  One-sided ultrasonic non-destructive evaluation (UNDE) is extensively used to
characterize structures that need to be inspected and maintained from defects
and flaws that could affect the performance of power plants, such as nuclear
power plants. Most UNDE systems send acoustic pulses into the structure of
interest, measure the received waveform and use an algorithm to reconstruct the
quantity of interest. The most widely used algorithm in UNDE systems is the
synthetic aperture focusing technique (SAFT) because it produces acceptable
results in real time. A few regularized inversion techniques with linear models
have been proposed which can improve on SAFT, but they tend to make simplifying
assumptions that do not address how to obtain reconstructions from large real
data sets. In this paper, we propose a model-based iterative reconstruction
(MBIR) algorithm designed for scanning UNDE systems. To further reduce some of
the artifacts in the results, we enhance the forward model to account for the
transmitted beam profile, the occurrence of direct arrival signals, and the
correlation between scans from adjacent regions. Next, we combine the forward
model with a spatially variant prior model to account for the attenuation of
deeper regions. We also present an algorithm to jointly reconstruct
measurements from large data sets. Finally, using simulated and extensive
experimental data, we show MBIR results and demonstrate how we can improve over
SAFT as well as existing regularized inversion techniques.
