Large-scale seismic structural tests are crucial to validating both structural design methodologies and the effectiveness of seismic isolation devices. However, considering the significant costs of such tests, it is essential to leverage data from completed tests by taking advantage of numerical models of the tested structures, updated using data collected from the experiments, to complete additional studies that may be difficult, unsafe or impossible to test physically. However, updating complex numerical models poses its own challenges. The first contribution of this paper is to develop a multi-stage model updating method suitable for high-order models of base-isolated structures, which is motivated and evaluated through modeling and model updating of a full-scale four-story base-isolated reinforced-concrete frame building that was tested in 2013 at the NIED E-Defense laboratory in Japan. In most studies involving model updating, all to-be-updated parameters are typically updated simultaneously; however, given the observation that the superstructure in this study predominantly moves as a rigid body in low-frequency modes and the isolation layer plays a minor role in all other modes, this study proposes updating parameters in stages: first, the linear superstructure parameters are updated so that its natural frequencies and mode shapes match those identified via a subspace system identification of the experimental building responses to low-level random excitations; then, the isolation-layer device linear parameters are updated so that the natural frequencies, damping ratios and mode shapes of the three isolation modes match. These two stages break a large-scale linear model updating problem into two smaller problems, thereby reducing the search space for the to-be-updated parameters, which generally reduces computational costs regardless of what optimization algorithm is adopted. Due to the limited instrumentation, the identified modes constitute only a subset of all modes; to match each identified mode with a FEM mode, the second contribution is a procedure proposed to compare each identified mode with a candidate set of FEM modes and to select the best match. Further, nonlinear isolation-layer device models are proposed, updated and validated with experimental data. Finally, combining the isolation-layer devices’ nonlinear models with the updated superstructure linear FEM, the final result is a data-calibrated nonlinear numerical model that will be used for further studies of controllable damping and validation of new design methodologies, and is being made available for use by the research community, alleviating the dearth of experimentally-calibrated numerical models of full-scale base-isolated buildings with lateral–torsional coupling effects.
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