Analysis demonstrates strong correlations in pavement structure assessment techniques, highlighting effective management strategies.
Context: Pavement condition data are a fundamental component of pavement management systems (PMS) and play a critical role in structural evaluation. The quality of these data directly influences decision-making processes at the network, project, or research level particularly regarding the pavement project life cycle. Method: This study aimed to assess 18 techniques for evaluating the structure of flexible pavements, utilizing both non-destructive (NDT) and destructive (DT) testing. Following a comprehensive review of the consulted techniques, proprietary models were developed and implemented across multiple projects to structurally evaluate in-service pavements. Statistical analysis was employed to determine the relationships between parameters, distinguishing between those based on empirical and mechanistic approaches. Results: The application of evaluation techniques revealed that parameters such as radial strain (εrca), vertical strain (εzsr), and the structural number exhibit a strong correlation when categorized within the same approach. Conversely, their correlation is moderately strong when differing approaches are used. Additionally, models relying solely on deflection basin data demonstrated high correlation with rigorous methods that incorporate thickness data. Conclusions: These findings underscore the practical value of the developed models in pavement management at the network level, offering cost-effective solutions that enhance the detection of structural deficiencies and inform maintenance and rehabilitation strategies.
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Suárez et al. (2025) studied this question.
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