Performance Related Specification (PRS) is presently known as the most advanced specification type in asphalt pavement Quality Assurance (QA). One of the major, important features noticed in the PRS QA is that it takes material variability into account in the performance prediction models by applying several essential statistical techniques available in the literature. Therefore, the uncertainty existing in the material properties can consequently be encoded in the evaluation of asphalt mix quality. For this reason, it is of critical significance to correctly utilize the statistical applications in the PRS QA. One of the products of the NCHRP 9-22 project is a computerized quality assurance tool named Quality Related Specification Software (QRSS). The computer program has the capability of quantitatively evaluating the as-constructed asphalt mix quality compared to the as-design mix quality in terms of predicted service life. To stochastically quantify the quality of both as-design and as-built mixes with the consideration of material variability, it was of necessity to utilize several essential statistical techniques and apply them into the QA procedure. This paper presents the techniques utilized and their applications implemented in the QRSS. It includes statistical methods to estimate variance of a multivariate function (e.g. Monte Carlo simulation and Rosenblueth method); conversion methods from distress to service life; expression of predicted distress as well as its service life using probability distributions; and a method to quantify the relative difference in predicted service life between as-design and as-constructed mixes using cumulative distribution.
Samenvatting