## 2 Materials and Methods
### Image and Signal Processing  
For DIC, the camera frame rate was set to 20 Hz to capture the 10 Hz testing frequency. This resulted in a substantial number of images per test, with the largest test recording containing 100,000 images. These images were stored on a computer for subsequent analysis. It is important to note that, at this stage, the development is based on an offline analysis. However, for its further implementation, an online analysis will be required. Details of the online analysis are not covered in this paper. The analysis of the images relied on a commercial Image Correlation algorithm using GOM correlate software (2019 version, free trial). Given the uniaxial loading conditions, the displacement field in the longitudinal direction was used as the main magnitude. It is important to note that due to the geometric nature of the sandwich structure, only the side face of the fins can be monitored, given their thickness (100 um). As a result, no stochastic pattern could be applied and observed in such a tiny surface. Therefore, only the side face of the fins was monitored, as illustrated in the next image (Figure 5). This image depicts the longitudinal displacement in the axial direction, where load was applied, along with the corresponding values. The final computed magnitude is strain, obtained by using the following formula:  
\[\textit{Strain}\ 1=\frac{(\textit{Displ.1}-\textit{Displ.5})}{L} \tag{1}\]  
where \(L\) is the distance between the surface's centre. This formula was similarly applied to _Displ.2-Displ.6_, _Displ.3-Disp.7_, and _Displ.4-Disp.8_, respectively. This approach assessed the strain between two consecutive layers and at different locations. Under perfect uniaxial conditions, all the strain values should have been equal. This remains true during most parts of the test until local ruptures appear. For early damage identification, this approach proved valid, as uniaxial conditions were maintained at this stage. Therefore, the evolution of this magnitude was utilized as the representative parameter to identify damage. For the sake of brevity, not all the images were processed; instead, specific intervals were selected to assess the occurrence of damage. Consequently, in the results section, strain evolution is presented in intervals rather than a continuous curve. Figure 5: DIC image of a test showing three main surfaces being monitored. Regarding the optical microphone, a proof of concept was conducted before commencing the fatigue tests. This was done to properly evaluate the best mounting configuration of the sensor heads and calibrate the settings of the signal conditioning unit (SCU) for this application. During this procedure, a tensile test was performed with the sensor heads of the microphones placed at 5 mm from the sample to effectively capture any potential small cracks (refer to Figure 6). To analyze them, a spectrogram was calculated. A spectrogram is a three-dimensional representation showing the spectral acoustic energy of the signal over time and frequency. In its calculation, the time signal of the acoustic process emissions was split into overlapping segments and a Fourier transformation was applied to each segment. The result is presented in Figure 7, where time is represented on the horizontal axis, frequency on the vertical axis, and the respective acoustic energy amplitude is depicted as color. Figure 6: Experimental set-up employed for tensile test during Acoustic Emission testing. Figure 7: Acoustic Emission results for tensile testing. In the illustrated spectrogram (Figure 7), several noteworthy aspects can be highlighted. The graph represents a 50 ms duration test, where initially, no signals are observed except for the low frequency background noise. Towards the end of the test, numerous high-amplitude and high-frequency events became evident, likely associated with the phenomenon of metallic sheet rupture. Of particular interest was a smaller peak observed 15 ms prior to rupture, possibly linked to a small crack that did not lead to rupture.