Investigation of factors affecting dynamic modulus and phase angle of various asphalt concrete mixtures

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• 作者：Yasir Ali ; Muhammad Irfan ; Sarfraz Ahmed ; Shahab Khanzada…
• 关键词：Asphalt concrete ; Mixtures ; Dynamic modulus ; Regression model
• 刊名：Materials and Structures
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：49
• 期：3
• 页码：857-868
• 全文大小：1,305 KB
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• 作者单位：Yasir Ali (1)
  Muhammad Irfan (2)
  Sarfraz Ahmed (2)
  Shahab Khanzada (3)
  Tariq Mahmood (4)
  
  1. School of Civil & Environmental Engineering (SCEE), National Institute of Transportation (NIT), National University of Sciences & Technology (NUST), Islamabad, 44000, Pakistan
  2. Military College of Engineering, National University of Sciences & Technology, NUST Campus, Risalpur, 24080, Pakistan
  3. National Highway Authority (NHA), Mauve Area, G-9/1, Islamabad, 44000, Pakistan
  4. School of Civil & Environmental Engineering (SCEE), National University of Sciences & Technology (NUST), Islamabad, 44000, Pakistan
  
• 刊物类别：Engineering
• 刊物主题：Structural Mechanics
  Theoretical and Applied Mechanics
  Mechanical Engineering
  Operating Procedures and Materials Treatment
  Civil Engineering
  Building Materials
  
• 出版者：Springer Netherlands
• ISSN：1871-6873

文摘

This study investigated the dynamic response of various asphalt concrete (AC) mixtures subjected to sinusoidal loading. Eight AC mixtures (four wearing and four base course) were selected including (but not limited to): superpave, asphalt institute manual series, and dense bituminous macadam. The uniaxial dynamic modulus (|E*|) test at various temperatures (4.4–54.4 °C) and frequencies (0.1–25 Hz) was conducted using asphalt mixture performance tester. Statistical analysis of two-level factorial was employed to regulate the factors affecting the AC mixtures. The results revealed that an increase in temperature (from 21.1 to 37.8 °C), translated into 45 and 43 % drop in |E*| values on average while 80 and 67 % decrease in |E*| values was attributed to the sweep of frequency (from 25 to 0.1 Hz) for wearing and base course mixes, respectively. Non-linear regression model was developed to express the dynamic modulus as a function of test temperature, loading frequency and mixture volumetric parameter. Furthermore, Witczak model of dynamic modulus prediction was evaluated and the results indicated a close fit with an average under prediction error of 0.20. The study characterized and ranked the representative AC mixtures that could help in selecting the material/gradation for mechanistic-empirical pavement design approach. Keywords Asphalt concrete Mixtures Dynamic modulus Regression model