Parameter Optimization of Friction Pendulum Bearings Based on the Adaptive Genetic Algorithm Considering the Overall Evolutionary Status

Abstract

Improper design of friction pendulum bearings can lead to poor seismic reduction performance and may result in the failure of local vulnerable components. And the parameter design of friction pendulum bearings mainly relies on experience and verification calculations at present. This paper proposes an adaptive genetic algorithm considering the overall evolution state of the population, adjusting crossover and mutation probabilities adaptively based on individual fitness and population diversity. Compared to traditional algorithms, it exhibits better global search capabilities and convergence efficiency. Combining the improved genetic algorithm with finite element models, a parameter optimization method is proposed. The parameters of friction pendulum bearings are optimized. In response to the situation in this paper, the optimal friction coefficient of the friction pendulum bearing is determined to be 0.01 and the optimal equivalent radius is 3.3 m. This can provide a reference for the design of seismic isolation devices.