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Due to the widespread application of carbon fiber woven composites in aerospace, automobile and industrial area, understanding the damage evolution of carbon fiber woven composites are the most important aspect with respect to service life. Damage initiation and propagation of composites require greater mass force and little force can cause the failure of the structure on composite materials once exceeding the critical threshold at the onset of damage. A better knowledge of dynamic behaviors for damage growth can help to improve structural optimization design and production of high-performance composites. In this study, the mechanical behaviors of composites were analyzed under uniaxial tensile loading tests. Simultaneously, the chronology of internal damage evolution process in composite was detected by acoustic emission (AE). The AE signals recorded is filtered by the Maxmin Distance algorithm and following the k-means algorithm was used to achieve damage modes recognition. Based on microscopic observations and frequency range, the three clusters are correlated with different damage mode like matrix cracking, fiber/matrix debonding and fiber breakage. In addition, the Sentry Function (SF) affected by the mechanical behavior of the material was adopted to investigate evolution of the acoustic events and verify the results of clustering results.

Understanding the damage and failure of carbon/glass epoxy hybrid woven composites under tensile loading based on acoustic emission signals is a challenging task in their practical uses. In this study, an approach based on fuzzy c-means algorithm is proposed to process the acoustic emission signals from tensile loading of composites monitored by combining acoustic emission technology and digital image correlation method. The results show that the acoustic emission signals from tensile loading can be divided into three clusters. The three clusters correspond to three kinds of damage modes including matrix cracking, fiber/matrix debonding, delamination, and fiber breakage. By comparing the acoustic characteristics of these classes, a correlation procedure between the clusters and the damage mechanisms observed is proposed. Meanwhile, it can be found that debonding and fiber break signals for glass fiber correspond to a lower frequency range than that for carbon fiber. Moreover, the method combining acoustic emission and digital image correlation can effectively monitor the damage process of the specimen both on the inside and outside, which can provide a reference for the health monitoring of composite structure.

Understanding the failure mechanisms of the buckling process of glass fiber composites based on acoustic emission (AE) signals is a challenging task. In this work, a method combining AE with digital image correlation (DIC) was used to monitor compressive buckling behaviors of delamination composites. The analysis of AE signals is based on the k-means algorithm and principal component analysis (PCA). According to PCA, three characteristic parameters of AE signals like amplitude, peak frequency, and RA value (rise time divided by amplitude), are selected for cluster analysis by k-means algorithm. The results show that the AE signals of the compression process can be divided into three clusters. The three clusters correspond to three kinds of damage modes such as matrix cracking, fiber/matrix debonding, delamination and fiber breakage. The characteristic frequency of each mode is found by cluster analysis. Besides, the size and position of delamination defects result in the reduction of mechanical properties of the glass fiber composites. The complementary technology combining AE with DIC is effective for damage monitoring of the composites. Clear changes of the displacement fields can accurately detect the damage location and degree of the specimen.

To study the deformation and damage behaviors of three-dimensional (3D) woven composites, uniaxial tensile tests of the composites were conducted and real-time acoustic emission (AE) signals and speckle images were simultaneously obtained. A k-means clustering algorithm combined with principal component analysis (PCA) was used to analyze the AE signals, and the deformation fields on the surface of composite specimens were measured by the digital image correlation (DIC) method. It was found that the corresponding AE signals were divided into three typical clusters. On the basis of the frequency range of each type, the relationships between the resulting clusters and damage mechanisms were established. The results showed that different damage mechanisms in 3D woven composites are well determined by the frequency rather than the peak amplitude. The characteristics of AE signals such as the high frequency, the medium frequency, and most of the low frequency are associated with fiber damage, fiber/matrix debonding, and matrix cracking, respectively. The change in the displacement distribution can effectively enable visual inspection of damage accumulation in composites.

The construction of the biproduct of Hopf algebras, which consists of smash product and the dual notion of smash coproduct, was first formulated by Radford. In this paper we study the quasitriangular structures over biproduct Hopf algebras B*H. We show the necessary and sufficient conditions for biproduct Hopf algebras to be quasitriangular. For the case when they are, we determine completely the unique formula of the quasitriangular structures. And so we find a way to construct solutions of the Yang-Baxter equation over biproduct Hopf algebras in the sense of (Majid, 1990).

Nonresonant third harmonic generation with tuning range between 157.0-158.8 nm and 210.4-214.0 nm in zinc vapor is reported. Using two-photon excitation of Zn 4s4d(1)D(2), 4s6s(1)S(0), and 4s6d(1)D(2) states, parametric processes with signal waves 213.8 nm, 159.0 nm, and 145.8 nm are also investigated.