This work deals with the analysis in the frequency domain of the temperature signal and mechanical energy rate of C45 steel under two different fatigue stepwise loading series at stress ratios of 0.1 and -1. It was first investigated the energy distribution among the harmonic components of the signals to understand possible variations caused by a different stress ratio. In addition, the second amplitude harmonic (SAH) of heat dissipated and mechanical energy rates have been considered in the analysis and their relationship was investigated. It has been shown as it depends only on the material, hence it is valid whatever the kind of the test is without any assumption on the energy supplied to the material or material hysteresis loop stabilisation. The adopted approach allows the analysis of intrinsic dissipations by means of rapid, full-field and contactless techniques without any specific requirement on loading condition or temperature signal stabilisation.

The stiffness degradation represents one of the most interesting phenomena used for describing the fatigue behaviour of composites. In this regard, in literature, several works have been presented for modelling the fatigue life by studying the stiffness degradation. A critical aspect of modelling damage fatigue is represented by the difficulties in simulating the whole behaviour of material and then in describing the damage progression in all its stages. In addition, the validation of models requires the measurement of stiffness variations by means of experimental techniques. Above all for real components, the difficulties in defying proper models are accompanied by the difficulties in measuring stiffness degradation due to inapplicability of classic experimental techniques. In this work, the stiffness degradation of quasi-isotropic carbon-fibre-reinforced-polymer obtained by automated fiber placement, has been assessed by means of Thermoelastic Stress Analysis. The amplitude of temperature signal at the mechanical frequency (thermoelastic signal) was considered as an indicator of material degradation and compared to the data provided by an extensometer. The correlation between thermoelastic and mechanical data allowed to build a new experimental model for evaluating and predicting material stiffness degradation by just using thermoelastic data. The proposed approach seems to be very promising for stiffness degradation assessment of real and complex mechanical components subjected to actual loading conditions.