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Title:

Development of an Improved and More Effective Dynamic Modulus E* Model for Mixtures in Costa Rica by Means of Artificial Neural Networks

Accession Number:

01475553

Record Type:

Component

Availability:

Transportation Research Board Business Office

500 Fifth Street, NW
Washington, DC 20001 United States

Abstract:

Various dynamic modulus (E*) predictive models have been developed to estimate E* as an alternative to laboratory testing. The most widely used model is the 1999 I-37A Witczak predictive equation based on North American mixtures laboratory results. The differences in material properties, traffic information, and environmental conditions for Latin American countries make it necessary to calibrate these models using local conditions. Consequently, the National Laboratory of Materials and Structural Models at the University of Costa Rica (in Spanish, LanammeUCR) has previously performed a local calibration of this model based on E* values for different types of Costa Rican mixtures. However, further research has shown that there is still room for improvement in the accuracy of the calibrated model (Witczak-Lanamme model) based on advanced regression techniques such as artificial neural networks (ANN). The objective of this study was to develop an improved and more effective dynamic modulus E* predictive regression model for mixtures in Costa Rica by means of ANN based models. A comparison of the predicted E* values among the Witczak model, Witczak-Lanamme model and the new and improved model based on artificial neural networks (ANN-Lanamme model) indicated that the former not only met the model adequacy checking criteria but also exhibited the best goodness of fit parameters and the lowest overall bias. The findings of this study also supported the use of more advanced regression techniques that can become a more attractive alternative to local calibration of the Witczak I-37A equation.

Supplemental Notes:

This paper was sponsored by TRB committee AFD80 Strength and Deformation Characteristics of Pavement Sections.

Monograph Accession #:

01470560

Report/Paper Numbers:

13-2176

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Leiva-Villacorta, Fabricio
Loria-Salazar, Luis
Aguiar-Moya, José Pablo

Pagination:

17p

Publication Date:

2013

Conference:

Transportation Research Board 92nd Annual Meeting

Location: Washington DC, United States
Date: 2013-1-13 to 2013-1-17
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References; Tables

Uncontrolled Terms:

Geographic Terms:

Subject Areas:

Highways; Pavements; I22: Design of Pavements, Railways and Guideways

Source Data:

Transportation Research Board Annual Meeting 2013 Paper #13-2176

Files:

TRIS, TRB, ATRI

Created Date:

Feb 5 2013 12:29PM