## 4 Results
### Statistical Reliability of the Permeability Tests Results  
In order to verify the normality, a Q-Q (quantile-quantile) plot graph and the Shapiro-Wilk test were used. The null hypothesis (H\({}_{0}\)) for the Shapiro-Wilk test is that the distribution is normal for the result with \(p\geq 0.05\). In the case of \(p<0.05\), the null hypothesis was rejected. The results for the Shapiro-Wilk test for all blends estimate the distribution for all blends as a normal distribution. Figure 6 shows the graphs for the Q-Q plot. Figure 5: The relationship between the flux velocity and the hydraulic gradient for the blends. (**a**) blend 0.05–16 mm; (**b**) blend 0–16 mm; (**c**) blend 0–8 mm. Figure 6: The Q–Q (quantile-quantile) plot graph for the blends. (**a**) blend 0.05–16 mm; (**b**) blend 0–16 mm; (**c**) blend 0–8 mm. For a better illustration of the nature and structure of the results and the accuracy of the tests performed, Table 2 summarizes the results of the analysis of errors for each of the tested gradients. The analysis of the test results in terms of the standard deviation and the interval between the highest and lowest result flux velocity for tests are also included (Figure 7). For the research conducted at low gradients of 0.2-0.3, the values for both the standard deviation and the interval were significantly higher. On this basis, we can conclude that the study at these gradients is unstable. \begin{table}
\begin{tabular}{c c c c c} \hline
**Hydraulic** & **Standard** & **Absolute Error of** & **Relative Error** & **Percent of Error** \\
**Gradient i (-)** & **Deviation** & **Measurement (m/s)** & **(m/s)** & **(\%)** \\ \hline \multicolumn{5}{c}{**Blend 0.5–16 mm**} \\
0.2 & \(3.4\times 10^{-6}\) & \(1.0\times 10^{-8}\) & \(1.1\times 10^{-4}\) & \(7.0\times 10^{-4}\) \\
0.3 & \(3.5\times  
In order to determine the estimated value before calculating the flux velocity average, all coefficients have been registered during the laboratory filtration process. The coefficient of permeability for all tests results was the mean, in accordance with which the average value of coefficient of permeability was calculated and presented in Table 3.  
Next, the flux velocity was calculated using Darcy's Law, \(v\) = k\(\cdot\)i, where \(v\) is the flux velocity (m/s), k is the coefficient of permeability (m/s), and i is the hydraulic gradient, also included in Table 4. In the remainder of the paper, the results obtained on the basis of these calculations will have a specific name, flux velocity for kavg. In the next step, a graph of the relationship between the average of the flux velocity and the hydraulic gradient was constructed. The trend line was derived for these values, taking into account the confidence interval at 0.95 to define the threshold gradient. The test results on unstable gradients 0.2 and 0.3 were derived with an additional trend line, marked on Figure 8, representing an unstable flux velocity, in order to verify whether this will cause the cutting of the \(x\)-axis at 0 of the confidence interval for the used linear trend line equation. It can be concluded from Figure 8 that the points of intersection with the \(x\)-axis for the unstable flux velocity are within the confidence interval or at the border, designated for all tests at specified gradients for each blend. \begin{table}
\begin{tabular}{c c c c c c} \hline \multirow{2}{*}{**i (-)**} & \multicolumn{2}{c}{**Blend 0.05–16 mm**} & \multicolumn{2}{c}{**Blend 0–16 mm**} & \multicolumn{2}{c}{**Blend 0–8 mm**} \\ \cline{2-7}  & **kavg (m/s)** & \(v\) **(m/s)** & \(\mathbf{k_{avg}}\) **(m/s)** & \(v\) **(m/s)** & \(\mathbf{k_{avg}}\) **(m/s)** & \(v\) **(m/s)** \\ \hline
0.2 & & 2.0 \(\times\) 10\({}^{-5}\) & & 3.8 \(\times\) 10\({}^{-6}\) & & 4.2 \(\times\) 10\({}^{-6}\) \\
0.3 Figure 9 presents the two methods of determining the threshold gradient (i\({}_{0}\)). The first is a simplified method based on kavg and on the basis of the determination of the flux velocity described earlier.