Abstract

One of the most challenging task for earthquake engineers is the accurate prediction of the dynamic response of structures implementing sliding seismic isolators, like the curved surface sliders. Indeed, the force–displacement behaviour of these devices strictly depends on the coefficiens of friction developed at the two sliding surfaces whose values vary instantaneously depending on variable compression load, sliding velocity, and contact temperature developed during the seismic motion. However, only the overall (or effective) friction coefficient of the isolator can be estimated, as weighted average of the values at the two sliding surfaces, through tipycal displacement controlled prototype experimental tests. This information is not suitable for the calibration of predictive isolator models (e.g. FEM analyses) or to characterize the tribological behaviour of potentially different friction pads at the two sliding surfaces. In this paper, an estimation approach, based on a Constrained Unscented Kalman Filter (CUKF) integrated with a Random Walk Model technique (RWM), that is capable to identify the two distinct friction coefficients, and their time-variations during displacement-controlled test is presented. The proposed tool allows the identification of the distinct frictional properties without any a-priori knowledge about the design properties at the two sliding surfaces that can widely differ in terms of adopted sliding materials, presence of lubrificant, and radius of curvature. The developed tool is firstly validated through the comparison with the results of FEM analyses and then applied on experimental tests carried out on a full-scale isolator prototype demonstrating its suitability for the assessment of the actual friction coefficients.

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