PSI - Issue 78

Available online at www.sciencedirect.com

ScienceDirect

Procedia Structural Integrity 78 (2026) 823–830

© 2025 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of XX ANIDIS Conference organizers Keywords: Dynamic Identification; Based-Isolated Buildings; Friction Pendulum System; Genetic Algorithms; Structural Health Monitoring. This work establishes the basis for future developments, including multi-degree-of-freedom models with torsional effects and the integration of machine learning techniques for advanced rheological characterization and prediction of response under extreme loading, ultimately enabling comprehensive diagnostic systems for the post-seismic management of base-isolated structures. XX ANIDIS Conference Dynamic identification of seismic isolator properties in base-isolated buildings Livia Fabbretti a, *, Eleni Chatzi b , Filippo Ubertini a , and Marco Breccolotti a a Department of Civil and Environmental Engineering, University of Perugia, Via Goffredo Duranti, 93, Perugia, 06125, Italy b Department of Civil, Environmental, and Geomatic Engineering, ETH Zürich, Stefano-Franscini-Platz, 5, Zürich, 8093, Switzerland Abstract In this work, a dynamic identification methodology is presented, aimed at developing diagnostic tools for the post-earthquake assessment of seismic isolation system performance. The methodology has been specifically developed for an existing base-isolated building with pendulum-type seismic isolators where a monitoring system has recently been installed. This approach will allow identification of the global nonlinear hysteretic behavior of the isolators by analyzing structural response data acquired during strong-motion seismic events. The structure is represented by a simplified six-degree-of-freedom (6DOF) model, in which the monitored quantities – accelerations and displacements – are considered as the key dynamic variables. The properties of this simplified system were determined by calculating equivalent values derived from the comprehensive full-scale model. Waiting for the actual data recorded by the monitoring system, this 6DOF model is utilized to generate synthetic structural responses, which are employed as a substitute for experimental data. An iterative optimization algorithm calibrates the global isolator parameters (initial stiffness, friction coefficients, and rate parameter) by minimizing discrepancies between theoretical performance targets and simulated responses. The real seismic accelerograms used as inputs for numerical simulations serve a dual purpose: training the parameter identification process through synthetic dat a assimilation and testing the model’s predictive capability under unseen ground motions. The approach will thus enable the detection of significant parameter variations, which may indicate mechanical degradation, structural modifications, or modeling inaccuracies.

* Corresponding author. Tel.: +39 3492971485 E-mail address: liviafabbretti.lf@gmail.com

2452-3216 © 2025 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of XX ANIDIS Conference organizers 10.1016/j.prostr.2025.12.105