The development of shape memory actuators has enabled noteworthy applications in the mechanical engineering, robotics, aerospace, and oil industries and in medicine. These applications have been targeted on miniaturization and taking full advantage of spaces. This article analyses a Ti-Ni shape memory actuator used as part of a flow control system. A Ti-Ni spring actuator is subjected to thermomechanical training and parameters such as transformation temperature, thermal hysteresis and shape memory effect performance were investigated. These parameters were important for understanding the behavior of the actuator related to martensitic phase transformation during the heating and cooling cycles which it undergoes when in service. The multiple regression methodology was used as a computational tool for analysing data in order to simulate and predict the results for stress and cycles where the experimental data was not developed. The results obtained using the training cycles enable actuators to be characterized and the numerical simulation to be validated.
shape memory effect; Ti-Ni actuators; multiple regression analysis
