Experimental analysis of the fatigue of shape memory alloys through power-law statistics

In this paper, fatigue failure is investigated by studying the collective motion of defects inside a NiTi shape memory alloys material. To this end, an experimental study of the statistical distributions of acoustic emissions avalanches due to these defects along cycling is presented. It is found that these distributions follow power-law statistics for which the evolutions of exponents through cyclic driving are estimated. The goal is to track changes in the dissipation modes through the shifts of the power-law exponents and consequently identify fatigue failure precursors. It's shown that these fatigue precursors can be interpreted using the paradigm of self organized criticality (SOC).