Dynamic Backcalculation of Pavement Structure using Multiple Sets of Time-Series Data

Backcalculation analysis is generally greatly affected by errors in the measured deflection data. An average of multiple deflection data sets corresponding to a standard load is normally used in static backcalculation in order to reduce effects of these errors. However, this procedure can not be applied in case of time series data. A rather time consuming procedure is used, where backcalculation is performed using each deflection data set and then an average of the backcalculated pavement layer properties is determined. This paper proposes a new method where multiple sets of time series data can be used simultaneously in dynamic backcalculation to determine an average result. Computation time is similar to the case of one data set. Domain of analysis and the number of nodes are also examined.