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82 and base materials. In cases in which testing equipment reveals that newer routine analyses are needed or that the are not available, a threshold value based on the available test database needs to be carefully screened before it is used soil property range in the literature or a value determined to develop correlations. Screening of the data is needed to from MR empirical correlations is chosen. In such cases, address the material variability, quality controls in testing, engineering judgment should be exercised. Recommended and variability of testing methods used to determine resilient approaches for determining resilient or elastic moduli are properties. mentioned in chapter six. Recent exercises using more rigorous statistical approaches by following “joint estimation and mixed effects” appear to Summary provide good correlations (Archilla et al. 2007). Archilla et al. (2007) mentioned one such procedure in the recent yet It is difficult to list the modeling component of each resilient unpublished[still in press or published in 2007?] research. modulus study performed in the literature. In most of these Independent validation studies are needed to evaluate and studies, the correlations developed are shown to predict better understand these methods in providing improved the moduli properties accurately, as observed by two stud- resilient moduli predictions. ies reported here by Santha (1994) and Maher et al. (2000). Problems arise when the correlations developed elsewhere Other methods such as the one developed by Han et al. are tested on different soils. As shown by Wolfe and Buta- (2006) use statistical approaches in an expert system for lia (20004) and Malla and Joshi (2006), the model corre- predicting resilient properties. In this method, the user is lations provide poor predictions when used on other soils. given four alternate methods, one based on certainty rules Such problems should be expected because correlations are and three based on statistical methods, to predict resilient developed from data that may have shown large variations properties. Based on the reasonableness and accuracy of the for similar types, similar compaction, and stress conditions. data provided by the user, the expert system picks the model and provides predictions of moduli. Han et al. (2006) noted For example, Von Quintus and Killingsworth (1998) that, although the initial validation studies show encourag- and Yau and Von Quintus (2002, 2004) developed correla- ing results, more research studies are needed to improve the tions from the LTPP database that showed high R2 values quality of the estimation. These recent studies all show that from the statistical regression analysis. When attempted the new analyses are providing directions that could lead to on other soils for other states, however, these correlations better estimation of resilient properties of both bases and have provided poor predictions of resilient properties. This subgrades using powerful statistically intensive tools.