A temperature- and strain-rate-dependent model of NiTi shape memory alloys for seismic control of bridges
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This paper proposes a neuro-fuzzy model of NiTi shape memory alloy (SMA) wires that is capable of capturing behavior of superelastic SMAs at different temperatures and at various loading rates while remaining simple enough to realize numerical simulations. First, in order to collect data, uniaxial tensile tests are conducted on superelastic wires in the temperature range of 0 C to 40 C, and at the loading frequencies of 0.05 Hz to 2 Hz that is the range of interest for seismic applications. Then, an adaptive neuro-fuzzy inference system (ANFIS) is employed to construct a model of SMAs based on experimental input-output data pairs. The fuzzy model obtained from ANFIS training is validated by using an experimental data set that is not used during training. Upon having a model that can represent behavior of superelastic SMAs at various ambient temperature and loading-rates, nonlinear simulation of a multi-span continuous bridge isolated by rubber bearings that is equipped with SMA dampers is carried out. Response of the bridge to a historical earthquake record is presented at different ambient temperatures in order to evaluate the effect of temperature on the performance of the structure. It is shown that SMA damping elements can effectively decrease peak deck displacement and the relative displacement between piers and superstructure in an isolated bridge while recovering all the deformations to their original position. 2009 SPIE.
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Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2009
