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Application of FWD data in developing dynamic modulus master curves of in-service asphalt layers

    Nader Solatifar Affiliation
    ; Amir Kavussi Affiliation
    ; Mojtaba Abbasghorbani Affiliation
    ; Henrikas Sivilevičius Affiliation

Abstract

This paper presents a simple method to determine dynamic modulus master curve of asphalt layers by con­ducting Falling Weight Deflectometer (FWD) for use in mechanistic-empirical rehabilitation. Ten new and rehabilitated in-service asphalt pavements with different physical characteristics were selected in Khuzestan and Kerman provinces in south of Iran. FWD testing was conducted on these pavements and core samples were taken. Witczak prediction model was used to predict dynamic modulus master curves from mix volumetric properties as well as the bitumen viscosity characteristics. Adjustments were made using FWD results and the in-situ dynamic modulus master curves were ob­tained. In order to evaluate the efficiency of the proposed method, the results were compared with those obtained by us­ing the developed procedure of the state-of-the-practice, Mechanistic-Empirical Pavement Design Guide (MEPDG). Re­sults showed the proposed method has several advantages over MEPDG including: (1) simplicity in directly constructing in-situ dynamic modulus master curve; (2) developing in-situ master curve in the same trend with the main predicted one; (3) covering the large differences between in-situ and predicted master curve in high frequencies; and (4) the value obtained for the in-situ dynamic modulus is the same as the value measured by the FWD for a corresponding frequency.

Keyword : dynamic modulus, Witczak prediction model, Falling Weight Deflectometer (FWD), Mechanistic-Empirical Pavement Design Guide (MEPDG), in-service pavements

How to Cite
Solatifar, N., Kavussi, A., Abbasghorbani, M., & Sivilevičius, H. (2017). Application of FWD data in developing dynamic modulus master curves of in-service asphalt layers. Journal of Civil Engineering and Management, 23(5), 661-671. https://doi.org/10.3846/13923730.2017.1292948
Published in Issue
May 24, 2017
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