ABSTRACT
Temperature gradients in concrete pavements significantly affect fatigue damage accumulation, with high gradients having the potential to reduce performance under vehicle loads. While temperature profiles are non-linear throughout the depth, an equivalent linear temperature gradient (ELTG) accounts for the effect of temperature in pavement design. Critical ELTG values are difficult to predict because ELTG is affected by design parameters as well as climate conditions and varies diurnally and seasonally. To identify critical parameters which affect ELTG, a database of hourly temperature profiles was generated for a series of jointed plain concrete pavements (JPCP) throughout Pennsylvania. A stepwise regression model was developed with an R2 of 0.81 to determine maximum daily ELTG as a function of the design parameters and climate. This equation can assist engineers in making decisions on when superloads can be transported without significant damage or performing falling weight deflectometer testing will be most informative. Slab thickness, concrete albedo, and daily temperature range (DTR) were the most significant parameters that affected ELTG. A higher albedo showed an equivalent effect in reducing maximum ELTG as increasing the thickness of the slab. This finding can be used to reduce maximum gradients, which will increase the predicted service life of JPCPs.
Acknowledgements
The authors would like to thank Ping Lyu and Josh Kline for their assistance in generating the database of temperature profiles.
Disclosure statement
No potential conflict of interest was reported by the authors.