An integrated structural model for predicting rigid pavement damage based on NDT survey data

Designed to withstand repetitive cycles of aircrafts’ static loads and thermic gradients, apron rigid pavement requires long-term serviceability and structural reliability throughout its service period. Due to the vast dimensions of concrete superstructural asset monitored, international and local aviation regulative agencies advise the implementation of an effective Airport Pavement Management System (APMS), leading to structural analysis and residual service life prediction models of the existing asset to support airport handlers in construction and maintenance strategies.
Relying on measuring paved areas’ evolutive conditions, in an APMS it is recommended to carry out space and time consistent multi-source Non-Destructive Testing techniques (NDT). At the present state-of-the-art geometrical and mechanical properties collected through NDT surveys are individually analysed and compared against correspondent alarm thresholds. The disaggregated elastic and structural information from each NDT technique conveys into a pavement mechanics analysis, usually performed through finite element methods at the scale of sample unit of measurement. The resultant stress field for the specific superstructural configuration feeds a cumulative concrete fatigue damage and residual life model based on sample unit’s preset service period and traffic mix.
To accurately estimate priority of intervention assessing functional entity, degrading condition severity and asset importance, a structural model for rigid pavement elastic analysis based on NDT survey data needs to be further refined at the level of detail of each elementary unit surveyed. By using the same level of detail of NDT data collection stage, an analytical approximate solution for rigid mechanic and thermic rigid pavement rheological behaviour is being developed as an interoperable and computationally efficient alternative to finite element methods. Conveying NDT sampled properties for each elementary unit into a related structural and damage analysis, an effective pavement management system could be achieved for data-driven and airport-wise scalable asset management.