Optimization of Seismic Base Isolation System Using a Fuzzy Reinforced Swarm Intelligence. (December 2022) - Kandemir, Elif Cagda; Mortazavi, Ali
Highlights: Optimization of damping parameters of an isolated structural systems. Applying FDEVM algorithm as a self-adaptive search algorithm. Simultaneously considered near-fault and far-fault earthquakes during the optimization process. Employing UBC code to verify the feasibility of the acquired solutions. Abstract: The current study deals with the optimization of seismic isolation system parameters applied in base-isolated buildings. In this regard, to consider the more realistic condition, both near-fault and far-fault earthquake ground motions are taken into account by simultaneously imposing six different acceleration records during the direct time integration analysis of the structure. The minimization of the system's peak acceleration ratio is defined as the objective function of the optimization model. To get feasible results, the determining parameters of the isolator are restricted. Such that, while the isolation system period and damping ratio are kept within a predefined range, the maximum displacement of the system is monitored and limited during the optimization process. To solve the proposed optimization model, an enhanced version of the Deferential Evolution method so-called Fuzzy Differential Evolution incorporated Virtual Mutant (FDEVM) is employed. The FDEVM method applies a fuzzy decision-making mechanism to adopt its search behavior based on the governing conditions of the current problem. It also uses a new mutant vector called virtual mutant to contribute information of all population based on each agent's quality. So, the FDEVM works as a self-adaptive and parameter-free search algorithm. The acquired results show that the FDEVM works properly to find the optimal values for the dynamic parameters of the seismic base isolation system.