Determination of optimal magnetorheological fluid particle loading and size for shear mode monotube damper

Abstract Magnetorheological (MR) fluids belong to a class of controllable fluids, and the composition and concentration of its components govern its magnetorheological properties. In this study, an optimum particle loading (or mass fraction) and size of iron particles in MR fluid for use in a shear...
Ausführliche Beschreibung

Abstract Magnetorheological (MR) fluids belong to a class of controllable fluids, and the composition and concentration of its components govern its magnetorheological properties. In this study, an optimum particle loading (or mass fraction) and size of iron particles in MR fluid for use in a shear mode monotube MR damper were determined based on the damping force and off-state viscosity of synthesized MR fluid samples. Initially, the morphological and magnetic properties of carbonyl iron particles were characterized. Six MR fluid samples were prepared composed of combination of three different particle loadings and two sizes of iron particles. Magnetorheological tests were conducted on these samples to determine the flow curves at off-state and on-state magnetic field conditions. Herschel–Bulkley model was used for mathematical representation of flow curves at different magnetic fields and to determine their dynamic yield stress. Further, a shear mode monotube MR damper with accumulator was designed by using optimization technique for desired dynamic range and damping force. Magnetostatic analysis was performed to determine the magnetic field strength generated in the shear gap at different currents. The damping force was calculated for synthesized MR fluids based on their dynamic yield stress corresponding to the magnetic field strength in the shear gap. Analysis of variance was performed to analyse the significance of independent factors on the damping force and off-state viscosity of MRF. The optimal particle loading and size which yielded maximum damping force with minimum off-state viscosity were determined using a multi-objective genetic algorithm. Ausführliche Beschreibung