Abstract

This research presents a method that accounts for variability in the principal design input variables for fully flexible highway pavements and assesses their effect on pavement performance. Variability is described by statistical terms such as mean and standard deviation and by its probability density distribution. Statistical characterisation of the variation of asphalt layer thickness, asphalt stiffness and subgrade stiffness is addressed. A model is then proposed that represents an improvement on the method of equivalent thickness for the rapid and repeated calculation of performance life. A Monte Carlo analysis is used to estimate pavement performance life to account for uncertainty of input variables and to calculate the probability of failure of a pavement structure. The output is a statistical assessment of the estimated pavement performance. Rather than the single deterministic result that would be derived by considering average values of input variables, a range of values and probabilities is found for any particular outcome. The probabilistic approach offers a way of incorporating risk assessment considerations that are vital for whole-life-cycle economic analysis and decisions. The paper investigates how variability affects the life-cycle cost of a pavement over a 60-year analysis period.

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