A Non-Destructive Pavement Evaluation for the Development of a Multi Distress Regression Model Integrated with the BACKCSA Model.

This paper highlights the application of non-destructive tests (NDT) to evaluate the pavement for maintenance in a road network. The falling weight deflectometer (FWD) and the network survey vehicle (NSV) test data which is rational in terms of technical, financial, and environmental aspects have been used. The data using NDT devices were collected from a network of roads from Odisha state, India, and analyzed to assess the structural adequacy of the pavements. Further, using the FWD deflection data, the resilient moduli (MR) of the pavements were back-calculated using a cuckoo search (BACKCSA) model developed as a part of this research work. The back-calculated layer moduli (MR) was used as an input for developing the pavement condition index (PCI) prediction model. In addition, the other pavement distresses viz., international roughness index (IRI), rut depth, cracking, and raveling was also collected using the NSV. The data collected for three cycles with a minimum difference of one year between each cycle was used for the development of perdition models. The NSV data was used for developing the multilinear regression (MLR) prediction models for building a comprehensive pavement management system. This paper highlights the novel approach in arriving at the MR, and incorporating the same in MLR models for predicting the maintenance strategy for a road network. [ABSTRACT FROM AUTHOR]