Progress implementing a model-based iterative reconstruction algorithm for ultrasound imaging of thick concrete
Author(s) -
Hani Almansouri,
Christi Johnson,
Dwight A Clayton,
Yarom Polsky,
Charles A. Bouman,
Hector Santos-Villalobos
Publication year - 2017
Publication title -
aip conference proceedings
Language(s) - English
Resource type - Conference proceedings
eISSN - 1551-7616
pISSN - 0094-243X
DOI - 10.1063/1.4974557
Subject(s) - computer science , probabilistic logic , iterative reconstruction , electromagnetic shielding , transducer , function (biology) , algorithm , acoustics , engineering , computer vision , artificial intelligence , physics , evolutionary biology , electrical engineering , biology
All commercial nuclear power plants (NPPs) in the United States contain concrete structures. These structures provide important foundation, support, shielding, and containment functions. Identification and management of aging and the degradation of concrete structures is fundamental to the proposed long-term operation of NPPs. Concrete structures in NPPs are often inaccessible and contain large volumes of massively thick concrete. While acoustic imaging using the synthetic aperture focusing technique (SAFT) works adequately well for thin specimens of concrete such as concrete transportation structures, enhancements are needed for heavily reinforced, thick concrete. We argue that image reconstruction quality for acoustic imaging in thick concrete could be improved with Model-Based Iterative Reconstruction (MBIR) techniques. MBIR works by designing a probabilistic model for the measurements (forward model) and a probabilistic model for the object (prior model). Both models are used to formulate an objective...
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