Temperature dependency analysis of the fracture characteristics of semi-flexible pavement (SFP) mixtures using acoustic emission technique

级配 声发射 材料科学 薄泥浆 开裂 复合材料 骨料(复合) 断裂(地质) 水泥 联锁 收缩率 中尺度气象学 极限抗拉强度 沥青 岩土工程 结构工程 计算机科学 工程类 地质学 气候学 计算机视觉
作者
Xing Cai,Zhen Leng,Prabin Kumar Ashish,Chenguang Shi,Jun Yang,Minghui Gong
出处
期刊:International Journal of Pavement Engineering [Taylor & Francis]
卷期号:24 (1) 被引量:7
标识
DOI:10.1080/10298436.2023.2201903
摘要

ABSTRACTABSTRACTThe poor cracking resistance of Semi-Flexible Pavement (SFP) mixture has limited its wider application. Particularly, the dual skeletal interlocking structure makes its damage process complicated. Its fracture process is expected to change with aggregate gradation and temperature, but the relevant knowledge is very limited. Thus, this study aims to investigate the effects of the two factors on the fracture characteristics of SFP using the acoustic emission (AE) technique and X-ray computed tomography (CT) approach. SFP specimens with three gradations (the target cement grout volume is 22%, 25% and 30%, respectively) were fabricated and subjected to the split tensile tests at three different temperatures (−10°C, 10°C and 25°C). Machine learning-based techniques were applied to analyze the AE signals to improve the understanding of the mesoscale damage process. Although the analysis of macro mechanical parameters showed the diminishing effect of temperature dependency on the fracture process with an increase in cement grout volume, the effect was found to be still significant based on the mesoscale analysis. Besides, it was found that the damage process transferred from the main crack going through cement to distributed meso-cracks in asphalt and cement with the temperature increase.KEYWORDS: Semi-flexible pavement materialsplitting processfracture characteristicdamage modeacoustic emissionpattern recognition Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThe work described in this paper was partially supported by a grant from the National Key R&D Program of China (No.: 2021YFB2601000), Research Grants Council of the Hong Kong Special Administrative Region, China (PolyU 15204022 for GRF project funded in 2022/23 Exercise) and the National Natural Science Foundation of China (No. 52208283).
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