Title: Development of a Simplified Method for Interpreting Surface Deflections for In-Service Flexible Pavement Evaluation
Abstract: A simplified method for evaluating flexible pavements using surface deflection measurements is presented. The horizontal tensile strain at the bottom of hot mix asphalt (HMA) layer that can be estimated from deflection measurements is proposed as a robust parameter for estimating remaining structural capacity and for use in pavement management. This deflection-strain relationship was developed for loading conditions corresponding to both the Falling Weight Deflectometer (FWD) and Rolling Wheel Deflectometer. The layered linear elastic analysis program, JULEA, was used to develop the deflection-strain relationship from the calculated deflection and tensile strain for a suite of randomly generated hypothetical pavement structures. Curvature indices, computed as the difference between the deflection at the center and at an offset distance, were found to be better predictors of HMA layer condition. These indices were used to develop relationships with horizontal tensile strain at the bottom of HMA layer. The relationships were found to be good indicators of the progressive deterioration typically observed in pavements over the design life. The mechanistic-empirical pavement design program CalME was used to compute structural deterioration over the pavement design life. The strain estimates for the FWD loading condition were validated with the field measurements. It is shown that tensile strains at the bottom of HMA layer computed from deflection measurements using the approach presented in this study can be used for the development of structural performance curves in pavement management applications. The proposed approach can also be extended to provide estimates of remaining structural capacity.
Publication Year: 2011
Publication Date: 2011-01-01
Language: en
Type: article
Access and Citation
Cited By Count: 7
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot