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Prediction of Subgrade Resilient Modulus using Artificial Neural Network
김성희,양지동,정진훈 대한토목학회 2014 KSCE JOURNAL OF CIVIL ENGINEERING Vol.18 No.5
The development of an Artificial Neural Network (ANN) model to estimate subgrade resilient modulus is described in this paper. Nine (9) different sources of subgrade materials locally available in Georgia were subjected to the resilient modulus test with tworeplicates. The stress state and physical properties on resilient behavior of subgrade soils were successfully correlated with an ANNmodel developed in this paper. The results demonstrated that the stress state and physical properties of subgrade soil significantlyinfluenced the subgrade resilient modulus, which in turn has a substantial effect on the pavement response predictions that impactpavement design.
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Use of Linear Viscoelastic Theory to Predict Resilient Behavior of Unbound Granular Materials
김성희,Kevin McFall,권재현,양지동,정진훈 대한토목학회 2016 KSCE JOURNAL OF CIVIL ENGINEERING Vol.20 No.5
This paper presents a methodology to estimate the stress-strain relationship of an unbound aggregate base using linear viscoelastic theory. Current Mechanistic-Empirical (ME) pavement design procedure adopts the resilient modulus concept to explain the behavior of granular materials for flexible pavement design. The resilient modulus is a stress dependent material property of granular materials that is different from strength. Although California Bearing Ratio (CBR) test results (i.e., stress and strain) can be used to estimate the strength of a granular material, it is not possible to estimate the resilient modulus directly. Therefore, it is necessary to estimate stress along with strain changes. The convolution integral enables the stress to be estimated from the given strain changes only if the relaxation modulus is measured. Aggregate specimens prepared from two different sources in Georgia were subjected to the relaxation modulus test. From the test data, the time-dependent stress due to a known strain rate was computed as a convolution integral of the strain. The computed stress-strain relationship was compared with that from the resilient modulus (MR) test. The results indicate that the stress-strain relationships from the MR test and the convolution integral are similar with nearly the same slopes when horizontal stress is assumed to be approximately 45% of vertical stress. This observation supports the use of the proposed methodology by state highway agencies to validate the MR test results for quality control and quality assurance of aggregate base material selection for pavement design and construction.
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