High-resolution subsurface imaging and neural network recognition: Non-intrusive buried substance location. Final report, January 26, 1997

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A high-frequency, high-resolution electromagnetic (EIVI) imaging system has been developed for environmental geophysics surveys. Some key features of this system include: (1) rapid surveying to allow dense spatial sampling over a large area, (2) high-accuracy measurements which are used to produce a high-resolution image of the subsurface, (3) measurements which have excellent signal-to-noise ratio over a wide bandwidth (31 kHz to 32 MHZ), (4) elimination of electric-field interference at high frequencies, (5) large-scale physical modeling to produce accurate theoretical responses over targets of interest in environmental geophysics surveys, (6) rapid neural network interpretation at the field site, and (7) visualization ... continued below

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177 p.

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Sternberg, B.K. & Poulton, M.M. December 31, 1998.

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Description

A high-frequency, high-resolution electromagnetic (EIVI) imaging system has been developed for environmental geophysics surveys. Some key features of this system include: (1) rapid surveying to allow dense spatial sampling over a large area, (2) high-accuracy measurements which are used to produce a high-resolution image of the subsurface, (3) measurements which have excellent signal-to-noise ratio over a wide bandwidth (31 kHz to 32 MHZ), (4) elimination of electric-field interference at high frequencies, (5) large-scale physical modeling to produce accurate theoretical responses over targets of interest in environmental geophysics surveys, (6) rapid neural network interpretation at the field site, and (7) visualization of complex structures during the survey. Four major experiments were conducted with the system: (1) Data were collected for several targets in our physical modeling facility. (2) We tested the system over targets buried in soil. (3) We conducted an extensive survey at the Idaho National Engineering Laboratory (INEL) Cold Test Pit (CTP). The location of the buried waste, category of waste, and thickness of the clay cap were successfully mapped. (4) We ran surveys over the acid pit at INEL. This was an operational survey over a hot site. The interpreted low-resistivity region correlated closely with the known extent of the acid pit.

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177 p.

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INIS; OSTI as DE98002010

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  • Other Information: PBD: [1998]

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  • Other: DE98002010
  • Report No.: DOE/MC/29101--5801
  • Grant Number: AC21-92MC29101
  • DOI: 10.2172/589268 | External Link
  • Office of Scientific & Technical Information Report Number: 589268
  • Archival Resource Key: ark:/67531/metadc691599

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  • December 31, 1998

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  • Aug. 14, 2015, 8:43 a.m.

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  • June 13, 2016, 7:42 p.m.

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Sternberg, B.K. & Poulton, M.M. High-resolution subsurface imaging and neural network recognition: Non-intrusive buried substance location. Final report, January 26, 1997, report, December 31, 1998; United States. (digital.library.unt.edu/ark:/67531/metadc691599/: accessed October 21, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.