| description abstract | Preventive-maintenance treatments are increasingly being adopted in pavement preservation during recent years. For such treatments to be effective, their selection must be based on the right conditions. This study quantifies the effectiveness of different treatments under different climatic, traffic, and pavement conditions. Regression models were developed to predict the non-wheel-path (NWP) longitudinal cracking for thin overlay, chip seal, slurry seal, crack seal, and control (untreated) sections. The analyses made use of the wet-freeze climate zone long-term pavement performance longitudinal cracking data from the specific pavement study 3 study. For each of the treatments, NWP longitudinal cracking at a given time was predicted using the annual average precipitation, annual average temperature, annual average freeze index, annual average daily traffic, annual average daily truck traffic, structural number, age since construction and age since treatment (AST) corresponding to the time of prediction, and the magnitude of the last distress measured before treatment (DBT). The developed regression models enabled comparison of the effectiveness of different treatments and selection of the best and worst treatments for use under varying conditions. A sensitivity analysis was performed to rank the variables that contributed to more and less cracks. The treatment effectiveness was found to be most sensitive to DBT followed by AST, climate, pavement structural conditions, and traffic. The sensitivity analysis was also used to rank the treatments in terms of effectiveness in mitigating cracks. Overall, chip seal was found to be the most effective treatment followed by slurry seal, thin overlay, crack seal, and untreated. | |
