Geometric optimisation of double ended magnetorheological fluid damper

The main focus of this paper is to optimally design the Magnetorheological Fluid Damper using modern optimization algorithms such as Genetic Algorithm (GA), JAYA and GWO (Grey Wolf Optimizer). The objective function of the problem is to maximize the damping force of the damper. To calculate the damping force for different values of the design parameter Computational Fluid Dynamics (CFD) analysis has been used. The fluid properties to be implemented in the CFD analysis are evaluated through rheological experimentation under different magnetic flux. The design variables in the problem are the length of fluid exposed to the magnetic, Yield Shear stress, and fluid flow gap. The objective function has been formulated by Statistical modeling of the damper wherein a set of Design of Experiments. Obtained set of experiments are statistically (i.e. Analysis of Variance, ANOVA) analyzed to confirm the suitability of the design variable values in the optimization techniques. This equation along with a set of design variables constraints are used in the optimization techniques to find the optimal values of dimensions of the damper to achieve the maximum damping force. From the results it has been observed that the JAYA and GWO technique offered maximum damping force compared to the GA.