Modeling Pavement Response to Vehicular Traffic on Ohio Test Road

Abstract

Methods of cost allocation for highway pavement rehabilitation and maintenance activities and pavement management estimations are based on empirical and semiempirical founded predictions that come up short, particularly when a roadway is subjected to heavy multiaxle vehicles. Additionally, materials used in constructing the pavement structure do not always behave in an elastic manner, and the ability to predict the pavement response in the presence of other than elastic material behavior is essential. Finally, prediction of pavement states of distress, based on empirical methods, and elastic material behavior is inadequate, particularly when traffic of heavy vehicles is involved. Battelle has been working on a mechanistic approach to address the issues and concerns at the core of current pavement design methods. The overall approach consists of combining three major software modules—a structural module that includes a general primary response model, a material characterization module, and a damage and distress module—are interconnected so that the influence of one on the other is continually updated. Four miles of highway pavement have been heavily instrumented with structural and environmental sensors so that pavement response can be monitored on both short- and long-term bases. Field test results from these pavements have been acquired and, along with laboratory data, have been used to partially validate and provide insight into pavement behavior under various loading conditions. The unique requirements for the design and implementation of the structural and environmental sensing elements are discussed. The mechanistic aspects in the software for the structural and material models are described, and predicted and field-measured results are compared.