## 4 Test Results
### Cluster Analysis  
The selection of suitable variables was extremely important in cluster analysis, as was the isolation of the principal components at the earlier stage. The key issue was to choose the variables that best represent the population of recycled MCAS mixes with waste materials. The previous stage of the analysis was aimed at eliminating outlying points and minimizing the collinearity of new variables. The subsequent grouping step was based on the new four factorial variables Z1 to Z4 and indirectly on the real variables which represented the specimens of the mixtures. [PERSON]'s method was used as a hierarchical method of agglomeration [37; 38] In practice, there is no arbitrary method that clearly states the number of clusters. The Grabinski [39] and the frequently used Sneath criterion were used in this study [40]. The limit value for the Sneath criterion is shown in Figure 3.  
The vertical axis in Figure 3 shows every second case. The main intention was to present as many cases from the specific group as possible. On the basis of the agglomeration results (Figure 3) and using four variables (Z1 to Z4), three new groups were obtained, different in terms of physical and mechanical parameters. Their differentiation was very clear given the normalized distances between the clusters. The red line in Figure 3 cuts off a set of high internal similarity objects (clusters) but characterized by a great dissimilarity between one another. This information is important because the agglomeration can be the basis for assigning particular MCAS specimens. Finally, three groups were chosen for further analysis. Table 4 shows the types of MCAS recycled mixtures represented by the highest number of specimens in the given group. Figure 3: Dendrogram showing similarities between recycled MCAS mixes with waste materials. The mix denotation as RAP20/VA80 indicates the use of 20% RAP and 80% VA in the mix. In the case of mixtures with mineral dust, D.P12.5/A1.2 denotes a blend of 12.5% dolomite mineral dust (D) and 1.2% foamed bitumen. The grouping as described above provides preliminary information on certain factors that separate the properties of the specimens being analyzed. In the present form, the amount of bitumen in the mixtures with mineral dust (D/P/A and B/P/A) was a major factor in assigning them to adequate groups. The amount and type of dust played a secondary role. Other important elements were the amount of recycled aggregate (RA) and the amount of RAP used in the recycling process. The increase in the amounts of RAP and foam bitumen caused the convergence between the grouping results for the recycled mixture specimens with the average results in Group 3. However, the presence of cement in the mix or its increased content due to the addition of recycled cement concrete materials could also influence the grouping effect because Group 1 includes a case of mixtures with high amounts of reclaimed concrete (RC) and a case of a low bitumen mixture, which may suggest excessive stiffness of the mixtures. The next step in multidimensional inference was the statistical estimation of the results within particular groups of MCAS specimens with waste materials. First, the average dynamic stiffness modulus (E) and the phase shift (\(\delta\)) were evaluated. Due to the high collinearity of rheological results and in compliance with provisions [30; 31], the results of the stiffness modulus determined at 5 \({}^{\circ}\)C and 10 Hz loading time were used for comparative purposes. As for the phase angle, the average value determined at 40 \({}^{\circ}\)C was used. This choice was based on the distinctness of this case observed in Table 3, as reflected in the behavior of the mixtures at high service temperatures. The viscoelasticity results of the recycled MCAS mixes are shown in Figure 4.  
The results in Figure 4a show that the mix specimens in Group 1 had the highest average dynamic moduli (E). The average value of the stiffness modulus determined at 5 \({}^{\circ}\)C and 10 Hz was E = 13,787 MPa.