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Proceedings Paper

High fidelity ultrasound imaging of concrete structures
Author(s): N. Dianne Bull Ezell; S. V. Venkatakrishnan; Hani Al Mansouri; Hector Santos-Villalobos; Dan Floyd
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Paper Abstract

As plans are made to extend licenses for the aging fleet of commercial nuclear power plants for periods of sixty years and beyond, research into the long-term integrity of their concrete structures has increased. Ultrasound tomography is a useful tool for nondestructive evaluation of these concrete structures. Typically, pulse-echo measurements are made over a large surface and are processed using a reconstruction algorithm, producing a 3D image of the structure that highlights embedded defects. These measurements are processed using a delay-and-sum algorithm such as the synthetic aperture focusing technique (SAFT). Oak Ridge National Laboratory is developing novel ultrasound model-based image reconstruction (U-MBIR) algorithms to improve the imaging capability of pulse-echo ultrasound array imagers. U-MBIR is an inversion technique that reconstructs the sample under test from the ultrasound measurements by formulating and solving a mathematical optimization problem using two sets of terms: one set ensures that the reconstruction matches measured data based on a model for the physics of beam propagation with the noise in the detector, and another set ensures that the reconstruction has certain properties based on a model for the object being scanned. This paper compares three techniques: SAFT, frequency-banded SAFT (FB-SAFT), and U-MBIR. The U-MBIR method produces higher quality images of the underlying concrete structures compared to the images produced using SAFT and FB-SAFT from the same set of measurements. This paper also illustrates the detection of various defects with higher confidence due to the lower noise and artifact-free U-MBIR images.

Paper Details

Date Published: 18 March 2019
PDF: 9 pages
Proc. SPIE 10973, Smart Structures and NDE for Energy Systems and Industry 4.0, 109730S (18 March 2019); doi: 10.1117/12.2514323
Show Author Affiliations
N. Dianne Bull Ezell, Oak Ridge National Lab. (United States)
S. V. Venkatakrishnan, Oak Ridge National Lab. (United States)
Hani Al Mansouri, Purdue Univ. (United States)
Hector Santos-Villalobos, Oak Ridge National Lab. (United States)
Dan Floyd, The Univ. of Tennessee Knoxville (United States)


Published in SPIE Proceedings Vol. 10973:
Smart Structures and NDE for Energy Systems and Industry 4.0
Norbert G. Meyendorf; Kerrie Gath; Christopher Niezrecki, Editor(s)

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