## 3 Results and Discussion
### Relevance of Evaluation Methods
#### 3.5.3 Correlation of Tests  
To examine the correlation between different tests, the Pearson test was conducted. The Pearson test measures the linear correlation between data using a correlation coefficient that ranges from \(-1\) to \(1\). A correlation coefficient close to \(1\) or \(-1\) indicates a strong correlation, while a correlation coefficient close to \(0\) indicates a weak correlation. The results of the Pearson correlation analysis are shown in Figure 28.  
Figure 28: The results of the Pearson correlation analysis.  
Figure 27: Coefficient of variation of test indicators.  
1. The \(-10\)\({}^{\circ}\)C BBT had a good positive correlation with the LT-SCB test. The correlation coefficients between their parameters were all greater than 0.5, indicating that the flexural fatigue resistance and the low-temperature crack resistance of the asphalt mixture were consistent under low-temperature conditions. The higher the toughness of the asphalt mixture, the higher its deformation and load dissipation, and the higher its crack resistance. 2. The \(15\)\({}^{\circ}\)C BBT had a poor correlation with other tests. The correlation coefficients between their parameters were mainly less than 0.5, indicating that the flexural fatigue resistance of the asphalt mixture at room temperature was different from other types of cracking resistance. 3. The CE-SCB test had a good correlation with the OT. The correlation coefficients between the \(G_{f}\), \(FI\), and the \(R\) and \(CRI\) were \(-0.638\), \(0.543\), and \(-0.756\), \(0.714\), respectively. These values indicated that the \(G_{f}\) of the asphalt mixture increased as the \(R\) decreased. The \(FI\) and \(CRI\) characterized the load decay and the crack growth rate after peak load. The higher the \(FI\) and \(CRI\), the slower the load decay and the crack growth, and the higher the crack resistance. 4. The \(-10\)\({}^{\circ}\)C BBT, LT-SCB, CE-SCB, and OT tests had some degree of negative correlation. For example, the correlation coefficient between the \(G_{f}\) of the LT-SCB test and the \(G_{f}\) of the CE-SCB test was \(-0.681\), which implies that the asphalt mixture with higher energy consumption at low-temperature cracking was less prone to cracking, while the asphalt mixture with lower energy consumption at crack expansion after cracking had faster crack development. This indicated that the cracking mechanism of asphalt mixtures under different conditions was different and that different types of tests should be considered comprehensively in performance evaluation.  
In summary, the BBT, LT-SCB, CE-SCB, and OT tests can evaluate the crack resistance of asphalt mixtures, but they have different emphases. The LT-SCB test is highly influenced by the asphalt film thickness, which cannot effectively reflect the impact of gradation change on crack resistance. Moreover, the specimen preparation process is complex, time-consuming, and limited by equipment conditions. The OT data are relatively stable, but the test sensitivity to gradation is low. Therefore, this paper suggests that the \(\varepsilon_{B}\) and \(D_{sc}\) of the \(-10\)\({}^{\circ}\)C BBT and the \(G_{f}\) and \(FI\) of the CE-SCB test should be used as the crack resistance evaluation indices of AR-SAMI.