Cyclic Loading Behavior of Asphalt Concrete Mixture Using Disk-Shaped Compact Tension (DC(T)) Test and Released Energy Approach

The evaluation of fracture behavior under cyclic loading using the disk-shaped compact tension (DC(T)) test and a released energy based analysis approach is the focus of this study. The cyclic DC(T) test was developed based on the monotonic DC(T) test (Wagoner and Buttlar, 2005); however, some modifications to the geometry and testing mode were necessary to facilitate the cyclic fracture test. Exploring possible extensions of the DC(T) test device to consider cyclic fracture phenomena such as cyclic thermal cracking, block cracking and reflective cracking was the motivation of the research. Under cyclic loading at four test temperatures (-12, 0, 10, and 20oC), five different asphalt concrete mixes were tested. Selected for this study as the standard testing parameters were the load-controlled testing mode utilizing a sine waveform and a frequency of 0.5 Hz with no rest period, after an extensive exploratory stage. A peak load obtained from the monotonic DC(T) test was additionally used as a reference value for determining loading magnitudes of the cyclic DC(T) test for a given mixture and test temperature. A released energy approach was introduced as a key concept for characterization of the cyclic fracture data generated in this study, for data analysis. A released energy rate parameter, R2, was identified with the characteristic of mixture and temperature independence, stemming from this approach. It was shown that cyclic loading behavior could be predicted based upon three different data sets deriving from the DC(T) test, by correlating a fracture energy based parameter to released energy rate (R2): one that involved a comprehensive cyclic loading testing suite; a somewhat simpler method involving a limited number of required cyclic tests; and a highly simplified approach where cyclic fracture behavior was predicted using monotonic fracture test results alone (standard DC(T) fracture energy). While all three prediction methods were shown to be plausible, the more rigorous the testing suite, the more accurate the prediction, as was expected. The authors provide practical extensions of the work for design and analysis.


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  • Accession Number: 01606986
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jul 27 2016 4:54PM