Composite materials have been increasingly used in aircraft structures. However, these composite structures are susceptible to damage from external low-velocity impacts. In this paper, an impact identification algorithm is proposed to estimate the impact location and force time history simultaneously. A localisation method based on basis vectors is proposed, and the impact force time history is reconstructed by simplified transfer functions. The basis vector stands for the relationship between the impact location and the sensor signals, and the transfer function shows the relationship of the sensor signal and the force time history. An experiment is conducted on a flat glass fibre-epoxy matrix composite plate to verify the developed algorithm using only four sensors. The soft impactor and hard impactor are two typical impactors for impact events; therefore, the impact experiment is performed by the rubber and the steel impactors, respectively. The experimental results indicate that the proposed algorithm is feasible for the identification of impact events on plate-like composite structures.

The objective of this paper is to present an analytical model for the crashworthiness analysis of plane lock gates impacted by river ships. The model is able to assess the indentation by the colliding ship at impact point, to detect possible failure in impact vicinity and to estimate the actions on gate bearings. These latter are calculated by assuming the crash to a quasi-static load, and linear reactions distributions along the bearings. The gate geometry, the bow shape of the colliding ship, its initial velocity and the impact location on the gate, are taken into account. The ships are assumed to be quite rigid with respect to the gate. The modeling has been developed with Matlab. Results of impact of one given lock gate with two different ships: a passenger vessel and a carrier, are compared with FEM results. Impact forces and maximum indentation are well matched. Actions on bearings can be locally rather different because of their time dependence and the non-linearity of their distributions.