Automatic Inverse Analysis of Asphalt Pavement Field Aging Based on System Identification

Abstract

Field aging significantly accelerates distresses (fatigue cracking, water damage, etc.) of asphalt pavements due to exposure to the natural environment. Conventional studies explore field aging by laboratory tests of field cores, while little work is devoted to the inverse analysis of aging by nondestructive tests (e.g., falling weight deflectometer (FWD) test). To backcalulate the aging parameters accurately and automatically, an inverse analysis method of asphalt pavement field aging was proposed based on System Identification (SID) in this study. In this inverse procedure, a kinetics-based two-reaction field aging model was employed as the theoretical aging model and the parameter adjustment algorithm was developed based on sensitivity analysis. Fifty sections from four different climate zones in Long Term Pavement Performance (LTPP) database were selected for investigation, where backcalculated moduli from LTPP and field aging temperatures determined by a pavement hourly temperature model were utilized. The results indicated that SID was feasible to inversely analyze the field aging of asphalt pavements automatically with high accuracy and efficiency. To investigate the factors affecting aging parameters, the multiple linear regression analysis and one-dimensional sensitivity analysis were performed. Among those variables, shortwave radiation and cloud cover showed the dominant effects on field aging resistance.