Reliability Methods Applicable to Mechanistic–Empirical Pavement Design Method

Abstract

Pavement design incorporates a large number of variable design parameters. The combination of the variances associated with input variables contributes to component and system reliability, and this combination of variances can have a significant effect on the predicted performance of the pavement. Reliability analysis provides a solution to this design problem. Numerous reliability methods are available and applicable to pavement design. Previously implemented reliability methods incorporate only a few basic reliability concepts, typically by using the first and second moments of the random variables. Additional reliability methods are available to design engineers, and more advanced methods can be easily used in pavement design. Many advanced reliability methods were viewed as excessively and computationally expensive. Advancements in both the methods and the computational power available to the designer make a number of reliability methods cost-efficient. Ultimately, reliability analysis in pavement design is most useful if it can be efficiently and accurately applied to components of pavement design and the combination of these components in an overall system analysis. This study investigates potential reliability methods and discusses their advantages and disadvantages in the mechanistic–empirical design approach to pavement design. The mechanistic–empirical design procedure is used to establish failure limit states for the reliability analysis. The results from numerous reliability methods are compared with a Monte Carlo simulation. The accuracies of the methods in relation to the simulation method and the computational costs are then compared and discussed.