Full-scale simulations of a (Magnetorheological) MR damper are carried out for revealing its hysteretic behaviors associated with implementation of semi-active control using the routine of computational fluid dynamics. By virtue of the structural symmetry of the MR damper, a two-dimensional configuration for finite element simulation is built up. Herschel-Bulkley model is employed to represent the property of the MR fluid, of which the control parameters and their relevances to the input current are addressed. Typical cases involving sinusoidal and irregular displacements, steady and transient currents loaded upon the MR damper are investigated. Numerical investigations reveal that the damper force has a positive correlation with input current, excitation amplitude and excitation frequency. The full-scale simulation is proved to exhibit a sound accuracy through the validation of experimental data. It provides a logical manner revealing the true performance of MR dampers under desirable operating modes in practice, and can be readily integrated with the gain design of the associated semi-actively controlled structure. This progress bypasses the technical challenge inherent in the traditional tests with low-frequency cyclic loadings due to the limitation of experimental setup. Besides, comparative study between two-dimensional and three-dimensional configuration simulations of the MR damper shows that former has a better applicability, which can be carried out on a low-cost platform.

The magnetorheological (MR) damper is a new device proposed for structural protection. It is filled with MR fluid that can be changed, when exposed to a magnetic field, regularly from free flowing liquid, linear viscous one to semi-solid. A phenomenological model based on the Bouc-Wen hysteresis model is adopted to predict both the force-displacement behavior and the complex nonlinear force-velocity response. The theory of fuzzy control is adopted here to determine the command voltage of MR dampers, but the applying of fuzzy control rules has always to deal with the classic problem of optimization. And due to the structural responses of analysis results, it can be confirmed that the reducing effects have an obviously improvement after an optimization by genetic algorithm.