Document Type

Article

Publication Date

2008

Journal or Book Title

Institution of Engineers Singapore Journal Part A: Civil and Structural Engineering

Volume

1

Issue

4

First Page

280

Last Page

290

DOI

10.1080/19373260802217892

Abstract

The falling weight deflectometer (FWD) is a non-destructive test equipment used to assess the structural condition of highway and airfield pavement systems and to determine the moduli of pavement layers. The backcalculated moduli are not only good pavement layer condition indicators but are also necessary inputs for conducting mechanistic based pavement structural analysis. In this study, artificial neural networks (ANNs)-based backcalculation models were employed to rapidly and accurately predict flexible airport pavement layer moduli from realistic FWD deflection basins acquired at the U.S. Federal Aviation Administration's National Airport Pavement Test Facility (NAPTF). The uniformity characteristics of NAPTF flexible pavements were successfully mapped using the ANN predictions.

Research Focus Area

Construction Engineering and Management, Transportation Engineering

Comments

This is a manuscript of an article from IES Journal Part A: Civil & Structural Engineering 1 (2008): 280, doi: 10.1080/19373260802217892. Posted with permission.

Copyright Owner

Taylor & Francis

Language

en

File Format

application/pdf

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