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International Journal of Advanced Engineering, Management and Science


ANN Models to Correlate Structural and Functional Conditions in AC Pavements at Network Level

( Vol-3,Issue-9,September 2017 )

Author(s): Fawaz Alharbi, Omar Smadi



Total View : 1681
Downloads : 164
Page No: 919-923
ijaems crossref doiDOI: 10.24001/ijaems.3.9.3

Keywords:

Artificial Neural Network, AC pavement, Functional Performance, Iowa pavements, Structural performance,

Abstract:

Artificial Neural Network (ANN) model was developed to estimate the correlation between structural capacity and functional conditions in Asphalt Cement (AC) pavements at the network level. To achieve this objective, the relevant data were obtained and integrated from the Iowa Pavement Management Program (IPMP) including construction parameters, traffic loading and subgrade stiffness, and Iowa Environmental Mesonet (IEM) for climate data. The ANN model proves its ability to learn and generalize from the input data. Overall, rutting data were found to be appropriate indicator of the structural capacity. Since the deflection tests are expensive and require experience and knowledge to deal with such data, this approach might be feasible for small transportation agencies (cities and counties) that do not have these capabilities.

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