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Background: Residual stress often generates during preparation, processing and use of silicon carbide (SiC) single crystal, which seriously affects the quality and service life of materials. Objective: This work aimed at evaluating the stress states in 6H-SiC single crystal wafers with different crystallographic orientations. Methods: The principle of determining the stress state of the hexagonal crystal system material through a multiple regression method was derived by modifying the related theory. Then the in-plane residual stress states of 6H-SiC samples grown along the [0001], 10 1 ¯ 0 and 11 2 ¯ 0 orientations were calculated, respectively. And the effect of the number of diffraction planes on the stress measurement results was studied. Finally, the stress results of SiC-6H materials grown in different crystallographic orientations were compared. Results: We found that the plane stress errors were gradually decreased with increase of the number of crystallographic planes, and were much lower than the ones estimated when the stress-free interplanar spacing was known; The residual stress states in single-crystal 6H-SiC of different crystallographic orientations were significantly different. Single-crystal 6H-SiC with 11 2 ¯ 0 growth direction had the smallest stress values, which was associated with the primary slip system {0001} ⟨ 11 2 ¯ 0 ⟩ . Conclusions: The improved methodology based on the multiple regression analysis can be applied to the stress measurement of single-crystal 6H-SiC. At least 6 planes should be used for stress detection to ensure the accuracy of residual stress results. Crystallographic orientation significantly influences the in-plane residual stress state in silicon carbide single crystal. [ABSTRACT FROM AUTHOR]

Calcium-magnesium-alumina-silicate (CMAS) corrosion has been regarded as the most important factor that leads to the degradation of thermal barrier coatings (TBCs). The failure mechanism of TBCs attacked by CMAS corrosion in the actual service conditions is still not clear due to the lack of an environmental simulator and nondestructive testing techniques. To solve the above problems, a real-time acoustic emission method combined with infrared thermography are developed to investigate the failure mechanism of TBCs attacked by CMAS corrosion. The results show that the acoustic emission signal spectrum only depends on the failure mode of the TBCs, and five failure modes are identified: surface vertical cracks, sliding interfacial cracks, opening interfacial cracks, substrate deformation and noise. The lifetime of TBCs attacked by CMAS corrosion is 40 thermal shock cycles, which is nearly six times lower than that of TBCs without CMAS corrosion (350 cycles). Conclusions: The failure mechanism of the former is interlaminar cracking and delamination in the ceramic coating; while that for the latter is interfacial delamination in the vicinity of thermal growth oxide. [ABSTRACT FROM AUTHOR]

The experimental identification of contact stress is important in many areas. In this paper, we present an inverse method for identifying the stress distribution on non-conforming contact interface based on local displacement measurements. A mechanical model is established to formulate the relationship between the contact stress and the displacement field near the interface. An optical method, named segmentation-aided digital image correlation is utilized to measure the near-field displacement. The contact stress is then inversed by finding the optimal model that best matches the measurements. Three model parameters, i.e., the contact center, contact length and maximum contact stress, are identified through an optimization procedure. The parameters are initialized by an image processing method and then iteratively refined by minimizing the discrepancy between the model predictions and the measured displacements. Both simulated and real-world experiments are conducted and the results verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, we propose segmentation-aided digital image correlation (SA-DIC) for measuring the deformation near the interface between two contact bodies. Conventional DIC assumes that the shape function correctly warps a square subset from the reference image to the deformed image. When the subset is close to the contact interface, it contains pixels from the two contact bodies and the background if clearance is present. The displacement field in the subset is greatly complicated by the induced discontinuity and mismatches the shape function. To resolve this problem, SA-DIC automatically segments the image pixels into three categories: the two contact bodies and the invalid area. By using complementary speckle patterns, the contact interface exhibits a sharp intensity transition and it is extracted by edge detection. The background pixels are identified from the difference of the reference image pair captured with distinct background. Based on the image segmentation, only the pixels belonging to the same category are included in the subset. Their displacements are homogeneous and thus well characterized by the shape function used in DIC. Both simulated and real-world experiments are carried out to evaluate the proposed method and compare with conventional DIC. The results show that SA-DIC is able to measure the localized deformation due to the contact, while conventional DIC generates large errors near the contact interface and falsely locates the most deformed areas. [ABSTRACT FROM AUTHOR]

To identify failure modes in thermal barrier coatings (TBCs), we propose a method of processing acoustic emission signals based on the wavelet packet transform and neural networks. The results show that there are four typical failure modes in TBCs: surface cracks, sliding interface cracks, opening interface cracks, and substrate deformation. These failure modes can be discriminated by the wavelet energy coefficients that parameterize their characteristic frequency bands. By using the energy coefficient vector as an input, the back-propagation neural network has a self-learning ability to cluster signals with the same order features. In comparison with experiments, this processing method is effective for intelligently discriminating the failure modes of TBCs. [ABSTRACT FROM AUTHOR]