Evaluation and Formulation of Assessment Criteria for Dominant Distresses in Preventive Maintenance of Cement Concrete Pavements

• Main Authors: Qiqi Chen, Guanhu Wang, Xuelin Huang, Guanpeng Wang, Ke Li
• Format: Article
• Language: English
• Published: Hindawi Limited 2020-01-01
• Series: Mathematical Problems in Engineering
• Online Access: http://dx.doi.org/10.1155/2020/8645213

Different types of distresses affect cement concrete pavement at different degrees. The determination of dominant distresses of the pavement preventive maintenance (PM) and its judgement standard can provide corresponding basis for PM decision. In this paper, 22 military airports in Northeast China, such as Heilongjiang Province, Jilin Province, and Liaoning Province, were selected to collect the data of pavement distresses. Based on the structural equation model (SEM), the structural relationship between the influencing factors of each distress and the pavement damage was established, and the goodness-of-fit of the model was tested. In addition, through path analysis, the influence degree of five kinds of latent variables such as joint distress, surface distress, vertical distress, repair distress, and fracture distress on pavement damage was obtained. Four distresses, such as corner peeling, surface peeling, surface crack, and interplate slip, were identified as the dominant distresses of PM of cement concrete pavement. On this basis, a binary classification model of confusion matrix was constructed. The basic evaluation index, receiver operating characteristic (ROC) curve, and Kolmogorov–Smirnov (KS) curve were used to comprehensively determine the judgement standard of the dominant distresses of pavement PM from multiple evaluation angles (corner peeling rate ≤ 35%, surface peeling rate ≤ 30%, surface crack rate ≤ 8%, and interplate slip rate ≤ 0.5%). The judgement standard can be combined with the corresponding prediction model to determine the optimal timing of PM of cement concrete pavement and provide pavement maintenance managers with the support of decision-making.