Balancing Acceptance Risks and Pay Factors through Dynamic Modulus Based Performance Prediction Models

Abstract

Several studies have been conducted to examine acceptance risks or pay factors for highway materials and pavements. While guidelines such as AASHTO R-9 have provided desired acceptance risk levels for both contractor and agency, past studies often did not address how to link acceptance risks to pay factors. Thus, there is a need to develop a methodology for systematically quantifying and adjusting pay factors and risks for rational rewards in relation to the material quality acceptance risk level. In phase one of this study, a systematic methodology was introduced to balance the acceptance risk and pay factors, with a novel risk-adjustment factor linking the two. In phase two, the suggested methodology was applied to hot mix asphalt to illustrate the workings of the methodology. The analysis illustrated that, in some cases, adjusting a single acceptance parameter in isolation does not lead to the desired balance between risk levels and pay factors. Therefore, a step-by-step multivariate analysis was applied to achieve the desired balance between agency and contractor risk levels. The proposed methodology aids in quantifying acceptance risks for highway materials based on production quality, provides a means for balancing the risks between agency and contractor, and identifies the process for rewarding reasonable pay factors for construction quality in similar materials.