Structural number prediction for flexible pavements using the long term pavement performance data

Abstract

Structural Number (SN) is a numerical value used as pavement structural capacity indicator. This paper reviews the most recognised historical SN prediction models. These models are COST, Schnoor and Horak, Kavussi et al., Rohde, and Kim et al. These models predict the structural number of existing flexible pavement systems (SNeff) based primarily on the Falling Weight Deflectometer (FWD) data. One major drawback 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. The accuracy of the investigated SNeff prediction models after applying temperature correction to the AC layer modulus (E-AC) and the FWD peak deflection (D-o) to a reference temperature of 21 degrees C was examined. FWD data and backcalculated moduli of pavement layers were collected from the Long Term Pavement Performance (LTPP) database. Fourteen pavement test sections covering the four climatic regions in the U.S. with 1293 FWD test points were used to evaluate and improve the accuracy of the investigated models compared to the AASHTO 1993 method. 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 validated using another set of LTPP data and they yielded comparable predictions.