Abstract

In recent years, the American Association of State Highway and Transportation Officials (AASHTO) has recommended the use of resilient modulus for characterizing highway materials for pavement design. This recommendation evolved as a result of a trend in pavement design of using mechanistic models, which are based on the theory of elasticity (layered elastic analysis) or linear and nonlinear, finite element and finite difference methods, or a combination of both those theoretical approaches. Although much progress has been made in recent years in developing mathematical, mechanistic pavement design models, results obtained from those models are only as good as the material parameters used in the models. Resilient modulus of the subgrade soil is an important parameter in the mechanistic models and in the 1993 AASHTO pavement design equation. The main goal of this study was to establish a simple and efficient means of predicting the resilient modulus of any given type of Kentucky soil. To accomplish this purpose, 128 tests were performed on several different soil types from various locations in Kentucky. Specimens were remolded to simulate compaction conditions encountered in the field. Tests were performed on soaked and unsoaked specimens so that an assessment could be made of the effect of moisture on resilient modulus values. Vast differences were found between soaked and unsoaked values of resilient modulus. Based on an analysis of the data, a new mathematical model is proposed which relates resilient modulus to any given selected, or calculated, principal stresses in the subgrade. This model improves the means of obtaining best data fits between resilient modulus and stresses. Furthermore, if the AASHTO classification and group index are known, then the resilient modulus of the soil can be predicted from the new model for any known stress condition in the subgrade. Multiple regression analysis was used to obtain relationships between resilient modulus and confining stress and deviator stress. No difficulties were encountered in testing as-compacted (unsoaked) samples. Values of R-squared of 91% of unsoaked test specimens were greater than, or equal to, 0.87. However, values of R-squared of only 35% of tested, soaked samples exceeded 0.87. Difficulties were encountered in testing soaked specimens. More research is needed to test saturated, or nearly saturated, soil specimens--conditions that often exist in the field. To make the resilient modulus data and the new model readily available to design personnel of the Kentucky Transportation Cabinet, a windows computer software application was developed in a client/server environment. This program is embedded in the Kentucky Geotechnical Database, which resides on a Cabinet server in Frankfort, Kentucky. The resilient predictor model and data are readily available to pavement design personnel statewide.

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