Conventional passive base isolators often experience large displacement demand that require more advanced architecture to ensure safety and serviceability. To reduce this displacement demand, hybrid base isolation system is often prescribed where the passive isolation system is augmented with additional devices, e.g., a tuned mass damper inerter (TMDI) system along with a magneto-rheological (MR) damper in the present study. An inerter is a two-terminal flywheel where the generated force is proportional to the relative acceleration between its two ends, while a MR damper offers current or magnetic-flux dependent adjustable dynamic properties in real-time. However, their optimal tuning in presence of uncertainty offers serious challenges. With this in view, present study focuses on the reliability-based optimal tuning of hybrid base isolation system where uncertainty associated with MR damper and ground excitation play the vital role. Thus, the damper is tested in the laboratory to experimentally model the random variables. A sparse polynomial chaos expansion based meta model is used to replace the original limit state function for improved computational efficiency. Finally, the response of a full-scale base isolated building is used to compare the algorithm for optimal reliability based tuning of the hybrid system. The results show the enhanced performance of the proposed system compared to the traditional base isolation to simultaneously mitigate the structural response and the isolator displacement demand.
Das et al. (Mon,) studied this question.