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Title:

Developing Rigid Airport Pavement Multiple-Slab Response Models for Top-Down Cracking Mode using Artificial Neural Networks
Cover of Developing Rigid Airport Pavement Multiple-Slab Response Models for Top-Down Cracking Mode using Artificial Neural Networks

Accession Number:

01625820

Record Type:

Component

Abstract:

The Federal Aviation Administration (FAA) has recognized for some time that its current rigid pavement design model, involving a single slab loaded at one edge by a single aircraft gear, is inadequate to account for top-down cracking. Thus, one of the major observed failure modes for rigid pavements is poorly represented in the FAA Rigid and Flexible Iterative Elastic Layer Design (FAARFIELD) program. A research version of the FAARFIELD design software has been developed (FAARFIELD 2.0), in which the single-slab three-dimensional finite element (3D-FE) response model is replaced by a 4-slab 3D-FE model with initial temperature curling to produce reasonable thickness designs accounting for top-down cracking behavior. However, the long and unpredictable run times associated with the 4-slab model and curled slabs make routine design with this model impractical. In this paper, use of artificial intelligence (AI)-based alternatives such as artificial neural networks (ANNs) with potential for producing accurate stress predictions in a fraction of the time needed to perform a full 3D-FE computation has been investigated. In the development of ANN models, a synthetic database of FAARFIELD input-output pairs representing a number of realistic scenarios were developed. Moreover, ANN models for only mechanical and simultaneous mechanical and thermal loading cases were developed and accuracy predictions of these models were documented. It was observed that very high accuracies were achieved in predicting pavement responses for all cases investigated.

Supplemental Notes:

This paper was sponsored by TRB committee AV070 Standing Committee on Aircraft/Airport Compatibility.

Monograph Accession #:

01618707

Report/Paper Numbers:

17-05375

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Kaya, Orhan
Rezaei-Tarahomi, Adel
Ceylan, Halil
Gopalakrishnan, Kasthurirangan
Kim, Sunghwan
Brill, David R

Pagination:

12p

Publication Date:

2017

Conference:

Transportation Research Board 96th Annual Meeting

Location: Washington DC, United States
Date: 2017-1-8 to 2017-1-12
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References; Tables

Subject Areas:

Aviation; Design; Pavements

Source Data:

Transportation Research Board Annual Meeting 2017 Paper #17-05375

Files:

PRP, TRIS, TRB, ATRI

Created Date:

Dec 8 2016 12:07PM