International Federation of Digital Seismograph Networks

X5 (2018-2018): Determining the Shear Wave Velocity structure of Shallow Marine Sediments utilizing the MASW method

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FDSN Network Information

FDSN code X5 (2018-2018) Network name Determining the Shear Wave Velocity structure of Shallow Marine Sediments utilizing the MASW method (MASW in Shallow Marine Sediments)
Start year 2018 Operated by
  • University of North Florida (UNF), United States of America
End year 2018 Deployment region -
Description

Experiment intent is to utilize the Multi-channel Analysis of Surface Waves (MASW) method to determine the shear wave velocity structure and, ultimately, the correlated SPT blow count and bearing capacity of shallow marine sediments for pile driving suitability. The experimental setup includes a marine seismic source, a 24-channel hydrophone array/streamer, data analysis software (all procured separately by this investigator) as well as a seismograph and associated software (nature of this request, specifically interested in the Geode 24 seismograph and associated field laptop with data acquisition software) to acquire Scholte surface waves excited by the seismic source. The experiment is currently planned to be conducted at three sites: 1) Validation tests conducted on campus at the University of North Florida in Jacksonville, FL, 2) Marine site located within or near the Little Talbot Island State Park in Jacksonville, FL, 3) Florida Department of Transportation marine pile driving test sites in the Jacksonville area (exact location to be determined). The overall goal of the project is to: 1) Successfully operate the experimental setup/proof of concept of MASW equipment package in shallow marine waters, 2) Compare MASW shear wave velocity and SPT blow count determinations to FDOT soil reports and boring logs for comparison and validation of MASW method, 3) Compare MASW shear wave velocity and SPT blow count determinations to U.S. Navy geotechnical testing for comparison and validation.

Citation Information

Digital Object Identifier (DOI) 10.7914/SN/X5_2018
Citation
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