3D-Move Simulation of TSDDs for Pavement Characterizations

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Authors

Nasimifar, Seyyedmahdi

Issue Date

2015

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Dissertation

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3D-Move model , Deflection basin index , Dynamic analyses , Pavement Management System , Traffic Speed Deflection Devices

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Abstract

State highway agencies (SHAs) spend billions of dollars each year on various transportation infrastructure assets to meet legislative, agency and public expectations. Recently, some organizations in the USA and Europe have developed devices that continuously measure pavement deflection and can reduce the cost associated for network-level pavement data collection. Traffic Speed Deflectometer (TSD), Rolling Wheel Deflectometer (RWD) and Euroconsult, Curviametro (CRV) are such devices that are being used around the world and were evaluated in this study. The proper incorporation of the measurements from these devices to network level pavement management system (PMS) applications requires appropriate, device-specific, analysis methodology. To assess the appropriateness of any proposed methodology, field evaluations in conjunction with analytical models to simulate the TSDDs measurements are required important steps. The Federal Highway Administration (FHWA) commissioned the evaluation of these devices at the MnROAD facility in September 2013. 3D-Move program that has the capability of modeling moving loads and the resulting dynamic pavement responses was used as an analytical tool in this study. Using a variety of independent pavement responses that included surface deflection bowls as well as horizontal strains at the bottom of the AC layers confirmed the ability of the 3D-Move model to simulate TSDD loading under realistic pavement conditions. Using the calibrated 3D-Move software, an analytical investigation was then undertaken to explore relationships between load-induced pavement structural-related response and the corresponding surface deflection basin related indices. A key element was the simulation of pavement deflections using the 3D-Move model with a focus on understanding the parameters that affect the TSDD measurements that included vehicle speed and loadings, and pavement layer properties (thicknesses and stiffnesses). This step enables the use of TSDDs in PMS applications. The outcome of this study facilitated use of TSDDs in network level pavement management system by categorizing pavements based only on AC thickness and then relating DSI200-300 (D200 - D300) and DSI300-900 (D300 – D900) to fatigue and rutting strain, respectively through appropriate equations. The study also provided some practical suggestions to improve the performance of TSDDs in PMS applications.

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