## 5 Implementation of the Algorithms
### Applying the Regression Algorithm  
The presented data were obtained from a BEAST slab evaluation on 24 June 2021. By this time, the BEAST concrete slab had undergone 85 freeze-thaw cycles and 1,671,506 live load cycles and had been sprayed with 3360 gallons of salt brine. Before utilizing the regression algorithm, the data from each technology were analyzed and visualized to compare the differences in data interpretation with and without the ML algorithm. Figure 17a-e present a surface map of the BEAST slab for the electrical resistivity, half-cell potential, degree of saturation, impact echo condition assessment, and concrete cover, respectively.  
The results from the impact echo test were unable to determine the depth of delamination as it was shallow, with a maximum depth of about 3 cm (1.25 in). The delamination was found to be located within the concrete cover located at the boundary between the top reinforcement mesh and the concrete. As per the visible spalling, the shallow delamination corresponded with the top reinforcement layer, as shown in Figure 17d. Furthermore, the concrete cover measurements were obtained from the GPR survey, as illustrated in Figure 17e. A comparison of results from before and after implementing the algorithm is  
Figure 15: The loading device that represents the truck axel loads at the BEAST® facility.  
displayed in Figures 18 and 19 for ER and the HCP, respectively. Significant modifications in the ER measurement values can be observed by comparing Figure 18a (without the algorithm) to Figure 18b (with the algorithm). The measurements increased from approximately 12 kOhm.cm to roughly 25 kOhm.cm, with the minimum resistivity after using the algorithm appearing in the center of the slab. These changes are due to the impact of the DoS and delamination, which have a considerable influence on the measurement values, as discussed earlier in Section 3. The algorithm improves the interpretation by correcting for the differences with reference values. The algorithm attempts to counteract the effect of the DoS by reducing resistivity in areas with a low DoS and increasing resistivity in areas with a high DoS. Furthermore, the IE delamination map in Figure 17d highlights the location of shallow delamination, which is reflected in the corrected ER values in Figure 18b. The algorithm tries to mitigate the impact of delamination on the ER measurement values by decreasing resistivity in the delaminated area, primarily in the center of the deck, as shown in Figure 17d.  
Figure 16: Data collection of the NDE technologies on the BEAST slab. (**a**) Grid mark on the concrete deck; (**b**) electrical resistivity; (**c**) half-cell potential; (**d**) impact echo; (**e**) MOIST-Scan.  
Figure 17: NDE surface map from the data collected on the BEAST slab for the (**a**) electrical resistivity; (**b**) half-cell potential; (**c**) degree of saturation; (**d**) impact echo condition assessment; (**e**) concrete cover, obtained via GPR survey.  
Similarly, the algorithm has produced significant changes in the HCP values. The corrected HCP values in Figure 18(b) are a result of the impact of the DoS, delamination, and CC parameters. The algorithm corrects the impact of these parameters by moving the HCP values towards the right side of the scale (less negative values) for areas with high DoS values. Likewise, the HCP values are shifted towards less negative values for areas with low CC values. However, the HCP values are shifted towards the left side (more negative values) for areas with low DoS values.