CONCRETE GRAVITY DAMS FE MODELS PARAMETERS UPDATING USING AMBIENT VIBRATIONS

Most of the dams around the world were designed before the introduction of seismic regulations and without concerns about their dynamic behavior. The failure of a large gravity dam might have catastrophic effects putting at risk a large number of human lives, not counting the considerable economic consequences. Since there are no case histories of concrete gravity dams failed after seismic events, numerical models assume great importance for the evaluation of the seismic performance of such structures or to control them within a SHM framework. Several different sources of uncertainty are involved in numerical models of concrete gravity dams, their effects can be reduced by exploiting all available information about the structure. Ambient vibrations are an important source of information because they can be used to characterize the dynamic behavior of the structure. In this paper, a procedure, defined in the Bayesian framework, which allows calibrating the dynamic model parameters using ambient vibration is presented. Ambient vibrations are used to determine the modal characteristics of the system, by applying the Operational Modal Analysis (OMA), which are used in the updating process. The use of meta models based on the general Polynomial Chaos Expansion (gPCE) and a modified version of Markov Chain Monte Carlo (MCMC) allows both considering the SSI in the numerical model of the dam and solving the problem of coherence between experimental and numerical modes. Finally, the proposed procedure is applied to the case of an Italian dam showing the applicability to real cases.