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Effect of the damper property variability on the seismic reliability of linear systems equipped with viscous dampers

Dall’Asta, Andrea and Scozzese, Fabrizio and Ragni, Laura and Tubaldi, Enrico (2017) Effect of the damper property variability on the seismic reliability of linear systems equipped with viscous dampers. Bulletin of Earthquake Engineering, 15 (11). pp. 5025-5053. ISSN 1573-1456

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    Abstract

    Viscous dampers are dissipation devices widely employed for seismic structural control. To date, the performance of systems equipped with viscous dampers has been extensively analysed only by employing deterministic approaches. However, these approaches neglect the response dispersion due to the uncertainties in the input as well as the variability of the system properties. Some recent works have highlighted the important role of these seismic input uncertainties in the seismic performance of linear and nonlinear viscous dampers. This study analyses the effect of the variability of damper properties on the probabilistic system response and risk. In particular, the paper aims at evaluating the impact of the tolerance allowed in devices' quality control and production tests in terms of variation of the exceedance probabilities of the Engineering Demand Parameters (EDPs) which are most relevant for the seismic performance. A preliminary study is carried out to relate the variability of the constitutive damper characteristics to the tolerance limit allowed in tests and to evaluate the consequences on the device's dissipation properties. In the subsequent part of the study, the sensitivity of the dynamic response is analysed by harmonic analysis. Finally, the seismic response sensitivity is studied by evaluating the influence of the allowed variability of the constitutive damper characteristics on the response hazard curves, providing the exceedance probability per year of EDPs. A set of linear elastic systems with different dynamic properties, equipped with linear and nonlinear dampers, are considered in the analyses, and subset simulation is employed together with the Markov Chain Monte Carlo method to achieve a confident estimate of small exceedance probabilities.