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Title:

Generalized Regression Approach to Develop Predictive Models for Dynamic Modulus and Phase Angle of Asphalt Mixtures

Accession Number:

01628584

Record Type:

Component

Abstract:

Dynamic modulus (|E*|) and phase angle (δ) are viscoelastic properties of asphalt mixtures that are necessary for determination of constitutive response of mixtures to traffic and thermal loading. These parameters are necessary for analysis and design of asphalt pavements. While a number of |E*| and δ predictive models have been developed, many of them require lab measured properties, such as, gradation and binder complex modulus (G*) for accurate predictions. Furthermore, the majority of previous work has been focused on prediction of |E*| and only few models have been explored for prediction of δ. This research utilized generalized regression modelling to develop |E*| and δ prediction models using nominal asphalt mix properties (such as, asphalt content, air void and aggregate size) that are often readily available during initial mixture design and specification process. Using nominal properties not only eliminates need for even the simplest lab tests, but also provides the pavement design engineers with the ability to conduct mechanistic analysis with reliable material properties. A total of 81 asphalt mixtures and 4374 lab measurements of |E*| and δ each were used for model development. The accuracy of prediction models is verified through statistical analysis. A case study is presented to demonstrate applicability of these models for performance predictions. The case study also presents verification that there are minimal differences in performance predictions when using predicted properties as compared to lab measured properties.

Supplemental Notes:

This paper was sponsored by TRB committee AFK50 Standing Committee on Structural Requirements of Asphalt Mixtures.

Monograph Accession #:

01618707

Report/Paper Numbers:

17-03440

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Nemati, Rasool
Dave, Eshan V

Pagination:

21p

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

Uncontrolled Terms:

Performance prediction; Phase angle

Subject Areas:

Highways; Materials; Pavements

Source Data:

Transportation Research Board Annual Meeting 2017 Paper #17-03440

Files:

TRIS, TRB, ATRI

Created Date:

Dec 8 2016 11:18AM