## 2 Materials and Methods
### DICM Analysis  
In this research, the strain distribution on the specimen surface was determined by DICM. It provides a non-destructive and non-contact method for measuring the object surface deformation under load. With this technique, it is possible to obtain a complete reconstruction of the defect geometry which is important for the analysis of cracking processes in concrete. DICM is based on digital image processing and numerical computation. Figure 5a demonstrates the subset-based DICM technique where a reference square subset with sufficient intensity variations is selected from the reference image taken from an un-deformed state. After using set parameters and a certain optimization algorithm, the image in a deformed state is searched for whose intensity pattern is of maximum similarity with the reference subset [38; 39]. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Threshold**} & **Sampling** & **Main** & **Pre-** & **PDT, HDT,** & **Pre-Trigger** & **Analog** \\  & **Rate** & **Amplifier** & **Amplifier** & **HLT** & **HLT** & **Filter** \\ \hline
**[dB]** & **[MHz]** & **[dB]** & **[dB]** & **[μs]** & **[μs]** & **[kHz]** \\ \hline
42 & 1 & 20 & 40 & 200, 800, 1000 & 256 & 5–400 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: AE test settings. Before the DICM test was conducted, the specimen surface was prepared by spraying black and white pigment to generate a random speckle pattern and provide strain and displacement measurements. In DIC, using an optimal speckle pattern is an important factor in reducing measurement noise and improving overall results of damage evolution in the material [40]. Therefore, the speckle pattern for concrete specimens was prepared in accordance with the guidelines developed by Correlation Solution, Inc [41]: the size of speckles ranged from 2 \(\times\) 2 to 15 \(\times\) 15 pixels, and the optimal speckle pattern was controlled by the exposure (electronic shutter of charge-coupled device (CCD) cameras). The DIC system consisted of two CCD cameras (Grasshopper3 GS3-U3-60S6M manufactured by Point Grey Research, Richmond, BC, Canada) with a spatial resolution of 2736 \(\times\) 2192 pixels and two fixed-focus lenses (28 mm, Xenoplan manufactured by Schneider-Kreuznach, Dresden, Germany). The system was calibrated by a calibration board with a circular grid (size 12 \(\times\) 9 mm, spacing 12 mm). During the calibration procedure, 21 pairs of images were recorded to ensure the accuracy of the calibration. For DICM analysis, a commercial software Vic-3D designed by Correlation Solution was used allowing accurate full-field 2D and 3D measurement of shape, displacement and strain of concrete specimens. Because DICM accuracy depends on numerous factors [42], the optimal conditions were set in accordance with the samples tested. User-defined inputs for image processing with DIC are illustrated in Table 3. The subset is the small group of pixels that allow us to track the changes by comparison of the reference image with later images of the deformed body taken at intervals of time. The subset size is set according to the sample dimension to reduce the noise level and loss of the spatial resolution of strain and displacement maps (sigma \(\sigma\)). The step size is pixel-spacing between centers of the subset, and it was set as \({}^{1}/_{4}\) of the subset size to get independent and non-repetitive data in our case. The filter size is set based on the optimal resolution of the data acquired. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Subset Size** & **Step Size** & **Filter Size** & **Correlation Accuracy, \(\sigma\)** \\ \hline
**[pixel]** & **[pixel]** & **[pixel]** & **[-]** \\ \hline
37–47 & 10 & 29 & less 0.02 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: DIC test settings. Figure 5: DICM: (**a**) DICM principle; (**b**) Strain measurement points.