01698434

Component

Heavy Weight Deflectometer (HWD) is commonly used in airfield pavement evaluation by means of imposing dynamic loading on pavement surface and measuring surface deflections. This study investigated traditional approaches and soft computing model for predicting airfield pavement responses from surface deflections measured under HWD testing conducted at National Airport Pavement Testing Facility (NAPTF). In the traditional approach, pavement layer moduli were backcalculated and then pavement responses were predicted based on multilayer elastic theory (MLE) and finite element (FE) method. The soft computing model was developed using Artificial Neural Network (ANN), which was trained using the synthetic database that contained surface deflections and critical strains calculated using different combinations of material property, layer thickness, HWD loading magnitude, and pavement temperature. It was found that the backcalculated moduli of asphalt surface layer were similar between MLE and FE methods; however, discrepancies were observed for the backcalculated moduli of unbound materials. In general, the traditional approach of backcalculation and forward calculation overestimated tensile strain in asphalt layers, especially for the pavement section with thin asphalt layer. On the other hand, the results show that the prediction accuracy of soft computing model is better than the traditional method as compared to field measurements. Further analysis of ANN model showed that Area Under Pavement Profile (AUPP) and Surface Curvature Index (SCI) had good correlations with critical tensile strain and shear strain in the asphalt layer, respectively.

This paper was sponsored by TRB committee AFD80 Standing Committee on Pavement Structural Modeling and Evaluation.

19-05505

English

4p

2019

Transportation Research Board 98th Annual Meeting

Digital/other

Figures; Tables

Accuracy; Airport runways; Backcalculation; Finite element method; Neural networks; Soft computing

National Airport Pavement Testing Facility

Heavy weight deflectometers; Layer moduli; Multilayered elasticity theory; Surface deflections

Aviation; Pavements

Transportation Research Board Annual Meeting 2019 Paper #19-05505

TRIS, TRB, ATRI

Dec 7 2018 9:23AM