Engineering Framework for Self-Consistent Analysis of Falling Weight Deflectometer Data

Abstract

In pavement engineering practice, the falling weight deflectometer (FWD) is a recognized nondestructive tool to evaluate the mechanical characteristics of layered pavement systems. Unfortunately, elastostatic backcalculation remains the norm in the interpretation of FWD data, even though its underlying (static) analysis is inconsistent with the dynamic nature of the FWD test. Because of wave propagation effects, which are especially pronounced in the presence of a shallow stiff layer, the peak pavement deflections induced by the FWD loading can differ significantly from their static counterparts and thus compromise the conventional backcalculation of pavement moduli. In this study a frequency domain–based preprocessing procedure was developed to extract the static pavement response from the transient FWD records to provide a more consistent input for the elastostatic recovery of pavement profiles. To ensure the fidelity of the educed static deflections, the key drawbacks of typical field FWD data, namely, the baseline offset and the low-frequency noise pollution, were examined and remedied. For pavement engineering applications, the featured preprocessing procedure for extracting the static deflections from dynamic FWD records was implemented in a user-friendly graphical environment, GopherCalc. By comparing the results of the proposed and existing backanalyses applied to both synthetically generated (elastodynamic) data and field records, it was found that the proposed procedure had the potential for mitigating systematic errors associated with the dynamic nature of the FWD test while retaining the computationally effective elastostatic backcalculation scheme.