Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Online Resource
    Online Resource
    SAGE Publications ; 2019
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2673, No. 5 ( 2019-05), p. 407-417
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2673, No. 5 ( 2019-05), p. 407-417
    Abstract: Faulting is a major and commonplace distress in jointed concrete pavement (JCP) that can directly cause pavement roughness and adversely influence the ride quality of a vehicle. Faulting also plays an essential role in concrete pavement design. Notwithstanding the importance of faulting, the accuracy and reasonability of the faulting prediction models that have been developed to date remain controversial. Furthermore, the process of faulting over time is still not fully understood. This paper proposes a novel mechanistic-empirical model to estimate faulting depth at joints in the wheel path in JCP. Two stages within the process of faulting were revealed by the model and are introduced in this study. To distinguish the two stages of faulting, an inflection point, as a critical faulting depth, was directly determined by this model and suggested to be an indicator of the initiation of erosion for concrete pavement design. The proposed model was proven accurate and reliable by using long-term pavement performance data. The parameters in the model were statistically calibrated with performance-related factors by Akaike’s Information Criterion for variable selection and performing stepwise regression.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2019
    detail.hit.zdb_id: 2403378-9
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. Further information can be found on the KOBV privacy pages