Mechanical and Microstructural Assessment of Inhomogeneities in Oxide Ceramic Matrix Composites Detected by Air-Coupled Ultrasound Inspection

Ceramic Matrix Composites (CMC) are promising materials for high-temperature applications where damage tolerant failure behavior is required. Non-destructive testing is essential for process development, monitoring, and quality assessment of CMC parts. Air-coupled ultrasound (ACU) is a fast and cost-efficient tool for non-destructive inspections of large components with respect to the detection of material inhomogeneities. Even though ACU inspection is usually used for visual inspection, the interpretation of C-scan images is often ambiguous with regard to critical defects and their impact on local material properties. This paper reports on a new approach to link the local acoustic damping of an oxide CMC plate obtained from ACU analysis with subsequent destructive mechanical testing and microstructural analyses. Local damping values of bending bars are extracted from ACU maps and compared with the results of subsequent resonant frequency damping analysis and 3-point bending tests. To support data interpretation, the homogeneous and inhomogeneous CMC areas detected in the ACU map are further analyzed by X-ray computed tomography and scanning electron microscopy. The results provide strong evidence that specific material properties such as Young’s modulus are not predictable from ACU damping maps. However, ACU shows a high, beneficial sensitivity for narrow but large area matrix cracks or delaminations, i.e., local damping is significantly correlated with specific properties such as shear moduli and bending strengths.

Ultrasound Assessment of Honey Using Fast Fourier Transform

Ultrasound inspection permits the characteristics of some foodstuffs to be determined easily and cheaply. This experimental study included the determination of various ultrasound parameters provided by the fast Fourier transform (FFT) which had not previously been considered in testing the physical properties of different varieties of honey. These parameters are practically independent of the criteria adopted for their calculation, unlike other ultrasound variables such as pulse velocity or attenuation whose determination can vary depending on those criteria. The study was carried out on four varieties of honey (Eucalyptus, Heather, Thyme, and Thousand Flowers) using 500-kHz transducers. A simultaneously performed honey texture analysis (Texture Profile Analysis-TPA) showed significant linear correlations between the ultrasound variables provided by FFT and the texture parameters. The FFT parameters distinguished between each of the four honey varieties studied.

A Bayesian Approach to Risk-Based Autonomy for a Robotic System Executing a Sequence of Independent Tasks

Enabling higher levels of autonomy requires an increased ability to identify and handle internal faults and unforeseen changes in the environment. This work presents an approach to improve this ability for a robotic system executing a series of independent tasks, such as inspection, sampling, or intervention, at different locations. A dynamic decision network (DDN) is used to infer the presence of internal faults and the state of the environment by fusing information over time. This knowledge is used to make risk-informed decisions enabling the system to proactively avoid failure and to minimize the consequence of faults. Past states are evaluated with new information to identify and counteract previous sub-optimal actions. A case study on an inspection drone tasked with contact-based ultrasound inspection is presented. The case study successfully demonstrates the proposed capabilities while minimizing time use and maximizing mission completion.

Permanent Deformation and Stiffness Degradation of Open Hole Glass/PA6 UD Thermoplastic Composite in Tension and Compression

UD glass/PA6 coupons with an open hole are subjected to tensile and compressive loading. Three layups: [0/90]5s, [+45/−45]5s and [+45/0/−45/90]3s with a shape based on ASTM D5766 were tested. Both monotonic loading as well as loading–unloading–reloading tests were executed. The strain field on the sample surface was measured with digital image correlation. This allowed identifying the distribution of the strain field during loading, permanent deformation and the evolution of the sample elastic modulus. This information is not frequently measured. Yet, it is vital for the development and validation of advanced failure models. The results indicate that the thermoplastic matrix allows large plastic deformation under tensile loading for the specimens with layup [+45/−45]5s. In addition, the specimen elastic modulus reduces by about 70%. The other layups show minor permanent deformation, while the elastic modulus reduces by up to 15%. Furthermore, the quasi-isotropic laminate shows a significant post-failure load-bearing capacity under compression loading. The results are complemented with post-mortem damage and fracture observations using optical microscopy and ultrasound inspection.

Caracterización dimensional con ultrasonido por arreglo de fases de discontinuidades inducidas en acero ASTM A36 mediante procesos de electroerosión y soldadura SMAW

This research evaluates the effect of the variables of Phased Array Ultrasonic Testing(PAUT) on the sectoral angular beam scans “S-Scan” and the geometric morphology of planar discontinuities such as the inclination forthe ultrasonic beam and the shape of the extremity on accuracy in measurements. The study was carried out in two stages. Duringthe first stage, eight ASTM A36 steel samples with machined notches by penetration from EDM and a welded sample with lack of penetration in a butt weld were designed and produced. In the second stage, it wasmeasured the size of the discontinuities using ultrasound inspection and different configurations of the phase arrangement. The effect of each variable and inspection setting with errors between 0.2 % and 120 % were determined by statistical analysis.

On the bandwidth and beam profile characteristics of a simple low frequency collimated ultrasound beam source

We numerically investigate the bandwidth and collimation characteristics of ultrasound beams generated by a simple collimated ultrasound beam source that consists of a piezoelectric disk operated near its radial mode resonances. We simulate the ultrasound beam generated in a fluid medium as a function of the excitation frequency for two cases: 1) free piezoelectric disk that corresponds to zero-traction along the lateral edge, and 2) fixed piezoelectric disk that corresponds to zero-displacement along the lateral edge. We present and discuss the physical mechanism underpinning the frequency-dependent collimation and bandwidth properties of the ultrasound beams. We observe that the collimated beam generated by the free disk repeatedly lengthens/shortens and also extends/retracts sidelobes with increasing frequency. Alternatively, fixing the piezoelectric disk results in a consistent beam profile shape across a broad range of frequencies. This facilitates generating broadband signals such as a Gaussian pulse or chirp, which are common in ultrasound imaging. Thus, the fixed piezoelectric disk finds application as a collimated ultrasound beam source in a wide range of applications including medical ultrasound imaging, scanning acoustic microscopy, sonar detection, and other nondestructive ultrasound inspection techniques.

ULTRASOUND INSPECTION OF COMPOSITE MATERIAL PRODUCTS

Polymer composite materials are used in modern rocket and space engineering, but the question of technical diagnostics of such products is very acute. The study of PCM products showed that the use of a portable ultrasonic flaw detector with high-frequency transducers is possible, but on small particles (product areas) of control.

A Bayesian Approach to Risk-Based Autonomy for a Robotic System Executing a Sequence of Independent Tasks

Enabling higher levels of autonomy requires an increased ability to identify and handle internal faults and unforeseen changes in the environment. This work presents an approach to improve this ability for a robotic system that is executing a series of independent tasks, such as inspection, sampling, or intervention, at different locations. A dynamic decision network (DDN) is used to infer the presence of internal faults and the state of the environment based on the available measurements. This knowledge is used to evaluate the risk of executing the current task, which is used to evaluate whether the task should be executed or skipped and whether maintenance actions are needed. Evaluating past states given new information is used to identify skipped tasks that should be revisited. The proposed approach is implemented for a drone tasked with contact-based ultrasound inspection of an industrial facility. The drone is able to successfully distinguish between different internal faults and adverse environmental states and act accordingly. The system makes risk-informed decisions based on uncertain knowledge, enabling it to minimize the time usage while minimizing the potential of harming the drone and maximizing mission completion.<br>

A Bayesian Approach to Risk-Based Autonomy for a Robotic System Executing a Sequence of Independent Tasks

Enabling higher levels of autonomy requires an increased ability to identify and handle internal faults and unforeseen changes in the environment. This work presents an approach to improve this ability for a robotic system that is executing a series of independent tasks, such as inspection, sampling, or intervention, at different locations. A dynamic decision network (DDN) is used to infer the presence of internal faults and the state of the environment based on the available measurements. This knowledge is used to evaluate the risk of executing the current task, which is used to evaluate whether the task should be executed or skipped and whether maintenance actions are needed. Evaluating past states given new information is used to identify skipped tasks that should be revisited. The proposed approach is implemented for a drone tasked with contact-based ultrasound inspection of an industrial facility. The drone is able to successfully distinguish between different internal faults and adverse environmental states and act accordingly. The system makes risk-informed decisions based on uncertain knowledge, enabling it to minimize the time usage while minimizing the potential of harming the drone and maximizing mission completion.<br>