Abstract
The Rolling Wheel Deflectometer (RWD) offers the benefit to measure pavement deflection without causing any traffic interruption or compromising safety along the tested road segments. This study describes a detailed field evaluation of the RWD system in Louisiana in which 16 different test sites representing a wide array of pavement conditions were tested. Measurements were used to assess the repeatability of RWD measurements, to examine the effect of truck speeds, and to study the relationship between RWD and FWD deflection measurements and pavement conditions. Based on the results of the experimental program, it was determined that the repeatability of RWD measurements was acceptable with an average coefficient of variation at all test speeds of 15%. In addition, the influence of the testing speed on the measured deflections was minimal. The scattering and uniformity of the FWD and RWD data appear to follow closely the conditions of the roadway. Both test methods appear to properly reflect pavement conditions and structural integrity of the road network by providing for a greater average deflection and scattering for sites in poor conditions. RWD deflection measurements were in general agreement with FWD deflections measurements; however, the mean center deflections from RWD and FWD were statistically different for 15 of the 16 sites. This study also developed and validated a direct and simple model for determining the pavement Structural Number (SN) using RWD deflection data. To develop this model, the relationship between the average RWD surface deflection and the peak FWD deflection was investigated. The developed model correlates pavement SN to two RWD-measured properties (average RWD deflection and RWD Index). The developed model was fitted to RWD data collected in 16 road-sections (each 1.5 miles), referred to as research sites, in Louisiana. The model was then validated based on FWD and RWD data collected on 52 road sections in Louisiana. Results showed a good agreement between SN calculations obtained from FWD and RWD deflection testing. While the developed model is independent of the pavement thickness and layer properties, it provides promising results as an indicator of structural integrity of the pavement structure at the network level. The fitting statistics support the use of the proposed model as a screening tool for identifying structurally-deficient pavements at the network level.
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