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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 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 Title: Monograph Accession #: 01470560
Report/Paper Numbers: 13-2176
Language: English
Corporate Authors: Transportation Research Board 500 Fifth Street, NW Authors: Leiva-Villacorta, FabricioLoria-Salazar, LuisAguiar-Moya, José PabloPagination: 17p
Publication Date: 2013
Conference:
Transportation Research Board 92nd Annual Meeting
Location:
Washington DC, United States Media Type: Digital/other
Features: Figures; References; Tables
TRT Terms: 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
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