Abstract

Multi-functional magnetorheological elastomers (MREs) with magnetic-controlled properties offer great potential for enabling new technologies in a diverse range of industry sectors, such as automotive, aerospace, civil, and biomedical applications. The main objective of this research dissertation is to develop analysis models for magneto-mechanical properties of smart MREs and to propose design optimization strategies to optimally design a novel sandwich beam-type MRE-based adaptive tuned vibration absorber. The dissertation comprises three major interrelated parts. In the first part, a quasi-static microstructure-based model has been proposed to investigate the magneto-elastic properties of MREs. The elastic response of the MREs at zero magnetic field is initially studied by comparing the results of three hyperelastic material models. Then, a microscale model is developed for predicting the quasi-static response of MREs under an external magnetic field. The model considers magnetic interaction between particles distributed in the carrier elastomeric matrix according to regular lattice models for isotropic MREs and according to chain-like structure for anisotropic MREs. Several lattice models are proposed, and performance of each lattice is compared with their counterparts. Detailed explanation is provided on the characteristics of the proposed lattices and on the resulting changes in the microstructure properties of the MREs. The simulation results for different lattice models are then compared with the experimental measurements for both isotropic and anisotropic MRE samples using an advanced rheometer equipped with a magnetorheological (MR) device.
In the second part, the dynamic magneto-mechanical properties of MREs are investigated. For this purpose, a dynamic physic-based model considering the microstructure of MREs is developed to accurately predict the frequency- and field-dependent linear viscoelastic properties of the material. The proposed model considers a cubic particle network in which magnetic particles are located at the junctures and connected with elastic springs. Using Langevin dynamics, the governing equations of motion of particles are derived to evaluate the relaxation spectrum associated with particles’ motion in parallel and normal directions with respect to the applied magnetic field. A dipole magnetic saturation model is also implemented to derive the storage and loss moduli of the MREs in terms of frequency and magnetic flux density. The material parameters in the proposed dynamic microstructure-based model have been identified using experimental tests. For this purpose, oscillatory shear tests were performed using the magneto-rheometer in linear viscoelastic region under a wide range of excitation frequency varying from 2 Hz to 100 Hz in presence of various levels of applied magnetic fields ranging from 0.0 T to 1.0 T. The viscoelastic properties, namely storage and loss moduli of both isotropic and anisotropic MREs, were subsequently measured and compared with those obtained using the developed model to quantitatively evaluate its performance.
The third part of the present dissertation aims to investigate the application of MREs in developing a novel sandwich beam-shaped MRE-based adaptive tuned vibration absorber (MRE-ATVA). An MRE-ATVA comprised of a light-weight sandwich beam treated with an MRE core layer and two electromagnets installed at both free ends is proposed. The MRE-ATVA is designed to have a lightweight and compact structure and the electromagnets provide the magnetic field required to activate the MRE layer while also act as the resonator of the absorber. The finite element (FE) model of the proposed MRE-ATVA and magnetic model of the electromagnets with three different potential designs are developed and combined to evaluate the frequency range of the absorber under varying magnetic field intensity. The results of the developed models are validated in multiple stages with available analytical and simulation data. The developed models are then utilized to formulate the multidisciplinary design optimization problem to maximize the operating frequency range of the MRE-ATVA while respecting constraints of weight, size, mechanical stress, and sandwich beam deflection. The optimization problem is solved combining the gradient based sequential quadratic programming (SQP) technique and stochastic based genetic algorithm (GA) to accurately obtain the global optimum solution. The performance of the optimal MRE-ATVAs with three potential designs are finally compared.