Document Type

Conference Proceeding

Conference

ANNIE 2006, ANN in Engineering

Publication Date

2006

Research Focus Area

Transportation Engineering

DOI

10.1115/1.802566.paper55

City

St. Louis, Missouri

Abstract

The primary objective of this study was to assess the pavement structural deterioration based on Non-Destructive Test (NDT) data using an Artificial Neural Networks (ANN) based approach. ANN-based prediction models were developed for rapid determination of flexible airfield pavement layer stiffnesses from actual NDT deflection data collected in the field in real time. For training the ANN models, ILLI-PAVE, an advanced finite-element pavement structural model which can account for non-linearity in the unbound pavement granular layers and subgrade layers, was employed. Using the ANN-predicted moduli based on the NDT test results, the relative severity effects of simulated Boeing 777 (B777) and Boeing 747 (B747) aircraft gear trafficking on the structural deterioration of National Airport Pavement Test Facility (NAPTF) flexible pavement test sections were characterized.

Comments

This is a manuscript of an article from ANNIE 2006, ANN in Engineering Conference, St. Louis, Missouri, November 5-8, 2006

Copyright Owner

American Society of Mechanical Engineers

Language

en

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