QUASI-STATIC CHARACTERIZATION AND MODELING OF THE BENDING BEHAVIOR OF SINGLE CRYSTAL GALFENOL FOR MAGNETOSTRICTIVE SENSORS AND ACTUATORS

Abstract

Iron-gallium alloys (Galfenol) are structural magnetostrictive materials that exhibit high free-strain at low magnetic fields, high stress-sensitivity and useful thermo-mechanical properties. Galfenol, like smart materials in general, is attractive for use as a dynamic actuator and/or sensor material and can hence find use in active shape and vibration control, real-time structural health monitoring and energy harvesting applications. Galfenol possesses significantly higher yield strength and greater ductility than most smart materials, which are generally limited to use under compressive loads. The unique structural attributes of Galfenol introduce opportunities for use of a smart material in applications that involve tension, bending, shear or torsion. A principal motivation for the research presented in this dissertation is that bending and shear loads lead to development of non-uniform stress and magnetic fields in Galfenol which introduce significantly more complexity to the considerations to be modeled, compared to modeling of purely axial loads.

This dissertation investigates the magnetostrictive response of Galfenol under different stress and magnetic field conditions which is essential for understanding and modeling Galfenol's behavior under bending, shear or torsion. Experimental data are used to calculate actuator and sensor figures of merit which can aid in design of adaptive structures. The research focuses on the bending behavior of Galfenol alloys as well as of laminated composites having Galfenol attached to other structural materials. A four-point bending test under magnetic field is designed, built and conducted on a Galfenol beam to understand its performance as a bending sensor. An extensive experimental study is conducted on Galfenol-Aluminum laminated composites to evaluate the effect of magnetic field, bending moment and Galfenol-Aluminum thickness ratio on actuation and sensing performance.

A generalized recursive algorithm is presented for non-linear modeling of smart structures. This approach is used to develop a magnetomechanical plate model (MMPM) for laminated magnetostrictive composites. Both the actuation and sensing behavior of laminated magnetostrictive composites as predicted by the MMPM are compared with results from existing models and also with experimental data obtained from this research. It is shown that the MMPM predictions are able to capture the non-linear magnetomechanical behavior as well as the structural couplings in the composites. Model simulations are used to predict optimal actuator and sensor design criteria. A parameter is introduced to demarcate deformation regimes dominated by extension and bending. The MMPM results offer significant improvement over existing model predictions by better capturing the physics of the magnetomechanical coupled behavior.