A genetic algorithm–based design approach for smart base isolation systems

Abstract

This article presents a new approach for designing effective smart base isolation systems composed of a low-damping linear base isolation and a semi-active magneto-rheological damper. The method is based on transforming the design procedure of the hybrid base isolation system into a constrained optimization problem. The magneto-rheological damper command voltages have been determined using H2/linear quadratic Gaussian and clipped-optimal control algorithms. Through a sensitivity analysis to identify the effective design parameters, base isolation and control algorithm parameters have been taken as design variables and optimally determined using genetic algorithm. To restrict increases in floor accelerations, the objective function of the optimization problem has been defined as minimizing the maximum base drift while putting specific constraint on the acceleration response. For illustration, the proposed method has been applied to design a semi-active hybrid isolation system for a four-story shear building under earthquake excitation. The results of numerical simulations show the effectiveness, simplicity, and capability of the proposed method. Furthermore, it has been shown that using the proposed method, the acceleration of the isolated structure can also be incorporated into design process and practically controlled with a slight sacrifice of control effectiveness in reducing the base drift.

Performance assessment of an earthquake-based optimally designed fluid viscous damper under blast loading

“…The GA is then used to solve the unconstrained optimization problem that the optimal values of damping coefficients and their average are presented in Table 4. The operators and parameters of GA have been defined as explained in Mohebbi et al (2018). It can be found that the total added damping is quite different for each earthquake record and the optimal FVD is highly dependent on the design seismic record.…”

“…To keep the seismic performance of structures within the serviceability and functional limits and to control the damage levels under extreme loads, another approach using the structural control systems is used (Soong and Dargush, 1997). Different control systems such as passive (Zhong et al, 2018), semi-active (Symans and Constantinou, 1999), active (Bigdeli and Kim, 2014), and hybrid (Mohebbi et al, 2018) devices have been employed to control the seismic behavior of structures.…”

Illustration Design Model with Clustering Optimization Genetic Algorithm

“…e theory that genetic algorithm can be used in the process of design improvement and optimization is proposed, and the theoretical framework of the whole design is explained [4,5]. His design system could be used to make cars and seats; the use of computeraided evolutionary design in the field of artistic innovation [6,7] opens a new door for evolutionary art. In addition to these, some people have applied computer simulation technology to more fields, such as the lamp in art and sculpture, making the application scope of this technology more extensive.…”

Parametric Estimation From Empirical Data Using Particle Swarm Optimization Method for Different Magnetorheological Damper Models

“…The optimization is calculated by minimizing the error between the model outputs and the experimental data. Among the most preferred algorithm is the Genetic Algorithm (GA) [21][22][23]. State estimation (SE) is also considered as a robust estimation method when multiple conforming gross errors exist, or multiple leverage points exist.…”