Effect of Knowledge Level of Layer Thickness on Pavement Structural Number (SN) Determination Based on FWD Data

Document Type : Scientific - Research

Abstract

Pavement evaluation at Network-level is performed with the aim of assessing conditions of pavements, the required maintenance level (i.e. preventive, rehabilitation or reconstruction) or prioritization purposes. The data required to assess network-level pavement evaluation are fewer than the case of project level evaluation. In addition, less pavement analysis and calculation are required. Asphalt pavement structural condition analysis at network level is generally performed using FWD data for determination of pavement layers moduli and effective Structural Number (SNeff). FWD data analysis requires information regarding pavement thickness. These can be determined using GPR or doing core and pit in pavement. Simplification of the collected data and analysis of FWD data are important issues for rapid assessment of road networks. In this study, ten different methods were evaluated in three different levels of thickness requirement (i.e. no information of pavement thickness, knowing pavement total thickness and having thicknesses of each layer) to determine pavement effective structural number. A field analysis was performed applying FWD on seven pavements having different structural numbers (i.e. having low, medium and high SN values). The above analysis was performed and it was revealed that among the various methods, Jameson with correlation coefficient of 0.71 in the category “no information of pavement thickness”; and Wimsatt with correlation coefficient of 0.92 in the category of “knowing total pavement thickness” showed to better represent pavement condition.

Keywords


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