SUMMARYThe present paper is concerned with the effective numerical implementation of the two-dimensional dual boundary element method, for linear elastic crack problems. The dual equations of the method are the displacement and the traction boundary integral equations. When the displacement equation is applied on one of the crack surfaces and the traction equation on the other, general mixed-mode crack problems can be solved with a single-region formulation. Both crack surfaces are discretized with discontinuous quadratic boundary elements; this strategy not only automatically satisfies the necessary conditions for the existence of the finite-part integrals, which occur naturally, but also circumvents the problem of collocation at crack tips, crack kinks and crack-edge corners. Examples of geometries with edge, and embedded crack are analysed with the present method. Highly accurate results are obtained, when the stress intensity factor is evaluated with the J-integral technique. The accuracy and efficiency of the implementation described herein make this formulation ideal for the study of crack growth problems under mixed-mode conditions.

Piezoelectric sensors are increasingly being used in active structural health monitoring, due to their durability, light weight and low power consumption. In the present work damage detection and characterization methodologies based on Lamb waves have been evaluated for aircraft panels. The applicability of various proposed delay-and-sum algorithms on isotropic and composite stiffened panels have been investigated, both numerically and experimentally. A numerical model for ultrasonic wave propagation in composite laminates is proposed and compared to signals recorded from experiments. A modified delay-and-sum algorithm is then proposed for detecting impact damage in composite plates with and without a stiffener which is shown to capture and localize damage with only four transducers.

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In this work a methodology for impact identification on composite stiffened panels using piezoceramic sensors has been presented. A large number of impacts covering a wide range of energies (corresponding to small and large mass impacts) at various locations of a composite stiffened panel have been simulated using the finite element (FE) method. To predict the impact location, artificial neural networks have been established using the data generated from FE analyses. A number of sensor signal features have been examined as inputs to the neural network and the effect of noise on the predictions has been investigated. The results of the study show that the trained network is capable of locating impacts with different energies at different locations (e.g. in the bay, over/under the stringer and on the foot of the stringer) in a complicated structure such as a composite stiffened panel.

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