Inverse analysis of viscoelastic pavement properties using data from embedded instrumentation

The paper deals with inferring the mechanical layer properties of pavement systems by way of inverse analysis. The proposed scheme is based on the availability of sensory gear embedded within the system - collecting different types of response traces resulting from moving wheel loads. The inverse analysis task simultaneously exploits the readings from all available sensors and therefore formulated as a multicriterion optimization problem. Data from an experimental asphalt pavement are employed to demonstrate the scheme. A versatile and computationally efficient layered viscoelastic pavement model is offered and implemented as a forward solver. Recoverable layer properties, elastic and viscoelastic, are derived and also compared with laboratory values. Results and possible future uses of the work are discussed.