Characterizing fatigue damage evolution in asphalt mixtures using acoustic emission and Gaussian mixture model analysis

被引:9
作者
Wei, Hui [1 ,2 ]
Liu, Yunyao [1 ]
Li, Jue [3 ]
Wang, Feiyue [4 ]
Zheng, Jianlong [1 ,2 ]
Yuan, Ziyang [1 ]
机构
[1] Changsha Univ Sci & Technol, Engn Res Ctr Catastroph Prophylaxis & Treatment Rd, Minist Educ, Changsha 410114, Peoples R China
[2] Xiangjiang Lab, Changsha 410205, Peoples R China
[3] Chongqing Jiaotong Univ, Coll Traff & Transportat, Chongqing 400074, Peoples R China
[4] Cent South Univ, Sch Civil Engn, Changsha 410083, Peoples R China
基金
中国国家自然科学基金;
关键词
Asphalt mixture; Fatigue failure; Acoustic emission parameter; Gaussian mixture model; Damage mode; CLASSIFICATION;
D O I
10.1016/j.conbuildmat.2023.133973
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The identification and investigation of fatigue crack evolution and damage modes in asphalt mixtures are crucial for understanding the corresponding mechanisms and characteristics of fatigue failure. In this study, the fourpoint bending fatigue tests were performed on the asphalt mixture specimens with precast joints using the acoustic emission (AE) technique to analyze the damage evolution. The failure modes of the asphalt mixtures were identified using the Gaussian mixture model (GMM). The results revealed that the fatigue damage of the asphalt mixtures can be categorized into four stages: Stage I (void compaction), Stage II (microcrack initiation and stable propagation), Stage III (crack aggregation and unstable propagation), and Stage IV (complete fracture). This division was defined based on the inflection points of the axial displacement curves, the cumulative number of AE events, and the cumulative ringing counts. The evolution of the AE b value was found to be correlated with the crack propagation. The rapid decline in the b value in Stage III was considered a harbinger of the eventual complete fracture in the asphalt mixtures. The GMM clustering analysis indicated that the fatigue damage of the asphalt mixtures primarily involved tensile damage (90%), and shear damage made a small contribution of 10%. Existing AE studies have focused on the quantitative evaluation of AE parameters, while research on clustering identification algorithms for these parameters is scarce. The analytical methods and findings of this study enable an effective identification of fatigue damage in asphalt mixtures at the laboratory scale and offer insights into the fatigue damage mechanisms of asphalt mixtures.
引用
收藏
页数:14
相关论文
共 47 条
  • [1] [Anonymous], 1945, NATURE, V156, P371
  • [2] Effects of Recycled Asphalt Pavement Amounts on Low-Temperature Cracking Performance of Asphalt Mixtures Using Acoustic Emissions
    Behnia, Behzad
    Dave, Eshan V.
    Ahmed, Sarfraz
    Buttlar, William G.
    Reis, Henrique
    [J]. TRANSPORTATION RESEARCH RECORD, 2011, (2208) : 64 - 71
  • [3] Fatigue process analysis of aged asphalt concrete from two-point bending test using acoustic emission and curve fitting techniques
    Benaboud, Soufyane
    Takarli, Mokhfi
    Pouteau, Bertrand
    Allou, Fatima
    Dubois, Frederic
    Hornych, Pierre
    Nguyen, Mai Lan
    [J]. CONSTRUCTION AND BUILDING MATERIALS, 2021, 301
  • [4] Damage analysis of semi-flexible pavement material under axial compression test based on acoustic emission technique
    Cai, Xing
    Fu, Liuxu
    Zhang, Jiayun
    Chen, Xianhua
    Yang, Jun
    [J]. CONSTRUCTION AND BUILDING MATERIALS, 2020, 239
  • [5] Chen H, 2023, INT J MODEL SIMUL SC, V14, DOI [10.1142/S1793962324500016, 10.1145/3549823.3549824, 10.1080/10298436.2021.2020269]
  • [6] Effects of actual loading waveforms on the fatigue behaviours of asphalt mixtures
    Cheng, Huailei
    Sun, Lijun
    Wang, Yuhong
    Chen, Xingyu
    [J]. INTERNATIONAL JOURNAL OF FATIGUE, 2021, 151
  • [7] Fatigue behaviours of asphalt mixture at different temperatures in four-point bending and indirect tensile fatigue tests
    Cheng, Huailei
    Liu, Jianing
    Sun, Lijun
    Liu, Liping
    Zhang, Yining
    [J]. CONSTRUCTION AND BUILDING MATERIALS, 2021, 273
  • [8] Assessing damage of reinforced concrete beam using "b-value" analysis of acoustic emission signals
    Colombo, IS
    Main, IG
    Forde, MC
    [J]. JOURNAL OF MATERIALS IN CIVIL ENGINEERING, 2003, 15 (03) : 280 - 286
  • [9] Asphalt rubber concrete fabricated by the dry process: Laboratory assessment of resistance against reflection cracking
    da Silva, Luis
    Benta, Agostinho
    Picado-Santos, Luis
    [J]. CONSTRUCTION AND BUILDING MATERIALS, 2018, 160 : 539 - 550
  • [10] Machine learning based crack mode classification from unlabeled acoustic emission waveform features
    Das, Avik Kumar
    Suthar, Deepak
    Leung, Christopher K. Y.
    [J]. CEMENT AND CONCRETE RESEARCH, 2019, 121 : 42 - 57