Project Details
RESEARCHERS
Yoon, Soojin; Kang, Kyubyung; Yoon, Yoojung; Hastak, Makarand; Ji, Richard
KEYWORDS
Composite pavements, Decision making, Hot mix asphalt (HMA), Pavement maintenance, Portland cement concrete, Reflection cracking
Project description
The assessment of pavement condition rating (PCR) for hot mix asphalt (HMA) surfaces and exposed portland cement concrete (PCC) in composite pavements is an important component of the decision-making process for treating reflective cracking. Visual inspections such as PCR or falling weight deflectometer (FWD) have been conducted as current practices for reflective cracking treatment. However, these evaluation methods are not able to identify the severity of cracking in the underlying PCC slab. , field engineers often tend to rely solely on visual inspection of the HMA surface without performing actual milling operations. Therefore a systematic decision-making process is needed to select appropriate maintenance treatments for reflective cracking in composite pavements. In response to this need, this research proposes a framework for composite pavement maintenance decision making that consists of three modules: (1) field evaluations to assess the condition of the pavement at the joint, (2) development of a PCC pavement condition prediction model to determine the severity of PCC cracking at the joint in a composite pavement, and (3) a treatment selection table to help determine a possible mitigation strategy for the treatment of each reflective crack type. A case study is conducted to validate the proposed prediction model, with the results showing 0.77 accuracy. Therefore the proposed systematic decision-making process is able to provide field engineers with a more accurate treatment selection process for reflective cracking in composite pavements than is currently available. Furthermore, the proposed process can reduce maintenance costs by simplifying field test evaluation methods and alleviating the need for milling the HMA surfaces.