Abstract

Currently, there is no simple procedure available to identify structurally weak pavement sections using Falling Weight Deflectometer (FWD) data at the network level (e.g., city, state or province). A simple method is needed to determine the structural condition of pavement sections that can be directly implemented and automated in the current pavement databases. The method needs to be simple enough to be used with a network level FWD database for the purpose of numerically ranking pavement sections at the network level from good to poor. Backcalculation has been utilized to obtain layer moduli and determine overlay (new added surface pavement layer) thickness at the project level. However, the use of the backcalculation technique at the network level is complicated and time consuming, which makes it not practical for network level pavement sections assessment. The objective of this research study is to develop a simple analysis method to determine the structural condition of pavements using currently available non-destructive testing (NDT) deflection measurement devices at the network level that can be directly implemented and automated in the database of a typical transportation agency (such as TxDOT). In addition, this proposed study aims to run an advanced 3D-Move simulation analyses to mimic the FWD deflection bowl obtained from the field in an effort, for the first time, to reduce the need to run extensive FWD testing on the network level. The proposed deflection and area ratio parameters will serve as indicators of the pavement structure’s capacity to carry heavy traffic. In addition, deflection and area ratio parameters will help with the overall evaluation of the health of the road network and the determination of the remaining life of individual road segments. This will allow transportation officials to obtain a clearer view of the state of the network. Therefore, they can have more accurate estimation of the required funds to maintain the highway network at a certain desired level. With this approach, more informed decisions about the most suitable maintenance and rehabilitation strategies can be made. Since the deflection data that are commonly collected by the agency will be utilized in this approach, the approach will be economically feasible. The developed single and overall parameter, CAr’ was well related to the number of load repetitions to fatigue failure, Nf, with a coefficient of determination, R2 of 0.96. The single parameter can be easily implemented in the PMS databases and thus, CAr’ will help the South-Central state DOTs and local highway agency officials to make more informed decisions about the most suitable maintenance and rehabilitation strategies.

Date of publication

Spring 3-30-2018

Document Type

Thesis

Language

english

Persistent identifier

http://hdl.handle.net/10950/1163

Committee members

Mena Souliman, Torey Nalbone, Michael Gangone, Stefan Romanoschi,

Degree

Master of Science in Civil Engineering

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