Inferring bearing capacity from sonar backscatter: application from a muddy field site

dc.contributor.authorPark, Sun Woo
dc.date.accessioned2024-02-28T15:06:14Z
dc.date.available2024-02-28T15:06:14Z
dc.date.issued2024
dc.date.updated2024-02-26T17:09:21Z
dc.description.abstractThis study expands on the application of sediment classification using acoustic backscatter and combine it with drop penetrometer data to test if the bearing capacity of the sediment layer can be related to the backscatter intensity. Total area of 5.14 km2 was surveyed using a vessel mounted multibeam sonar and AUV mounted side scan sonar on the Potomac river near Indian Head, Maryland. 9 sediment grabs were taken during October 2022 field work, and 18 contemporaneous grab samples and drop penetrometer measurements were taken during February 2023. Backscatter mosaic with the geotechnical data was used to train a supervised classification algorithm in ArcGIS Pro. Applying the data interpretation techniques developed so far to cohesive fluvial environment has shown good agreement between backscatter intensity and bearing capacity (precision: 0.75, accuracy: 0.78). This could have practical applications in coastal and riverine construction in muddy environments, allowing for fast and cost effective analysis of bearing capacity of a large site. Unexploded ordnance (UXO) in munition test sites could also be managed using sonar surveys since ordnance mobility and burial could have improved prediction with bed bearing capacity data (Trembanis and DuVal, 2021). This coordinated geoacoustic and geotechnical survey approach would reduce the risk of UXO site management since minimal contact with the bottom is necessary.
dc.description.advisorTrembanis, Arthur C.
dc.description.degreeM.S.
dc.description.departmentUniversity of Delaware, School of Marine Science and Policy
dc.identifier.doihttps://doi.org/10.58088/vk8w-9479
dc.identifier.unique1430990696
dc.identifier.urihttps://udspace.udel.edu/handle/19716/34040
dc.language.rfc3066en
dc.publisherUniversity of Delaware
dc.relation.urihttps://www.proquest.com/pqdtlocal1006271/dissertations-theses/inferring-bearing-capacity-sonar-backscatter/docview/2937475823/sem-2?accountid=10457
dc.subjectBackscatter
dc.subjectBearing capacity
dc.subjectSediment classification
dc.subjectSonar
dc.subjectMuddy field site
dc.titleInferring bearing capacity from sonar backscatter: application from a muddy field site
dc.typeThesis

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