Abstract
Appropriate characterisation of individual layer properties is crucial for mechanistic analysis of flexible pavements. Typically in inverse analyses, pavements are modelled as elastic or nonlinear elastic to obtain layer material properties through non-destructive falling weight deflectometer (FWD) testing. In this study, a layered viscoelastic–nonlinear forward model (called LAVAN) was used to develop a genetic algorithm-based backcalculation scheme (called BACKLAVAN). The LAVAN can consider both the viscoelastic behaviour of asphalt concrete (AC) layer and nonlinear elastic behaviour of unbound layers. The BACKLAVAN algorithm uses FWD load-response history at different test temperatures to backcalculate both the (damaged) E(t) and |E*| master curve of AC layers and the linear and nonlinear elastic moduli of unbound layers of in-service pavements. The BACKLAVAN algorithm was validated using two FWD tests run on a long-term pavement performance section. Comparison between the backcalculated and measured results indicates that it should be possible to infer linear viscoelastic properties of AC layer as well as nonlinear elastic properties of unbound layers from FWD tests.
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