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This work tends to characterize the effect of carbon black nanofillers on the properties of the woven carbon fiber reinforced thermoplastic polymers. First of all, composites from nanofilled Polyamide 6 resin reinforced by carbon fibers were fabricated. Scanning electron microscopy observations were performed to localize the nanoparticles and showed that particles penetrated the fiber zone. In fact, by reaching this zone, the carbon black nanofillers create a connectivity's network between fibers, which produces an easy pathway for the electrical current. It explains the noticed improvement of the electrical conductivity of the carbon black nanofilled composites. Electrical conductivity of neat matrix composite passed from 20 to 80S/cm by adding 8wt% of carbon black and to 140S/cm by adding 16wt% of the same nanofiller. The addition of nanofillers modifies the heating and cooling laws of carbon fiber reinforced polymer: the nanofilled carbon fiber reinforced polymer with 16wt% is the most conductive so it heats less. Based on these results, the use of the composite itself as an indicator of this mechanical state might be possible. In fact, the study of the influence of a mechanical loading on the electrical properties of the composite by recording the variance of an electrical set is possible. [ABSTRACT FROM AUTHOR]

Nowadays, nonlinear vibration methods are increasingly used for the detection of damage mechanisms in polymer matrix composite (PMC) materials, which are anisotropic and heterogeneous. The originality of this study was the use of two nonlinear vibration methods to detect different types of damage within PMC through an in situ embedded polyvinylidene fluoride (PVDF) piezoelectric sensor. The two used methods are nonlinear resonance (NLR) and single frequency excitation (SFE). They were first tested on damage introduced during the manufacturing of the smart PMC plates, and second, on the damage that occurred after the manufacturing. The results show that both techniques are interesting, and probably a combination of them will be the best choice for SHM purposes. During the experimentation, an accelerometer was used, in order to validate the effectiveness of the integrated PVDF sensor.

The present paper assessed the use of variable kinematic two-dimensional elements in the dynamic analysis of Lamb waves propagation in an isotropic plate with piezo-patches. The multi-field finite element model used in this work was based on the Carrera Unified Formulation which offers a versatile application enabling the model to apply the desired order theory. The used variable kinematic model allowed for the kinematic model to vary in space, thereby providing the possibility to implement a classical plate model in collaboration with a refined kinematic model in selected areas where higher order kinematics are needed. The propagation of the symmetric (S0) and the antisymmetric (A0) fundamental lamb waves in an isotropic strip was considered in both mechanical and piezo-elastic plate models. The convergence of the models was discussed for different kinematics approaches, under different mesh refinement, and under different time steps. The results were compared to the exact solution proposed in the literature in order to assess and further determine the effects of the different parameters used when dynamically modeling a Lamb wave propagating in such material. It was shown that the higher order kinematic models delivered a higher accuracy of the propagating wave evaluated using the corresponding Time Of Flight (TOF). Upon using the appropriate mesh refinement of 2000 elements and sufficient time steps of 4000 steps, the error between the TOF obtained analytically and numerically using a high order kinematics was found to be less than 1% for both types of fundamental Lamb waves S0 and A0. Node-dependent kinematics models were also exploited in wave propagation to decrease the computational cost and to study their effect on the accuracy of the obtained results. The obtained results show, in both the mechanical and the piezo-electric models, that a reduction in the computational cost of up to 50% can be easily attained using such models while maintaining an error inferior to 1%.