Parameter Identification of Asphalt Pavements Subjected to Moving Loads

Abstract

Pavements generally demand necessary maintenance and rehabilitation to maintain their service performance in the whole lifespan. The maintenance and rehabilitation strategies are usually formulated based on the results of non-destructive testing, in which the traffic speed deflectometer (TSD) test is an efficient tool for pavement detection at network level. In this paper, the TSD test on asphalt pavements is simulated by a spectral element method-based theoretical model, which is further combined with a nonlinear minimisation algorithm to achieve parameter identification. After conducting parameter sensitivity analysis, a case study is used to demonstrate the ability of the proposed parameter identification technique. The results show that this technique can deal with TSD measurements to identify the structural parameters of asphalt pavements. The presented parameter identification technique is a reliable tool to predict the structural parameters of asphalt pavements by analysing corresponding TSD measurements, which is beneficial to formulate accurate maintenance and rehabilitation strategies.