Document Type

Conference Proceeding

Conference

ANNs in Engineering

Publication Date

2007

Research Focus Area

Transportation Engineering

DOI

10.1115/1.802655.paper18

City

St. Louis, Missouri

Abstract

The primary objective of this study is to develop a simplified Hot Mix Asphalt (HMA) dynamic modulus (|E*|) prediction model with fewer input variables compared to the existing regression based models without compromising prediction accuracy. ANN-based prediction models were developed using the latest comprehensive |E*| database that is available to the researchers containing 7,400 data points from 346 HMA mixtures. The ANN model predictions were compared with the existing regression-based prediction models which are included in the latest Mechanistic-Empirical Pavement Design Guide (MEPDG). The ANN based |E*| models show significantly higher prediction accuracy compared to the existing regression models although they require relatively fewer inputs. The findings of this study present a “paradigm shift” in the way the hot-mix asphalt material characterization has been handled by pavement materials engineers.

Comments

This is a manuscript of an article from ANNIE 2007, ANNs in Engineering Conference, St. Louis, Missouri, November 10-14, 2007. Posted with permission.

Copyright Owner

American Society of Mechanical Engineers

Language

en

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