Computational Method for Determining Voids under Concrete Slabs through FWD Deflections

Abstract

Knowledge of the condition of an existing concrete pavement is vital to the success of any rehabilitation and maintenance project. Accurate mapping of the voids under concrete slabs provides critical information for roadway designers to derive optimum rehabilitation and maintenance strategies. The Falling Weight Deflectometer (FWD) has been used successfully for many years as a forensic engineering tool. However, the literature on applying FWD to detect voids under concrete slabs is quite limited. The FWD defections are influenced by many factors such as the load transfer across slabs, size of void area, slab thickness, and layer moduli of the concrete and supporting layers. To identify and characterize voids under concrete slabs, pavement engineers need computation methods or algorithms for interpretation of FWD deflection basin. In this study, a Finite Element Model (FEM) was applied to address the load transfer between the joints of concrete slabs. Results from sensitivity analysis indicate that there is an exponential relationship between the slab size and the load transfer efficiency. To simply the analysis without conducting FEM analysis each time, a regression equation is established to estimate the effect of slab size on load transfer efficiency. In addition, the proposed method considers the effects of slab size, thickness, and layer moduli. The proposed method has been calibrated and applied to one highway project, where the voids under the concrete slabs have been mapped accurately. It is concluded that the proposed method is very reliable and can accurately detect voids under concrete slabs using the FWD deflection basin.