Crack Detection of Asphalt Concrete Using Combined Fracture Mechanics and Digital Image Correlation
Publication: Journal of Transportation Engineering, Part B: Pavements
Volume 149, Issue 3
Abstract
Cracking is a common failure mode in asphalt concrete (AC) pavements. Many tests have been developed to characterize the fracture behavior of AC. Accurate crack detection during testing is crucial to describe AC fracture behavior. This paper proposes a framework to detect surface cracks in AC specimens using two-dimensional digital image correlation (DIC). Two significant drawbacks in previous research in this field were addressed. First, a multiseed incremental reliability-guided DIC was proposed to solve the decorrelation issue due to large deformation and discontinuities. The method was validated using synthetic deformed images. A correctly implemented analysis could accurately measure strains up to 450%, even with significant discontinuities (cracks) present in the deformed image. Second, a robust method was developed to detect cracks based on displacement fields. The proposed method uses critical crack tip opening displacement () to define the onset of cleavage fracture. The proposed method relies on well-developed fracture mechanics theory. The proposed threshold has a physical meaning and can be easily determined from DIC measurement. The method was validated using an extended finite-element model. The framework was implemented to measure the crack-propagation rate while conducting the Illinois-flexibility index test on two AC mixes. The calculated rates could distinguish mixes based on their cracking potential. The proposed framework could be applied to characterize AC cracking phenomenon, evaluate its fracture properties, assess asphalt mixture testing protocols, and develop theoretical models.
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Data Availability Statement
All data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors would like to thank the research engineers and students at the Illinois Center for Transportation for their input and support during this study. Special thanks to Greg Renshaw, Uthman Mohamed Ali, and Jose Julian Rivera Perez. The contents of this paper reflect the view of the authors, who are responsible for the facts and the accuracy of the data presented here.
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Published In
Journal of Transportation Engineering, Part B: Pavements
Volume 149 • Issue 3 • September 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Jun 15, 2022
Accepted: Mar 6, 2023
Published online: May 8, 2023
Published in print: Sep 1, 2023
Discussion open until: Oct 8, 2023
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