3D Quantitative Damage Characterization in the Coating of a Metal Substrate with Terahertz Waves

In this study, terahertz (THz) reflective imaging is applied to characterize damage in the coating on metal substrates. The coating was initially scratched, and after aging, different damage mechanisms have occurred. Since the coating is optically thin (compared to the wavelengths within the THz spectrum), the THz echoes will partially or totally overlap, which makes it difficult to reconstruct the damaged coating structure. THz frequency-wavelet domain deconvolution is applied to resolve the overlapping echoes. Based on the observed features in the deconvoluted THz signals, three types of damage, including corrosion, the appearance of blisters and delamination, are successfully identified. The corrosion area is located in the middle of the scratch, and the delamination occurs around the scratch. In the blister area, no delamination is observed, but the swelling of the coating is clearly revealed. Moreover, quantitative information in depth is also obtained by analyzing the deconvoluted data. The thickness of the delamination and the thickness of the coating in both the normal (undamaged) and blister areas can be calculated. 3D imaging results shown in Fig. 1 clearly exhibit the thickness distribution across the whole coating plane, which also highlights the features of the different damage mechanisms

Terahertz frequency-wavelet domain deconvolution for stratigraphic and subsurface investigation of art painting

Terahertz frequency-wavelet deconvolution is utilized specifically for the stratigraphic and subsurface investigation of art paintings with terahertz reflective imaging. In order to resolve the optically thin paint layers, a deconvolution technique is enhanced by the combination of frequency-domain filtering and stationary wavelet shrinkage, and applied to investigate a mid-20th century Italian oil painting on paperboard, After Fishing, by Ausonio Tanda. Based on the deconvolved terahertz data, the stratigraphy of the painting including the paint layers is reconstructed and subsurface features are clearly revealed, demonstrating that terahertz frequencywavelet deconvolution can be an effective tool to characterize stratified systems with optically thin layers

Visualization of subsurface damage in woven carbon fiber-reinforced composites using polarization-sensitive terahertz imaging

Polarization-sensitive terahertz imaging is applied to characterize subsurface damage in woven carbon fiber-reinforced composite laminates in this study. Terahertz subsurface spectral imaging based on terahertz deconvolution is tailored and applied to detect, in a nondestructive fashion, the subsurface damage within the first ply of the laminate caused by a four-point bending test. Subsurface damage types, including matrix cracking, fiber distortion/fracture, as well as intra-ply delamination, are successfully characterized. Our results show that, although the conductivity of carbon fibers rapidly attenuates terahertz propagation with depth, the imaging capability of terahertz radiation on woven carbon fiber-reinforced composites can nonetheless be significantly enhanced by taking advantage of the terahertz polarization and terahertz deconvolution. The method demonstrated in this study is capable of extracting and visualizing a number of fine details of the subsurface damage in woven carbon fiber-reinforced composites, and the results achieved are confirmed by comparative studies with X-ray tomography.The authors gratefully acknowledge the financial support of the Conseil Régional du Grand Est of the Fonds Européen de Développement Régional (FEDER), and of the Institut Carnot ARTS

Application of Ultrasonic Coda Wave Interferometry for Micro-cracks Monitoring in Woven Fabric Composites

The consequences of a four-point bending test, up to 12 mm, are examined by emitting 1 MHz ultrasonic guided waves in woven carbon fiber reinforced polymer specimens, using coda wave interferometry (CWI), revealing a potential use for nondestructive evaluation. It is known that CWI is more sensitive to realistic damage than the conventional method based on the first arriving time of flight in geophysical, or in civil engineering applications such as concrete structures. However, in composite materials CWI is not well established because of the involved structural complexity. In this paper, CWI is investigated for monitoring the occurrence of realistic defects such as micro-cracks in a woven carbon fiber composite plate. The micro-cracks are generated by a four-point bending test. The damage state is stepwise enhanced by gradually increasing the load level, until failure initiation. The damage is monitored, after each loading, using ultrasound. It is demonstrated that CWI is a powerful tool to detect damage, even low levels, in the sample. Two damage indicators based on CWI, i.e. signals correlation coefficient and relative velocity change, are investigated and appear to be complimentary. Under significant loading levels, the normalized cross-correlation coefficient between the waveforms recorded in the damaged and in the healthy sample (reference at 0 mm), decreases sharply; this first indicator is therefore useful for severe damage detection. It is also demonstrated, by means of a second indicator, that the relative velocity change between a baseline signal taken at zero loading, and the signals taken at various loadings, is linear as a function of the loading, until a critical level is reached; therefore this second indicator, is useful for low damage level detection. The obtained evolution of the relative velocity measurement is supported by relative comparison to the evolution of the bending modulus in function of displacement. The relative velocity change exhibits the same evolution as the bending modulus with loading. It could be used to indicate when the material stiffness has decreased significantly. The research is done in the framework of composite manufacturing quality control and appears to be a promising inspection technique.This work is supported by the Région Grand Est

Clinical prediction models for diagnosis of COVID-19 among adult patients: a validation and agreement study.

peer reviewed[en] BACKGROUND: Since the beginning of the pandemic, hospitals have been constantly overcrowded, with several observed waves of infected cases and hospitalisations. To avoid as much as possible this situation, efficient tools to facilitate the diagnosis of COVID-19 are needed. OBJECTIVE: To evaluate and compare prediction models to diagnose COVID-19 identified in a systematic review published recently using performance indicators such as discrimination and calibration measures. METHODS: A total of 1618 adult patients present at two Emergency Department triage centers and for whom qRT-PCR tests had been performed were included in this study. Six previously published models were reconstructed and assessed using diagnostic tests as sensitivity (Se) and negative predictive value (NPV), discrimination (Area Under the Roc Curve (AUROC)) and calibration measures. Agreement was also measured between them using Kappa's coefficient and IntraClass Correlation Coefficient (ICC). A sensitivity analysis has been conducted by waves of patients. RESULTS: Among the 6 selected models, those based only on symptoms and/or risk exposure were found to be less efficient than those based on biological parameters and/or radiological examination with smallest AUROC values ( 0.75 for Se and NPV but poor agreement (Kappa and ICC < 0.5) between them. The results of the first wave were similar to those of the second wave. CONCLUSION: Although quite acceptable and similar results were found between all models, the importance of radiological examination was also emphasized, making it difficult to find an appropriate triage system to classify patients at risk for COVID-19

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM

Bifurcation Scenarios in Semiconductor Lasers Subjected to Optical Feed back

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