Nondestructive Pavement Evaluation Using ILLI-PAVE Based Artificial Neural Network Models
Impact statement: This applied research advances engineering practices of Illinois Department of Transportation in the area of backcalculation of flexible pavement layer properties from Falling Weight Deflectometer field data.

Evaluating structural condition of existing, in-service pavements is a part of the routine maintenance and rehabilitation activities undertaken at the Illinois Department of Transportation (IDOT). In the field, the pavement deflection profiles (or basins) gathered from the nondestructive Falling Weight Deflectometer (FWD) test data are typically used to evaluate pavement structural conditions. This kind of evaluation requires the use of backcalculation type structural analysis to determine pavement layer stiffnesses and as a result estimate pavement remaining life. According to IDOT's mechanistic based pavement analysis and design procedures, recent use of artificial neural network models trained with ILLI-PAVE finite element solutions has proved to give much better results than the statistical algorithms currently in use.