الفهرس 
Research Methodology
PAVEMNT DEFLECTION MEASUREMENTS AND LAYERS’ MODULI BACKCALCULATIONOnly 14 pages are availabe for public view
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Abstract
The American Association of State Highway and Transportation Officials (AASHTO) developed the concept of the pavement Structural Number(SN)which is a numerical value that indicates the pavement structural capacity. This SN changes with time as pavements deteriorate due to exposure to traffic and climatic conditions over its service life. Thus,at any given age of the pavement structure, it is important to determine the Effective Structural Number of the pavement (SNeff) in order to assess the current structural capacity and consequently select the proper maintenance or rehabilitation treatment. Thus, there are many historical models that predict SNeff based mainly on the Falling Weight Deflectometer (FWD) data. One major concern with the majority of these models, is that they ignore the effect of temperature on the backcalculated modulus of the Asphalt Concrete (AC)layer and hence the predicted SNeff values. In addition, these models were either based on limited data from specific local projects or virtual data. Thus, this research aims at evaluating the accuracy of the most recognized historical models for SNeff prediction, namely;COST, Schnoor and Horak, Kavussi et al., Rohde, and Kim et al. after applying temperature correction to the AC layer modulus (EAC) and the FWD peak deflection (Do) to a reference temperature of 21oC. For this purpose, FWD data and backcalculated moduli of pavement layers were retrospectively collected from the Long Term Pavement Performance
(LTPP) database. Fourteen pavement test sections covering the four different climatic regions in the US with 899 FWD test points were used to evaluate and improve the accuracy of these models as compared to the AASHTO 1993 approach which requires the backcalculated moduli. Based on the LTPP database, the uncalibrated modified COST and Schnoor and Horak models produced very highly biased predictions(overpredictions),
while Rhode and Kavussi et al. models moderately underestimated SNeff
and Kim et al. model moderately overestimated SNeff values. The most
prominent models were calibrated and/or simplified. The proposed calibrated/simplified models produced more accurate and less biased SNeff
predictions as compared to the original models. The proposed modified models were also validated using 394 FWD test points from LTPP data and yielded comparable accuracy