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ASME J Nondestructive Evaluation. 2018;1(4):041001-041001-10. doi:10.1115/1.4040233.

The U.S. Air Force seeks to improve lifecycle management of composite structures. Nondestructive characterization of damage is a key input to this framework. One approach to characterization is model-based inversion of ultrasound inspection data; however, the computational expense of simulating the response from damage represents a major hurdle for practicality. A surrogate forward model with greater computational efficiency and sufficient accuracy is, therefore, critical to enable damage characterization via model-based inversion. In this work, a surrogate model based on Gaussian process regression (GPR) is developed on the chirplet decomposition of the simulated quasi-shear scatter from delamination-like features that form a shadowed region within a representative composite layup. The surrogate model is called in the solution of the inverse problem for the position of the hidden delamination, which is achieved with <0.5% error in <20 min on a workstation computer for two unique test cases. These results demonstrate that solving the inverse problem from the ultrasonic response is tractable for composite impact damage with hidden delaminations.

Commentary by Dr. Valentin Fuster
ASME J Nondestructive Evaluation. 2018;1(4):041002-041002-4. doi:10.1115/1.4040471.

This paper deals with an application of the Yule series model for contactless (blade tip timing, BTT) measurements. The approach creates a straightforward processing procedure from the experimental data to obtain estimates of blade logarithmic decrement and natural frequency. The existing analytical expressions for confidence intervals enable a priori evaluation for the accuracy of blade oscillation characteristics estimates. Proposed sensors allocation scheme ensures oscillation sampling rates providing efficient estimates of oscillation characteristics. Real-time measurements of blade logarithmic decrement and natural frequency give a chance of this method implementation for research and health monitoring purposes.

Commentary by Dr. Valentin Fuster
ASME J Nondestructive Evaluation. 2018;1(4):041003-041003-14. doi:10.1115/1.4040390.
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The correlation between the nonlinear acousto-ultrasonic response and the progressive accumulation of fatigue damage is investigated for an additively manufactured aluminum alloy AlSi7Mg and compared with the behavior of a conventional wrought aluminum alloy 6060-T5. A dual transducer and wedge setup is employed to excite a 30-cycle Hann-windowed tone burst at a center frequency of 500 kHz in plate-like specimens that are 7.2 mm thick. This choice of frequency-thickness is designed to excite the symmetric Lamb mode s1, which, in turn, generates a second-harmonic s2 mode in the presence of distributed material nonlinearity. This s1-s2 mode pair satisfies the conditions for internal resonance, thereby leading to a cumulative build-up of amplitude for the second-harmonic s2 mode with increasing propagation distance. Measurements of a nonlinearity parameter β derived from the second-harmonic amplitude are plotted against propagation distance at various fractions of fatigue life under constant amplitude loading, for three different stress levels corresponding to low-cycle fatigue (LCF), high-cycle fatigue (HCF), and an intermediate case. The results show both qualitative and quantitative differences between LCF and HCF, and between the additively manufactured specimens and the wrought alloy. The potential use of this nonlinearity parameter for monitoring the early stages of fatigue damage accumulation, and hence for predicting the residual fatigue life, is discussed, as well as the potential for quality control of the additive manufacturing (AM) process.

Commentary by Dr. Valentin Fuster
ASME J Nondestructive Evaluation. 2018;1(4):041004-041004-13. doi:10.1115/1.4040472.

Shockwave is a high pressure and short duration pulse that induce damage and lead to progressive collapse of the structure. The shock load excites high-frequency vibrational modes and causes failure due to large deformation in the structure. Shockwave experiments were conducted by imparting repetitive localized shock loads to create progressive damage states in the structure. Two-phase novel damage detection algorithm is proposed, that quantify and segregate perturbative damage from microscale damage. The first phase performs dimension reduction and damage state segregation using principal component analysis (PCA). In the second phase, the embedding dimension was reduced through empirical mode decomposition (EMD). The embedding parameters were derived using singular system analysis (SSA) and average mutual information function (AMIF). Based, on Takens theorem and embedding parameters, the response was represented in a multidimensional phase space trajectory (PST). The dissimilarity in the multidimensional PST was used to derive the damage sensitive features (DSFs). The DSFs namely: (i) change in phase space topology (CPST) and (ii) Mahalanobis distance between phase space topology (MDPST) are evaluated to quantify progressive damage states. The DSFs are able to quantify the occurrence, magnitude, and localization of progressive damage state in the structure. The proposed algorithm is robust and efficient to detect and quantify the evolution of damage state for extreme loading scenarios.

Commentary by Dr. Valentin Fuster

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