Design Optimization of Magneto-active Elastomer Unimorph Actuator for Shape Programming

In this study, a magneto-active elastomer (MAE) unimorph actuator is optimally designed for shape programming. An optimization design approach for the MAE unimorph actuator is developed to design the geometry and material properties of the structure. Within the design optimization, a previously developed and validated analytical model is applied to predict the actuation performance of MAE unimorph actuator under a user-specified external magnetic field. This model considers the unimorph as a segmented beam with large deflections and approximates the response of the material to the magnetic field as segment-wise applied torques. Then a single objective function representing the shape error is minimized using a genetic algorithm (GA). The multi-objective non-dominated sorting genetic algorithm II (NSGA-II) is also implemented to maximize both normalized free deflection and blocked force. A Pareto set of optimal solutions is obtained and the best design can be selected based on application requirements. This work has the potential to provide tailorable shape change in medical device applications that require adjustments over time such as changing patient anatomy as treatment progresses. The devices can be actuated under an external magnetic field without wires or human interference. Additive manufacturing can realize the feasibility of fabrication for the designed MAE unimorph actuator by printing complex geometry and spatially tailored magnetic and mechanical properties.