Application of Genetic Algorithm and Finite Element Method for backcalculating layer moduli of flexible pavements

The backcalculation program, GAPAVE, which uses the Genetic Algorithm (GA) and Finite Element Method (FEM), is developed to predict the layer moduli from Falling Weight Deflectometer (FWD) deflections. The use of the FEM in the forward calculation that incorporates the GA improves the accuracy in backcalculating the pavement layer moduli. The optimum GA parameters are selected from sensitivity analysis for six different pavement structures. It is found that the use of optimal GA parameters suggested from this study can improve the prediction quality in backcalculating the pavement layer moduli. FWD deflection data and resilient modulus test data obtained from the Long-Term Pavement Performance (LTPP) database are used to evaluate the performance of the GAPAVE program. Backcalculated layer moduli for the asphalt concrete and foundation layers are compared against the resilient moduli obtained from laboratory testing. The validation results indicate that GAPAVE with the optimal GA set of parameters can effectively estimate the actual stiffness characteristics of the pavement materials.