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78 Table 17 Model Correlations Developed by Malla and Joshi (2006) Several independent variables are used to reflect soil of their study. They noted considerable differences between type and current soil physical condition (Titi et al. 2006). predictions and measurements, which were attributed to dif- These are percent passing sieve #4 (PNo.4), percent passing ferences in test procedures and other conditions present in sieve #40 (PNo.40 ), percent passing sieve #200 (PNo.200 ), the LTPP database. liquid limit (LL), plastic limit (PL), plasticity index (PI), liquidity index (LI), amount of sand (%Sand), amount of silt (%Silt), amount of clay (%Clay), water content (w), Matrix Tables and dry unit weight (γd). The optimum water content (wopt.) and maximum dry unit weight (γdmax) and combi- In this section, the existing literature information is sum- nations of variables were also included (Titi et al. 2006). marized in a matrix format. The main focus of the table is to The developed models were evaluated based on the mul- provide a thorough assessment of various laboratory and field tiple collinearity problems and coefficient determination methods for determining the resilient properties of unbound values. bases and subgrades. Again, this assessment is based on the available information presented in this report. Table 18 presents equations recommended for fine- grained, plastic coarse-grained, and nonplastic coarse- Tables 19 and 20 provide a matrix-style comparison of grained soils. Figure 86 presents a typical comparison various items, including applicable soil types, relation to analysis for fine-grained soils. The results show that the pre- design modulus, type of MR interpretation (direct or indi- dicted moduli using recommended equations matched well rect), standardization, need for skilled personnel to perform with measured moduli. the test, cost details, applicability in new pavement con- struction projects, pavement rehabilitation projects, need of Titi et al. (2006) also presented a comprehensive analysis additional tests for validation, and type of MR correlations in which they predicted moduli using correlations developed that the test results provide. Table 21 presents an overview of from the LTPP database by Yau and Von Quintus (2004) the assessments of the modeling correlations. Assessments and compared the correlations with the measured moduli are based on repeatability and reliability of correlations,

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 79 Table 18 Correlations Developed for Wisconsin Subgrade Soils (Titi et al. 2006) Soil type Model Correlations Fine-Grained Soils Coarse-grained, non-plastic Coarse-grained, Plastic