The measurement of stress in a structure presents considerable interest in many fields of engineering. In this paper, the diagnostic potential of nonlinear elastic guided waves in a prestressed plate is investigated. To do so, an analytical model is formulated accounting for different aspects involved in the phenomenon. The fact that the initial strains can be finite is considered using the Green Lagrange strain tensor, and initial and final configurations are not merged, as it would be assumed in the infinitesimal strain theory. Moreover, an appropriate third-order expression of the strain energy of the hyperelastic body is adopted to account for the material nonlinearities. The model obtained enables to investigate both the linearized case, which gives the variation of phase and group velocity as a function of the initial stress, and the nonlinear case, involving second-harmonic generation as a function of the initial state of stress. The analysis is limited to Rayleigh-Lamb waves propagating in a plate. Three cases of initial prestress are considered, including prestress in the direction of the wave propagation, prestress orthogonal to the direction of wave propagation, and plane isotropic stress.
The dynamics of a parabolic arch is studied in its undamaged and damaged states. The damage consists of a notch that reduces the height of the cross section at a given abscissa. A damage identification technique, based on the minimization of an objective function measuring the differences between numerical and experimental variations of natural frequencies for undamaged and damaged states, is used. The uniqueness of the solution in different damage configurations is investigated using pseudo-experimental data and the reliability of the identification procedure is assessed. The identification procedure is then applied to an experimental case, where frequencies are obtained by impulsive tests on a prototype arch. The minimum number of experimental data needed to identify damage parameters is defined and the sensitivity of the identification algorithm to different possible choices of sets of data is analyzed.
29 February 2008 in Structural Control and Health Monitoring