Title

Prediction of Subgrade Resilient Modulus Using Artificial Neural Network

Department

Civil & Construction Engineering

Document Type

Article

Publication Date

5-20-2014

Abstract

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 two replicates. The stress state and physical properties on resilient behavior of subgrade soils were successfully correlated with an ANN model developed in this paper. The results demonstrated that the stress state and physical properties of subgrade soil significantly influenced the subgrade resilient modulus, which in turn has a substantial effect on the pavement response predictions that impact pavement design.

Journal

KSCE Journal of Civil Engineering

Journal ISSN

1976-3808

Volume

18

Issue

5

First Page

1372

Last Page

1379

Digital Object Identifier (DOI)

10.1007/s12205-014-0316-6