An evaluation of the built-in temperature difference input parameter in the jointed plain concrete pavement cracking model of the Mechanistic–Empirical Pavement Design Guide

2011 ◽  
Vol 12 (3) ◽  
pp. 215-228 ◽  
Author(s):  
J.M. Vandenbossche ◽  
F. Mu ◽  
J.J. Gutierrez ◽  
James Sherwood
Keyword(s):  
Temperature Difference ◽  
Input Parameter ◽  
Plain Concrete ◽  
Concrete Pavement ◽  
Pavement Design ◽  
Design Guide

Adaptation and Calibration of the Faulting Model for Thin Concrete Pavements

2021 ◽  
Author(s):  
Carlos Echevarría ◽  
Juan Pablo Covarrubias
Keyword(s):  
High Speed ◽  
Field Data ◽  
Plain Concrete ◽  
Concrete Pavement ◽  
Comfort Level ◽  
Concrete Pavements ◽  
Differential Model ◽  
Pavement Distress ◽  
Design Guide ◽  
Design Software

Joint faulting is a pavement distress that affects the comfort level of jointed plain concrete pavements. The appearance of joint faulting usually occurs in areas of high traffic of trucks at high speed. Variables such as level of rainfall and the erodibility of the subbase increases the magnitude of this phenomenon. To predict joint faulting in Thin Concrete Pavements, the design software OptiPave2, launched in 2012, used the same model developed for the Mechanistic Empirical Pavement Design Guide (MEPDG), which uses an energy differential model. After 6 years of the release of the software and after 10 years since the construction of some thin concrete pavement projects, there are pavements with clear signs of joint faulting and others without. For this reason, the OptiPave2 model was reviewed and compared with field data, concluding that the faulting model needed to be adjusted This new model was calibrated with the data from existing concrete pavement projects.

Characteristics of Jointed Plain Concrete Pavement (JPCP) Built-in Temperature in Different Climate Conditions

2013 ◽  
Vol 723 ◽  
pp. 960-967
Author(s):  
Chang Bin Hu ◽  
Zeng Hua Sun ◽  
Li Juan Wang
Keyword(s):  
Numerical Simulation ◽  
Solar Radiation ◽  
Air Temperature ◽  
Temperature Difference ◽  
Plain Concrete ◽  
Concrete Pavement ◽  
Early Age ◽  
Climate Conditions ◽  
Solar Radiation Intensity ◽  
Basic Temperature

To understand the characteristics of early-age built-in temperature in JPCP, the actual data of construction climate conditions of typical regions in China were investigated. Based on the application of early-age JPCP temperature numerical simulation program, built-in temperature characteristics of early-age pavement in typical regions was analyzed. The results show that the pavement constructed in different climate conditions produce difference characteristics of early-age built-in temperature due to geographical distinction. Positive built-in temperature difference of JPCP is larger in the regions which have difference in temperature between day and night or higher solar radiation intensity, while the negative built-in temperature difference isn’t influenced obviously by different regions and paving conditions. The maximum positive (negative) built-in temperature difference generally appears in pavement constructed in hot summer. The air temperature is the major factor affecting built-in basic temperature. The higher air temperature, results in the higher built-in basic temperature (temperature in slab bottom) is.

Jointed Plain Concrete (JPC) Pavement Variability and Method to Complement JPC Design with 3D Pavement Data

2021 ◽  
pp. 036119812199782
Author(s):  
Georgene Malone Geary ◽  
Yichang (James) Tsai
Keyword(s):  
Crack Detection ◽  
Plain Concrete ◽  
Pavement Design ◽  
Pavement Performance ◽  
Local Calibration ◽  
Design Guide ◽  
Unique Method ◽  
Departments Of Transportation ◽  
Transportation Agencies

3D pavement data are increasing in use and availability and open up new opportunities to evaluate variability in pavements. The majority of information we currently have on existing pavements is the result of the Long Term Pavement Performance Program (LTPP). While the program is comprehensive and the data are immense, the study sections are typically only 500 ft in length, which limits the ability to accurately gauge the variability of the distresses in a pavement over a longer length, especially cracking in Jointed Plain Concrete (JPC) slabs. 3D pavement data already collected by transportation agencies have the opportunity to complement LTPP data to analyze variability and improve the use of LTPP data. This paper presents a unique method to complement LTPP data using 3D pavement data, consisting of four steps: (1) crack detection using 3D pavement data; (2) categorize detected cracks by orientation and extent by slab using 3D slab-based methodology; (3) convert categorized slab level cracking into mechanistic-empirical pavement design guide cracking; and (4) perform local calibration with the 3D converted input values. The method uses 3D pavement data to provide a non-discrete value for percent cracking in GPS-3 LTPP sections for the purposes of local calibration. The proposed method is shown to be feasible using 3D pavement data and two JPC LTPP sections in Georgia. The method could be extended to any of the state Departments of Transportation that have active LTPP sections and are now or will shortly be collecting 3D pavement data.

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