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This research paper presents a machine learning-based optimal design of a superelastic shape memory alloy (SMA) integrated friction pendulum isolator for controlling underground blast-induced vibrations in buildings. The study utilizes multi-objective optimization to compare the performance of the SMA-FP isolator against traditional friction pendulum isolators, demonstrating significant reductions in top floor peak acceleration and isolator displacements. The findings indicate that the SMA-FP system offers

Author

Anil Kalyani

Language

EN