Abstract
The existing methods of asphalt mixture design are deterministic and rely only on the means of design parameters, such as unit weight and volumetric properties. This article presents a new design method of asphalt mixtures that considers the uncertainties of the measured properties and the calculated design parameters, represented by the coefficient of variation (CV). The uncertainties of the measured properties (typically CV < 1 %) propagate through the calculations and could result in high uncertainties in the calculated design parameters (e.g., CV > 40 %) that make them unreliable. The proposed method is developed in the context of the Marshall mix-design method and is applicable to the Superior Performing Asphalt Pavements method with minor modifications. The Taylor series expansion was used to develop the moments (mean and standard deviation) and CV of the calculated design parameters. The developed formulas were verified using Monte Carlo simulation. Criteria for sample acceptance are then presented based on the uncertainties of the design parameters. The uncertainty information is then used to establish confidence intervals for the design parameters, determine the optimum asphalt content, and compare the results with project specifications. Sensitivity analysis of the mix-design parameters is conducted, and practical implications are discussed. Numerical examples are presented to demonstrate the application of the proposed method. The proposed method takes the design of asphalt mixtures one step further toward a reliable performance-based design. As such, the method should be of interest to pavement engineers and practitioners.
