## 5 Geotechnical Interpretations
### Measuring the Unified Plasticity Potential of Soils
Also, each row indicates individual soils and shows the consistency limits, clay fraction, calcium carbonate, and montmorillonite content. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**Soil Properties**} & \multicolumn{3}{c}{**Top 10 Soils Ranking**} \\ \hline
**LL (\%)** & **PI (\%)** & **Clay (\%)** & **CaCO\({}_{3}\) (\%)** & **Mont. (\%)** & **PI Rank** & **This Study** \\ \hline
207.0 & 153.0 & 70.0 & 3.7 & 52.5 & 4 & 1 \\
202.0 & 153.0 & 78.0 & 3.7 & 58.7 & 5 & 2 \\
206.0 & 155.0 & 66.0 & 3.1 & 51.2 & 3 & 3 \\
203.0 & 156.0 & 79.0 & 3.7 & 50.0 & 1 & 4 \\
191.0 & 143.0 & 71.0 & 5.0 & 47.5 & 7 & 5 \\
141.0 & 90.0 & 80.0 & 1.8 & 50.0 & 25 & 6 \\
190.0 & 141.0 & 63.0 & 2.5 & 52.2 & 8 & 7 \\
151.0 & 98.0 & 63.0 & 3.1 & 45.0 & 17 & 8 \\
200.0 & 156.0 & 72.0 & 3.1 & 50.0 & 2 & 9 \\
183.0 & 131.0 & 55.0 & 3.7 & 43.7 & 8 & 10 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: The ranking of the top 10 soils that shows the most plasticity. An inspection of Tables 5 and 6 directly reveals that there is a strong parallel relation between the PI-based ranking and this study's ranking. Considering the top 10 soils, there is a very slight difference in ranking on most of the soils, only the sixth and eighth soils show a reasonable difference. The reason for this disparity is related to the considerably lower plasticity index of the sixth and eighth soils. However, careful examination of the factor analysis shows that the standardized score, i.e., plasticity potential, was calculated by assuming the consistency limits, clay fraction and montmorillonite content contribute to the plasticity of soils almost equally. This conclusion can be seen by examining the factor score coefficients in Appendix A. Examination of the least potentially plastic soils (Table 6) also coincides with the finding of the most potentially plastic soils. Therefore, this model can be assumed to work in a wide range of soil plasticity. The above-mentioned facts justify that a quantitative model can be formulated to measure the plasticity potential of soils. Presently, the finding is very definite: the standardized score is the plasticity potential of soils that can be assigned from 0 to 100. If this model is formulated, then one could assess the plasticity potential of any soil easily. However, there should be a reliable way to predict this plasticity potential. For this purpose, some soil parameters that are easy to derive that represent different properties of the soil should be used. Considering the liquid and plastic limits, clay fraction, montmorillonite and calcium carbonate content were already used in the analysis. Therefore, if these soil properties are used for the prediction, then there will be an overlapping measure within the model. Which invalidates the whole theory. However, the plasticity index itself was not an input parameter in the analysis, therefore the PI is one of the soil properties that can be used in a way to predict the soil plasticity potential. Figure 6 shows the relationship between this model and PI. The relationship between this model and PI yielded a very strong correlation coefficient of 0.908. This indicates the PI can be confidently used to predict the unified plasticity potential of the soils. The elemental aspect of using this model instead of PI alone is that in this study the plasticity potential of soils was measured by five different soil properties. However, the PI alone is rather a sole parameter. Therefore, using the PI to predict this study's plasticity model allows the user to evaluate the soil plasticity in a more refined and realistic way. Therefore, using this model should represent a much more accurate way of soil plasticity. In fact, one can assume that this model is a modified plasticity index to some degree. Also, the plasticity potential is formulated as a logarithmic function of the plasticity index as shown in the equation below.