Skip to main content
SpringerLink
Log in

Research on pavement cracking possibility based on the load mechanical response

  • Article
  • Published:
Science China Technological Sciences Aims and scope Submit manuscript

Abstract

Cavities under roads are one of the main reasons for early structural damage to pavements. It is necessary to conduct a structural analysis of road sections with cavities and evaluate the possibility of pavement cracking caused by different cavity sizes. In this study, an analysis method for evaluating the possibility of pavement cracking based on the load-mechanical response is proposed. An example library of the mechanical response of asphalt concrete (AC) pavements was established by numerical simulation. Based on the tensile cracking characteristics of pavements in the mechanical response research, the tensile strain at the bottom of the AC layer was selected as the key analysis parameter. Sensitivity analysis of the tensile strain was conducted, and the main factors controlling pavement cracking were determined. A tensile strain response prediction model was established using multiple linear regression, and its reliability was verified. The cavity influence coefficient (CIC) and pavement cracking factor (PCF) were constructed to analyze the cracking possibility. The variation in PCF with the cavity size and pavement structure parameters was studied. A quantitative relationship between the depth and length of the cavity for a given PCF was obtained. This law conforms to a power function. The possibility of pavement cracking can be determined by measuring the cavity size. Compared to the existing cavity management system, the proposed method provided analysis results of the cracking possibility that were more consistent when the cavity depth was small and the length was long. The findings of this study provide new insights for evaluating the possibility of pavement cracking.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Fernandes F M, Pais J C. Laboratory observation of cracks in road pavements with GPR. Construct Build Mater, 2017, 154: 1130–1138

    Article  Google Scholar 

  2. Huang W, Liang S M, Wei Y. Surface deflection-based reliability analysis of asphalt pavement design. Sci China Tech Sci, 2020, 63: 1824–1836

    Article  Google Scholar 

  3. Norouzi Y, Ghasemi S H, Nowak A S, et al. Performance-based design of asphalt pavements concerning the reliability analysis. Construct Build Mater, 2022, 332: 127393

    Article  Google Scholar 

  4. Zhong Y H, Zhang B, Guo C C, et al. Research on the identification method for void location of semi-rigid base pavement. Appl Mech Mater, 2011, 94–96: 1257–1260

    Article  Google Scholar 

  5. Rasol M, Pais J C, Pérez-Gracia V, et al. GPR monitoring for road transport infrastructure: A systematic review and machine learning insights. Construct Build Mater, 2022, 324: 126686

    Article  Google Scholar 

  6. Xu X, Zeng Q, Li D, et al. GPR detection of several common subsurface voids inside dikes and dams. Eng Geol, 2010, 111: 31–42

    Article  Google Scholar 

  7. Liu H, Shi Z S, Li J H, et al. Detection of road cavities in urban cities by 3D ground-penetrating radar. Geophysics, 2021, 86: WA25–WA33

    Article  Google Scholar 

  8. Lai W W L, Chang R K W, Sham J F C. A blind test of nondestructive underground void detection by ground penetrating radar (GPR). J Appl Geophys, 2018, 149: 10–17

    Article  Google Scholar 

  9. Li T, Zhang Z Z, Zong L D. Study of formation mechanism and prediction of sinkholes in soil stratum induced by subterranean cavity (in Chinese). Rock Soil Mech, 2015, 7: 1995–2002

    Google Scholar 

  10. Bianchi Fasani G, Bozzano F, Cardarelli E, et al. Underground cavity investigation within the city of Rome (Italy): A multi-disciplinary approach combining geological and geophysical data. Eng Geol, 2013, 152: 109–121

    Article  Google Scholar 

  11. Sun L, Chen C, Sun Q Q. Experimental and finite element analyses on the corrosion of underground pipelines. Sci China Tech Sci, 2015, 58: 1015–1020

    Article  Google Scholar 

  12. Mei C, Liu J H, Shi H Y, et al. Exploring impact of street layout on urban flood risk of people and vehicles under extreme rainfall based on numerical experiments. Sci China Tech Sci, 2023

  13. Wang X W, Xu Y S. Investigation on the phenomena and influence factors of urban ground collapse in China. Nat Hazards, 2022, 113: 1–33

    Article  Google Scholar 

  14. Lai W W L, Chang R K W, Sham J F C, et al. Perturbation mapping of water leak in buried water pipes via laboratory validation experiments with high-frequency ground penetrating radar (GPR). Tunnell Undergr Space Tech, 2016, 52: 157–167

    Article  Google Scholar 

  15. Guo X L, Yang K L, Guo Y X. Leak detection in pipelines by exclusively frequency domain method. Sci China Tech Sci, 2012, 55: 743–752

    Article  Google Scholar 

  16. Chen C Y, Xiao M, Jia H, et al. The genesis of urban underground roads diseases and classification of engineer (in Chinese). Bull Surv Mapp, 2013, 5–9

  17. Zhang C P, Zhang D L, Wang M S, et al. Catastrophe mechanism and control technology of ground collapse induced by urban tunneling (in Chinese). Rock Soil Mech, 2010, Supp.1: 303–309

  18. Kong F C, Lu D C, Ma Y D, et al. Novel hybrid method to predict the ground-displacement field caused by shallow tunnel excavation. Sci China Tech Sci, 2023, 66: 101–114

    Article  Google Scholar 

  19. Xiao W X, Qian J S. Analysis of the evolution of subgrade cavity of urban road (in Chinese). Trans Sci Tech, 2016, 02: 125–127

    Google Scholar 

  20. Shi G, Wang Y X, Wu T Y, et al. Model experiments on ground collapse under traffic roads (in Chinese). Chin J Undergr Space Eng, 2020, 16: 1202–1209

    Google Scholar 

  21. Qi G, Wang Z, Chen Y, et al. Analysis of instability mechanism and induced cause of urban pavement in Xining City, China. Adv Mater Sci Eng, 2022, 1–12

  22. Chen A, Zhao Y, Li P, et al. Crack propagation prediction of asphalt pavement after maintenance as a function of initial cracks distribution. Construct Build Mater, 2020, 231: 117157

    Article  Google Scholar 

  23. De Giorgi L, Leucci G. Detection of hazardous cavities below a road using combined geophysical methods. Surv Geophys, 2014, 35: 1003–1021

    Google Scholar 

  24. Ye Z, Zhang C, Ye Y. Principle of a low-frequency transient electromagnetic radar system and its application in the detection of underground pipelines and voids. Tunnell Undergr Space Tech, 2022, 122: 104392

    Article  Google Scholar 

  25. Yang L Q, Han Z J, Guo C C, et al. An innovative solution for the dynamic response of buried pipelines in layered transversely isotropic soil under pavement structures. Comput Geotech, 2022, 143: 104602

    Article  Google Scholar 

  26. Xiang P, Wang H. Optical fibre-based sensors for distributed strain monitoring of asphalt pavements. Int J Pavement Eng, 2018, 19: 842–850

    Article  Google Scholar 

  27. Wang H, Xiang P, Jiang L. Optical fiber sensor based in-field structural performance monitoring of multilayered asphalt pavement. J Lightw Technol, 2018, 36: 3624–3632

    Article  Google Scholar 

  28. Wang H, Xiang P. Strain transfer analysis of optical fiber based sensors embedded in an asphalt pavement structure. Meas Sci Technol, 2016, 27: 075106

    Article  Google Scholar 

  29. Wang M, Li S C, Liu R T, et al. Failure mechanism of void road under vehicle load (in Chinese). Highway, 2022, 7: 63–72

    Google Scholar 

  30. Zhu X Y, Chen W Q, Huang Z Y, et al. Fast multipole boundary element analysis of 2D viscoelastic composites with imperfect interfaces. Sci China Tech Sci, 2010, 53: 2160–2171

    Article  MATH  Google Scholar 

  31. Wang W, Su J Y, Ma D H, et al. Integrated risk assessment of complex disaster system based on a non-linear information dynamics model. Sci China Tech Sci, 2012, 55: 3344–3351

    Article  Google Scholar 

  32. Li Z X, Shi X L, Cao J D, et al. CPSO-XGBoost segmented regression model for asphalt pavement deflection basin area prediction. Sci China Tech Sci, 2022, 65: 1470–1481

    Article  Google Scholar 

  33. Tan Y, Long Y Y. Review of cave-in failures of urban roadways in China: A database. J Perform Constr Facil, 2021, 35: 04021080

    Article  Google Scholar 

  34. Kuliczkowska E. Risk of structural failure in concrete sewers due to internal corrosion. Eng Fail Anal, 2016, 66: 110–119

    Article  Google Scholar 

  35. Kuliczkowska E. The interaction between road traffic safety and the condition of sewers laid under roads. Transp Res Part D-Transp Environ, 2016, 48: 203–213

    Article  Google Scholar 

  36. Kuliczkowska E, Parka A. Management of risk of tree and shrub root intrusion into sewers. Urban Forry Urban Greening, 2017, 21: 1–10

    Article  Google Scholar 

  37. JGJ/T 437-2018. Standard for Comprehensive Detection and Risk Evaluation of Underground Disasters in Urban Area. Beijing: Ministry of Housing and Urban-Rural Development of the People’s Republic of China, 2018

    Google Scholar 

  38. Lee K, Park J, Byeong-Hyun C, et al. Analysis of influencing factors on cavity collapse and evaluation of the existing cavity management system. J Korean Geosynth Soc, 2018, 17: 45–54

    Google Scholar 

  39. Zhu X, Zhang Q, Chen L, et al. Mechanical response of hydronic asphalt pavement under temperature—Vehicle coupled load: A finite element simulation and accelerated pavement testing study. Construct Build Mater, 2021, 272: 121884

    Article  Google Scholar 

  40. JTG D50-2017. Specifications for Design of Highway Asphalt Pavement. Beijing: Ministry of Transport of the People’s Republic of China, 2017

    Google Scholar 

  41. Chen X B, Zhao R L, Tong J H, et al. Critical load position for cavities beneath CRCP slab under vehicle loading. J Southeast Univ (English Ed), 2016, 1: 78–84

    Google Scholar 

  42. Mateos A, Millan M A, Harvey J T, et al. Mechanisms of asphalt cracking and concrete-asphalt debonding in concrete overlay on asphalt pavements. Construct Build Mater, 2021, 301: 124086

    Article  Google Scholar 

  43. Cui Y N, Xing Y M, Ni W C. Micromechanical characteristics of the asphalt mixture in bending condition. Sci China Tech Sci, 2013, 56: 392–397

    Article  Google Scholar 

  44. Zhu S Y, Fu Q, Cai C B, et al. Damage evolution and dynamic response of cement asphalt mortar layer of slab track under vehicle dynamic load. Sci China Tech Sci, 2014, 57: 1883–1894

    Article  Google Scholar 

  45. Bańkowski W. Evaluation of fatigue life of asphalt concrete mixtures with reclaimed asphalt pavement. Appl Sci, 2018, 8: 469

    Article  Google Scholar 

  46. Zhou L, Ling J M, Lin X P. Prediction model for fatigue crack of asphalt pavement with environmental factors considered (in Chinese). Chin J High Trans, 2013, 6: 47–52

    Google Scholar 

  47. Zhao J, Wang H. Mechanistic-empirical analysis of asphalt pavement fatigue cracking under vehicular dynamic loads. Construct Build Mater, 2021, 284: 122877

    Article  Google Scholar 

  48. Song Y S, Ding Y L. Fatigue monitoring and analysis of orthotropic steel deck considering traffic volume and ambient temperature. Sci China Tech Sci, 2013, 56: 1758–1766

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Civil Engineering, Geotechnical and Structural Engineering Research Center, Shandong University, Jinan, 250061, China

    Meng Wang, ShuCai Li, RenTai Liu, ChunYu Zhang, ZhiJing Zhu & JiWen Bai

  2. College of Pipeline and Civil Engineering, China University of Petroleum (East China), Qingdao, 266580, China

    LianZhen Zhang

Authors
  1. Meng Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. ShuCai Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. RenTai Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. ChunYu Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. ZhiJing Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. LianZhen Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. JiWen Bai
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to RenTai Liu.

Additional information

This work was supported by the National Key Research and Development Program of China (Grant Nos. 2020YFB1600504, 2021YFB2600800), and the Major Scientific and Technological Innovation Projects in Shandong Province (Grant No. 2020CXGC011403).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, M., Li, S., Liu, R. et al. Research on pavement cracking possibility based on the load mechanical response. Sci. China Technol. Sci. 66, 3549–3561 (2023). https://doi.org/10.1007/s11431-023-2434-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11431-023-2434-4

Search

Navigation