10th International Conference on Concrete Pavements
Research Focus Area
Construction Engineering and Management, Transportation Engineering
Quebec City, Quebec, Canada
The backcalculation of pavement layer moduli from Falling Weight Deflectometer (FWD) measured surface deflections is a challenging task. It can also be formulated as a global optimization problem with the objective of finding the optimal pavement layer moduli values that minimize the error between measured and computed surface deflections. Over the years, several backcalculation methodologies have been developed including the use of soft computing techniques such as Neural Networks (NNs), Genetic Algorithms (GAs), etc. In this paper, Differential Evolution (DE), a stochastic parallel direct search evolution strategy optimization method is integrated with rapid surrogate mapping of Finite Element (FE) solutions through Neural Networks (NNs) in developing an automated rigid pavement backcalculation toolbox.
International Society for Concrete Pavements
Gopalakrishnan, Kasthurirangan and Ceylan, Halil, "Rigid Pavement Backcalculation Using Differential Evolution" (2012). Civil, Construction and Environmental Engineering Conference Presentations and Proceedings. 3.