## 4 Results and Discussion
### Effect of freeze-soak-scour Cycles on Properties of NHISS-AC
#### 4.2.3 Scouring Cycles Test  
The scouring cycle test is designed based on Pavement Material Dynamic Water Scouring Tester. The water gun pressure, the speed of the disk, and the scour time are set to 2.56 Mpa, 420 rad/min, and 4.8 min respectively to realize a scouring cycle. Then, after 0, 5, 10, 15, and 20 scouring cycles test, damaged NHSS-AC specimens were collected for the durability and performance test. The results are shown in Table 9. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{3}{*}{\begin{tabular}{c} **Number** \\ **of Cycle** \\ \end{tabular} } & \multirow{3}{*}{\begin{tabular}{c} **Voids** \\ **Content** \\ **(\%)** \\ \end{tabular} } & \multirow{3}{*}{\begin{tabular}{c} **Weight** \\ **Loss Ratio** \\ **(\%)** \\ \end{tabular} } & \multirow{3}{*}{\begin{tabular}{c} **Freeze–thaw** \\ **Splitting** \\ **Tensile** \\ **Ratio (\%)** \\ \end{tabular} } & \multirow{3}{*}{\begin{tabular}{c} **Marshall** \\ **Stability** \\ **(kn)** \\ \end{tabular} } & \multirow{3}{*}{\begin{tabular}{c} **Splitting** \\ **Tensile** \\ **Strength** \\ **(Mpa)** \\ \end{tabular} } & \multirow{3}{*}{\
\begin{tabular}{c} **Destruction** \\ **Tensile** \\ **Stiffness** \\ **Staffness** \\ **Modus** \\ **(\(\mu\varepsilon\))** \\ \end{tabular} } & \multirow{3}{*}{
\begin{tabular}{c} **Destruction** \\ **Tensile** \\ **Stiffness** \\ **Strain** \\ **(Mpa)** \\ \end{tabular} } \\ \hline
0 & 4.733 & 0.000 & 100 & 93.5 & 4.32 & 2.27 & 3282 \\
5 & 4.776 & 0.025 & 89.7 & 8.93 & 4.30 & 2.15 & 3442 \\
10 & 4.814 & 0.025 & 86.7 & 8.83 & 4.28 & 2.15 & 3422 \\
15 & 4.861 & 0.034 & 82.6 & 8.78 & 4.24 & 2.12 & 3441 \\
20 & 4.849 & 0.042 & 80.5 & 8.63 & 4.20 & 2.06 & 3511 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Variation of NHSS-AC parameters under soak cycle. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{3}{*}{ \begin{tabular}{c} **Number** \\ **of Cycle** \\ \end{tabular}  } & \multirow{3}{*}{ \begin{tabular}{c} **Voids** \\ **Content** \\ **(\%)** \\ \end{tabular}  } & \multirow{3}{*}{ \begin{tabular}{c} **Weight** \\ **Loss Ratio** \\ **(\%)** \\ \end{tabular}  } & \multirow{3}{*}{ \begin{tabular}{c} **Freeze–thaw** \\ **Splitting** \\ **Tensile** \\ **Ratio (\%)** \\ \end{tabular}  } & \multirow{3}{*}{ \begin{tabular}{c} **Marshall** \\ **Stability** \\ **(kn)** \\ \end{tabular}  } & \multirow{3}{*}{ \begin{tabular}{c} **Splitting** \\ **Tensile** \\ **Strength** \\ **(Mpa)** \\ \end{tabular}  } & \multirow{3}{*}{\ \begin{tabular}{c} **Destruction** \\ **Tensile** \\ **Stiffness** \\ **Staffness** \\ **Strain** \\ **(Mpa)** \\ \end{tabular}  } & \multirow{3}{*}{ \begin{tabular}{c} **Destruction** \\ **Tensile** \\ **Stiffness** \\ **Staffness** \\ **Modus** \\ **(Mpa)** \\ \end{tabular}  } \\ \hline
0 & 4.009 & 0.000 & 100 & 9.35 & 4.32 & 2.27 & 3282 \\
5 & 4.207 & 0.025 & 89.4 & 9.02 & 4.28 & 2.18 & 3374 \\
10 & 4.331 & 0.034 & 85.7 & 8.76 & 4.21 & 2.21 & 3275 \\
15 & 4.378 & 0.042 & 80.5 & 8.44 & 4.144.2.4. Analysis of Results Based on the Gray Rational Degree Theory  
The gray rational degree theory focuses on the problems of small samples and poor information which are difficult to solve in probability and statistics and fuzzy mathematics. The theory is based on information coverage, and explores the evolvement rule of things through the action of sequence operators. The main idea of gray rational degree theory is to judge whether the relationship is close according to the similarity of the geometric shape of the sequence curve. The closer the curve develops, the greater the correlation degree between the corresponding sequences will be. The method can provide a quantitative measure for the development and change trend of a system, which is very suitable for the judgment and analysis of dynamic process. The calculation process of grey correlation degree is shown below. Define the reference sequence and the comparison sequence.