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The study presents a basic framework for structural integrity assessment using synthetic aperture focusing technique and the extended finite element method. Synthetic aperture focusing technique (SAFT) is used to acquire detailed descriptions of three-dimensional flaws in engineering structures. Flaws extracted from SAFT can readily be represented as a surface mesh or a volume mesh. The mesh is integrated into a normal structural finite element model (FEM) via level set method to formulate an XFEM problem. Applying the cyclic fatigue load and solving the problem provides essential quantities for evaluation of the stress intensity factor (SIF), serving as a driven force of crack growth. The crack front is updated using crack growth equations, such as Paris' equation and its variants under cyclic loading condition. The result is considered to be accurate due to the fact that, for one thing it can minimize the uncertainty in quantification of three-dimensional flaws, and for another it provides a highly reliable solution to SIF for any point in the crack front under mixed mode loading conditions. Combination of the two components allows for removal of approximations and over conservativeness in conventional ultrasound based structural integrity assessment. [ABSTRACT FROM AUTHOR]

The study presents a data processing methodology for weld build-up using multiple scan patterns. To achieve an overall high probability of detection for flaws with different orientations, an inspection procedure with three different scan patterns is proposed. The three scan patterns are radial-tangential longitude wave pattern, axial-radial longitude wave pattern, and tangential shear wave pattern. Scientific fusion of the inspection data is implemented using volume reconstruction techniques. The idea is to perform spatial domain forward data mapping for all sampling points. A conservative scheme is employed to handle the case that multiple sampling points are mapped to one grid location. The scheme assigns the maximum value for the grid location to retain the largest equivalent reflector size for the location. The methodology is demonstrated and validated using a realistic ring of weld build-up. Tungsten balls and bars are embedded to the weld build-up during manufacturing process to represent natural flaws. Flat bottomed holes and side drilled holes are installed as artificial flaws. Automatic flaw identification and extraction are demonstrated. Results indicate the inspection procedure with multiple scan patterns can identify all the artificial and natural flaws. [ABSTRACT FROM AUTHOR]

The study presents a method and application of risk assessment methodology for turbine rotor fatigue failure using probabilistic ultrasonic nondestructive evaluations. A rigorous probabilistic modeling for ultrasonic flaw sizing is developed by incorporating the model-assisted probability of detection, and the probability density function (PDF) of the actual flaw size is derived. Two general scenarios, namely the ultrasonic inspection with an identified flaw indication and the ultrasonic inspection without flaw indication, are considered in the derivation. To perform estimations for fatigue reliability and remaining useful life, uncertainties from ultrasonic flaw sizing and fatigue model parameters are systematically included and quantified. The model parameter PDF is estimated using Bayesian parameter estimation and actual fatigue testing data. The overall method is demonstrated using a realistic application of steam turbine rotor, and the risk analysis under given safety criteria is provided to support maintenance planning. [ABSTRACT FROM AUTHOR]

Ultrasonic Synthetic Aperture Focusing Technique (SAFT) reconstruction method is developed to provide high-resolution images of the inspected areas and volumes. The basic idea of the method is to coherently superimpose multiple A-scan measurements, incorporating the phase information of the sampling points. The method involves two major steps: data mapping according to time-of-flight (ToF), and local normalizing. Data mapping refers to the process of mapping each of the sampling points to a three-dimensional grid that represents the geometry model of the object being inspected. The value for each cell of the grid is a summation of all sampling points mapped into the cell. Local normalizing refers to normalizing a selected region of interest (ROI) for defect visualization and quantification. Lab experiments are performed using a 10MHz phased array ultrasonic probe to collect data from a cylinder material block. The method is used to process the experimental data. Using the developed method, spatial resolution of inspection is significantly improved comparing with traditional reconstruction methods. Results indicate that four closely spaced 0.794mm-diameter flat-bottomed holes are clearly identified. [ABSTRACT FROM AUTHOR]

The automatic extraction and labeling of the rib centerlines is a useful yet challenging task in many clinical applications. In this paper, we propose a new approach integrating rib seed point detection and template matching to detect and identify each rib in chest CT scans. The bottom-up learning based detection exploits local image cues and top-down deformable template matching imposes global shape constraints. To adapt to the shape deformation of different rib cages whereas maintain high computational efficiency, we employ a Markov Random Field (MRF) based articulated rigid transformation method followed by Active Contour Model (ACM) deformation. Compared with traditional methods that each rib is individually detected, traced and labeled, the new approach is not only much more robust due to prior shape constraints of the whole rib cage, but removes tedious post-processing such as rib pairing and ordering steps because each rib is automatically labeled during the template matching. For experimental validation, we create an annotated database of 112 challenging volumes with ribs of various sizes, shapes, and pathologies such as metastases and fractures. The proposed approach shows orders of magnitude higher detection and labeling accuracy than state-of-the-art solutions and runs about 40 seconds for a complete rib cage on the average. [ABSTRACT FROM PUBLISHER]