A probabilistic investigation of long-term field performance of warm mix asphalt pavements

Abstract

Warm-mix asphalt (WMA) has been gaining popularity in sustainable road engineering due to its reduced environmental impacts. However, uncertainties remain regarding its long-term pavement performance compared to hot mix asphalt (HMA). Especially, the critical factors influencing the field performance of WMA are yet to be determined. Hence, this study analyzes the long-term field performance of pavement overlaid with WMA, using data from the Specific Pavement Studies 10 (SPS-10) of the long-term pavement performance (LTPP) program. The evaluation includes 58 field sections from nine projects across the United States, encompassing two WMA types (foaming processing and chemical additive) and their corresponding HMA control sections. Performance indicators such as alligator cracking, longitudinal cracking in the wheel path, transverse cracking, rutting, and roughness (measured by the international roughness index, IRI) were considered. Per-state and per-climate region Bayesian multilevel models were built to account for site- and region-level heterogeneity. The study results demonstrated that pavement with WMA performed equally well to the HMA counterparts under similar conditions, indicating that their potential for widespread application in meeting both performance standards and environmental conservation requirements. Also, WMA technologies did not differ in pavement performance, and thus the field performance of WMA was not a dominant factor in deciding WMA technology types. Furthermore, Bayesian multilevel models proved highly effective in performance data varying across construction sites and regions.

Keywords

• Warm mix asphalt
• Long-term performance
• LTPP
• Bayesian multilevel modeling