Abstract

Portland cement concrete pavements have been constructed in many areas in Argentina that feature heavy traffic and freeways and highways in freezing areas. To predict their performance, computational programs such as the World Bank's HDM-4 may be used. This particular software includes distress models that need to be adjusted to local conditions in order to optimize the evaluation of maintenance strategies and resource allocation. The main objective of this study is to evaluate the performance of concrete pavements in the midwestern region of Argentina by using the HDM-4 software to obtain calibration coefficients for each distress model. A specific methodology for model calibration was applied to concrete pavements of the national road network located in the provinces of San Juan, Mendoza, and Córdoba. Such roads include jointed plain and jointed reinforced concrete pavement (JPCP and JRCP), with an ample range of traffic levels and climate conditions. Calibration coefficients were determined individually for each road and for road groups with similar characteristics; the results were subsequently compared with data calibration results from the Long-Term Pavement Performance database obtained from previous studies. Many similarities were found in the ability of the models to predict distress levels. Some models show an irregular pattern in predicting distress without calibration, but other models show better results, such as those to predict joint faulting and international roughness index.

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