Development of dynamic modulus master curves of in-service asphalt layers using MEPDG models

被引:21
|
作者
Solatifar, Nader [1 ]
Kavussi, Amir [2 ]
Abbasghorbani, Mojtaba [3 ]
Katicha, Samer W. [4 ]
机构
[1] Urmia Univ, Dept Civil Engn, Orumiyeh, Iran
[2] Tarbiat Modares Univ, Fac Civil & Environm Engn, Tehran, Iran
[3] Tech & Soil Mech Lab, Consultant Engn Off, Tehran, Iran
[4] Virginia Polytech Inst & State Univ, Virginia Tech Transportat Inst, Ctr Sustainable Transportat Infrastruct, Blacksburg, VA 24061 USA
关键词
asphalt dynamic modulus; MEPDG; NCHRP 1-37A (Witczak) model; NCHRP 1-40D (Modified Witczak) model; FWD; hot climate areas; RESILIENT MODULUS; PREDICTIVE MODELS; CONCRETE; PERFORMANCE; MIXTURES;
D O I
10.1080/14680629.2017.1380688
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The new mechanistic-empirical pavement design guide (MEPDG) uses a combination of field and laboratory tests for structural analysis of in-service pavements. In this guide, asphalt dynamic modulus (|E*|) is one of the most important parameters used in flexible pavement design and rehabilitation approaches. This paper evaluates the validity of dynamic modulus models used in MEPDG for in-service asphalt pavements. For this purpose, nine asphalt pavement sites with various structural, ages and conditions were selected in Khuzestan and Kerman provinces in southern regions in Iran. At each site, falling weight deflectometer data, resilient modulus (determined from the cored samples) and surface condition data were collected. These three sets of data are necessary to compute damages at input levels of 1, 2 and 3 in MEPDG, respectively. Core samples were extracted, and mix volumetric properties as well as their binder characteristics were determined. Viscosity-based NCHRP 1-37A (Witczak) and G*-based NCHRP 1-40D (Modified Witczak) dynamic modulus predictive models were incorporated into these three input levels and six combinations of in situ |E*| master curves were developed. Analysis of the results indicates a weak correlation between field backcalculated moduli and those measured in laboratory. Hence, application of both field and laboratory moduli is not necessarily a good approach to determine damages, and the MEPDG proposed method would better be modified. Validation of MEPDG models showed that the NCHRP 1-37A model predicts dynamic modulus master curves with lower errors rather than the NCHRP 1-40D model. In addition, using the NCHRP 1-37A model at input level 1 would be a better approach among the others to evaluate both new and rehabilitated asphalt layers. Results will also be useful for local agencies in implementation of American Association of State Highway and Transportation Officials (AASHTO)mechanistic-empirical pavement design procedure in various climatic conditions.
引用
收藏
页码:225 / 243
页数:19
相关论文
共 50 条
  • [1] APPLICATION OF FWD DATA IN DEVELOPING DYNAMIC MODULUS MASTER CURVES OF IN-SERVICE ASPHALT LAYERS
    Solatifar, Nader
    Kavussi, Amir
    Abbasghorbani, Mojtab
    Sivilevicius, Henrikas
    JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT, 2017, 23 (05) : 661 - 671
  • [2] Dynamic Modulus Predictive Models for In-Service Asphalt Layers in Hot Climate Areas
    Solatifar, Nader
    Kavussi, Amir
    Abbasghorbani, Mojtaba
    JOURNAL OF MATERIALS IN CIVIL ENGINEERING, 2021, 33 (02)
  • [3] Dynamic Modulus Master Curve Construction Using the Modified MEPDG Model
    Rais, Nuryantizpura Mohamad
    Ab Wahab, Md. Yunus
    Endut, Intan Rohani
    Ab Latif, Amminudin
    2013 FIRST INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, MODELLING AND SIMULATION (AIMS 2013), 2013, : 212 - 216
  • [4] Study on Dynamic Modulus Prediction Model of In-Service Asphalt Pavement
    Wang, Duanyi
    Luo, Chuanxi
    Li, Jian
    He, Jun
    BUILDINGS, 2024, 14 (08)
  • [5] Effect of reclaimed asphalt shingles addition on asphalt concrete dynamic modulus master curves
    Zielinski, P.
    ARCHIVES OF CIVIL ENGINEERING, 2021, 67 (03) : 109 - 122
  • [6] Development of dynamic modulus master curves for hot-mix asphalt with abbreviated testing temperatures
    Apeagyei, Alex K.
    Diefenderfer, Brian K.
    Diefenderfer, Stacey D.
    INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING, 2012, 13 (02) : 98 - 109
  • [7] Performance of MEPDG Dynamic Modulus Predictive Models for Asphalt Concrete Mixtures: Local Calibration for Idaho
    El-Badawy, Sherif
    Bayomy, Fouad
    Awed, Ahmed
    JOURNAL OF MATERIALS IN CIVIL ENGINEERING, 2012, 24 (11) : 1412 - 1421
  • [8] A method of estimating tensile strength master curves using dynamic storage modulus master curves
    Wang, Xiao-Ying
    Yin, Xin-Mei
    Wang, Yue
    Huang, Ying
    Zhou, Hong-Mei
    Guti Huojian Jishu/Journal of Solid Rocket Technology, 2013, 36 (01): : 79 - 82
  • [9] Developing Master Curves and Predicting Dynamic Modulus of Polymer-Modified Asphalt Mixtures
    Zhu, Haoran
    Sun, Lu
    Yang, Jun
    Chen, Zhiwei
    Gu, Wenjun
    JOURNAL OF MATERIALS IN CIVIL ENGINEERING, 2011, 23 (02) : 131 - 137
  • [10] Probabilistic Modeling of Dynamic Modulus Master Curves for Hot-Mix Asphalt Mixtures
    Kahil, Noura Sirine
    Najjar, Shadi S.
    Chehab, Ghassan
    TRANSPORTATION RESEARCH RECORD, 2015, (2507) : 90 - 99