-FA_Data_Table.csv. Person who carried out this activity:
    Timothy R. Nelson
    Cherokee Nation Systems Solutions/U.S. Geological Survey
    Researcher VII
    600 Fourth Street South
    Saint Petersburg, Florida
    USA

    727-502-8098 (voice)
    727-502-8001 (FAX)
    trnelson@usgs.gov
    Date: 05-Aug-2017 (process 7 of 10)
    Flow velocity input for the video product was generated by extracting the along-tank component of flow velocity from the processed Vectrino 3D flow record. Free stream velocity was taken as an average of the Vectrino velocity bins, excluding any bins with erroneous velocities (such as constant zero or near zero values) or out of phase velocities compared to adjacent bins. These erroneous values might be a result of interference with the side of the tank, reflections off particles, or transfer issues. Transfer issues resulted when the computer used to record the Vectrino data in real-time was also performing additional tasks or data transfer. The bins used to calculate the average for each experiment run are listed in 2017-329-FA_Data_Table.csv. Due to storage limitations, excessively long Vectrino records were split into two files by the Vectrino software. These files were merged after processing into a continuous time-series. Person who carried out this activity:
    Timothy R. Nelson
    Cherokee Nation Systems Solutions/U.S. Geological Survey
    Researcher VII
    600 Fourth Street South
    Saint Petersburg, Florida
    USA

    727-502-8098 (voice)
    727-502-8001 (FAX)
    trnelson@usgs.gov
    Date: 19-Sep-2019 (process 8 of 10)
    Each flow velocity time-series was visually quality controlled (QC) for instances of transfer interference or tunnel maintenance which resulted in erroneous velocity values. Transfer errors occurred when data was transferred between disk drives on the desktop computer while the Vectrino was transferring data to the same computer. For the identified instances, the velocity was assigned a NaN value. Person who carried out this activity:
    Timothy R. Nelson
    Cherokee Nation Systems Solutions/U.S. Geological Survey
    Researcher VII
    600 Fourth Street South
    Saint Petersburg, Florida
    USA

    727-502-8098 (voice)
    727-502-8001 (FAX)
    trnelson@usgs.gov
    Date: 11-Jan-2020 (process 9 of 10)
    Interpretive video products were created in MATLAB v2018b and FFMPEG with an output file type of MPEG-4, using h264, at a FFMPEG constant quality of 15, a frame rate equal to the raw video frame rate, and resolution of 1080x1920 pixels. For each frame in the video, a figure was created consisting of the video frame from a single camera in the upper panel and the corresponding velocity time series in the bottom panel. A unique mask was created for each video camera to remove personnel and laboratory equipment not related to the transport of SOAs for privacy issues. Each mask was created using Matlab v2018b built in function "ginput" to create a polygon encompassing the small-oscillatory flow tunnel. Any pixel outside the polygon was assigned a red-green-blue pixel value of [0, 0, 0] (black). The video panel reduces the video resolution to approximately 830x1480. The velocity time series is displayed over a moving two-minute window with an orange dot indicating the current time in the video. The velocity time was adjusted to the video time by dividing the frame when the LED flash was detected in the video by the video frame rate. Only the velocity time series corresponding to collected video is shown. The current time indicator is centered in the bottom panel with the exception of the first minute and last minute of the video. The figure was saved as a portable network graphic ".png" file in a unique folder for each date, run, and camera. This was repeated for each frame in the video, then for each camera in a run, and then for all runs. A video was then created using FFMPEG for all frames for the unique date, run, camera combination using all frames in the selected folder. Each video has the format RunID_Camera.mp4, where RunID is a unique run identification code indicating a specific set of sediment, flow symmetry, and stroke length and is described in 2017-329-FA_Data_Table.csf. RunID ends with the Trial Number which consists of the letter, "T" followed by a sequential number starting at 1. Trial indicates the sediment type in the tank, flow symmetry, and stroke length remained unchanged. This occurred when the length of the video approached the limits of the camera's storage, there was concern regarding the Vectrino data quality, or a leak was observed in the tank. Camera is either CamA for Camera A, CamB for Camera B, GP01 for GoPro 1, or GP02 for GoPro 2. Trial indicates the sediment and tank configuration remained unchanged. Person who carried out this activity:
    Timothy R. Nelson
    Cherokee Nation Systems Solutions/U.S. Geological Survey
    Researcher VII
    600 Fourth Street South
    Saint Petersburg, Florida
    USA

    727-502-8098 (voice)
    727-502-8001 (FAX)
    trnelson@usgs.gov
    Date: 05-Mar-2020 (process 10 of 10)
    The video files were grouped by date and aSOA size prior to being archived within compressed ZIP (.zip) files. The filename convention utilized for each .zip file was: FAN_DATE_PT#, where FAN is the Field Activity Number (2016-364-DD), DATE is in the form YYYYMMDD where YYYY is the four-digit year, MM is the two-digit month, DD is the two-digit day, and PT# indicates the file grouping by sediment type for the day. Detailed information about which files are included in each archive, as well as sediment and tank settings, can be found in 2017-329-FA_Data_Table.csv. Person who carried out this activity:
    Timothy R. Nelson
    Cherokee Nation Systems Solutions/U.S. Geological Survey
    Researcher VII
    600 Fourth Street South
    Saint Petersburg, Florida
    USA

    727-502-8098 (voice)
    727-502-8001 (FAX)
    trnelson@usgs.gov
  3. What similar or related data should the user be aware of?
    Calantoni, J., Landry, B.J., and Penko, A.M., 20130401, Laboratory observations of sand ripple evolution using bimodal grain 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., Plant, N.G., Long, J.W., and Mclaughlin, M., 20150505, Nearshore dynamics of artificial sand and oil agglomerates: Marine Pollution Bulletin Volume 96, Issues 1-2, 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?
    Two Canon 7D digital single-lens reflex (DSLR) (Camera A and Camera B) and three GoPro Hero3+ cameras (GP01, GP02, and GP03), captured high-definition (HD) video to assist USGS researchers with observations of particle motion within the oscillatory flow tunnel located at NRL.. Camera A was outfitted with an 18-55 millimeter (mm) zoom lens at 29 mm focal length while Camera B used an 18 mm fisheye lens. Both Canon 7D DSLR cameras recorded at a resolution of 1920x1088 pixels and a frame rate of 29.97 frames per second (fps). The GoPro cameras were outfitted with the default fisheye lens and recorded in 1920x1080 resolution at 29.97 fps.. All cameras were remotely triggered to reduce user-induced movement and vibration within the videos.
  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?
    Video data is included for all experiments, and experiment segments. This dataset is considered complete for the information presented, as described in the abstract section. Users are advised to read the rest of the metadata record carefully for additional details.
  5. How consistent are the relationships among the observations, including topology?
    All videos were acquired with the same cameras described above. The cameras were mounted outside of the oscillatory flow tunnel.

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)
    Timothy R. Nelson
    Cherokee Nation Systems Solutions/U.S. Geological Survey
    Researcher VII
    600 Fourth Street South
    Saint Petersburg, Florida
    USA

    727-502-8098 (voice)
    727-502-8182 (FAX)
    trnelson@usgs.gov
  2. What's the catalog number I need to order this data set? For video file name information, please see 2017-329-FA_Data_Table.csv, which is included in the supplemental information section of the data release.
  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: This dataset provides experiment video data with a graphical representation of flow velocity. Images were collected during small-oscillatory flow tunnel laboratory experiments at the Naval Research Laboratory, Stennis Space Center, Stennis Mississippi and includes the associated metadata. in format MP4 (version 1) MPEG-4 video file
      Network links: https://coastal.er.usgs.gov/data-release/doi-P9Z2XFRJ/
    • Cost to order the data: None

  5. What hardware or software do I need in order to use the data set?
    Zip files contains data available in MPEG-4 (MP4) video file format. The user must have software capable of reading .mp4 video file format to use these data.

Who wrote the metadata?

Dates:
Last modified: 01-Nov-2021
Metadata author:
Timothy R. Nelson
Cherokee Nation Systems Solutions/U.S. Geological Survey
Researcher VII
600 Fourth Street South
Saint Petersburg, Florida
USA

727-502-8098 (voice)
727-502-8182 (FAX)
trnelson@usgs.gov
Metadata standard:
Content Standard for Digital Geospatial Metadata (FGDC-STD-001-1998)
This page is <https://cmgds.marine.usgs.gov/catalog/spcmsc/2017-329-FA_video_metadata.faq.html>
Generated by mp version 2.9.50 on Mon Nov 1 10:21:25 2021