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The paper presents signal and image processing algorithms to automatically detect delamination and disbond in composite plates from wavefield images obtained using a scanning laser Doppler vibrometer (LDV). Lamb waves are excited by a lead zirconate titanate transducer (PZT) mounted on the surface of a composite plate, and the out-of-plane velocity field is measured using an LDV. From the scanned time signals, wavefield images are constructed and processed to study the interaction of Lamb waves with hidden delaminations and disbonds. In particular, the frequency-wavenumber (f-k) domain filter and the Laplacian image filter are used to enhance the visibility of defects in the scanned images. Thereafter, a statistical cluster detection algorithm is used to identify the defect location and distinguish damaged specimens from undamaged ones.

The objective of this study was to evaluate the long term performance of cell-free vascular grafts made from a fast-degrading elastic polymer. We fabricated small arterial grafts from microporous tubes of poly(glycerol sebacate) (PGS) reinforced with polycaprolactone (PCL) nanofibers on the outer surface. Grafts were interpositioned in rat abdominal aortas and characterized at 1 year post-implant. Grafts remodeled into “neoarteries” (regenerated arteries) with similar gross appearance to native rat aortas. Neoarteries mimic arterial tissue architecture with a confluent endothelium and media and adventita-like layers. Patent vessels (80%) showed no significant stenosis, dilation, or calcification. Neoarteries contain nerves and have the same amount of mature elastin as native arteries. Despite some differences in matrix organization, regenerated arteries had similar dynamic mechanical compliance to native arteries in vivo. Neoarteries responded to vasomotor agents, albeit with different magnitude than native aortas. These data suggest that an elastic vascular graft that resorbs quickly has potential to improve the performance of vascular grafts used in small arteries. This design may also promote constructive remodeling in other soft tissues.

Ultrasonic guided waves (UGWs) are a useful tool in structural health monitoring (SHM) applications that can benefit from built-in transduction, moderately large inspection ranges, and high sensitivity to small flaws. This paper describes an SHM method based on UGWs and outlier analysis devoted to the detection and quantification of fatigue cracks in structural waveguides. The method combines the advantages of UGWs with the outcomes of the discrete wavelet transform (DWT) to extract defect-sensitive features aimed at performing a multivariate diagnosis of damage. In particular, the DWT is exploited to generate a set of relevant wavelet coefficients to construct a uni-dimensional or multi-dimensional damage index vector. The vector is fed to an outlier analysis to detect anomalous structural states. The general framework presented in this paper is applied to the detection of fatigue cracks in a steel beam. The probing hardware consists of a National Instruments PXI platform that controls the generation and detection of the ultrasonic signals by means of piezoelectric transducers made of lead zirconate titanate. The effectiveness of the proposed approach to diagnose the presence of defects as small as a few per cent of the waveguide cross-sectional area is demonstrated.(Some figures in this article are in colour only in the electronic version) Rose 1999, Staszewski 2003, Kundu 2004, Giurgiutiu 2005. In the case of an engineering system with complex geometry, the UGW-based approach is sometimes hindered by the multiple diffraction