数字图像相关
不连续性分类
断裂力学
开裂
断裂(地质)
数字图像
材料科学
沥青混凝土
结构工程
流离失所(心理学)
计算机科学
沥青
图像处理
工程类
数学
复合材料
图像(数学)
人工智能
心理学
数学分析
心理治疗师
作者
Zehui Zhu,Imad L. Al-Qadi
出处
期刊:Journal of transportation engineering
[American Society of Civil Engineers]
日期:2023-09-01
卷期号:149 (3)
被引量:5
标识
DOI:10.1061/jpeodx.pveng-1249
摘要
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 (δc) to define the onset of cleavage fracture. The proposed method relies on well-developed fracture mechanics theory. The proposed threshold δc 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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