Evaluation and Validation of a Model for Predicting Pavement Structural Number with Rolling Wheel Deflectometer Data
| Autor: | Paul W. Wilke, Zhongjie Zhang, Ahmed Hegab, Mostafa A. Elseifi, Kevin Gaspard |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
050210 logistics & transportation
Engineering business.industry Mechanical Engineering 05 social sciences Pavement management Structural engineering Coring Civil engineering Falling weight deflectometer Deflection (engineering) Nondestructive testing 0502 economics and business Network level 0501 psychology and cognitive sciences Screening tool business 050107 human factors Civil and Structural Engineering |
| Zdroj: | Transportation Research Record: Journal of the Transportation Research Board. 2525:13-19 |
| ISSN: | 2169-4052 0361-1981 |
| DOI: | 10.3141/2525-02 |
| Popis: | Because of costs and the slow test process, the use of structural capacity in pavement management activities at the network level has been limited. The rolling wheel deflectometer (RWD) was introduced to support existing nondestructive testing techniques by providing a screening tool for structurally deficient pavements at the network level. A model was developed to estimate structural number (SN) from RWD data obtained in a Louisiana study. The objective for this study was to evaluate the use of the Louisiana model to predict structural capacity in Pennsylvania and to compare the results with those of existing methods. RWD testing was conducted on 288 mi of the road network in Pennsylvania, and falling weight deflectometer (FWD) testing and coring were conducted on selected sites. The prediction from a model used to estimate SN from RWD deflection data was compared statistically with the prediction obtained from FWD testing and from roadway management system records used by the Pennsylvania Department of Transportation to calculate SN. The results of this analysis validated the use of the model to estimate the pavement SN according to RWD deflection data. In general, the predicted SN was in agreement with the SN calculated from the FWD. The original model with the fitted coefficients developed for Louisiana showed an average prediction error of 27%. However, after the model was refitted to the data set from Pennsylvania, the average error dropped to 19%. Results indicated that the model developed for SN prediction from the RWD provided an adequate prediction of SN for conditions different from those for which it was developed in Louisiana. |
| Databáze: | OpenAIRE |
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