Application of Sampling Strategies for Hot-Mix Asphalt Infrastructure: Quality Control-Quality Assurance Sampling; Specification for Performance Test Requirements

Abstract

Due to the lack of a rational, effective, and systematic quality control-quality assurance (QC/QA) methodology, the nonconformity of construction quality with design requirements for public works, especially for civil engineering infrastructure systems, can result in increased expenditures over time. Thus, development of a rational QC/QA methodology to ensure that the construction quality complies with the design requirements should have a high priority. The limited sample size constrained by the consideration of cost and time may result in the misjudgement that the construction quality does not meet the design requirements. In this chapter, the effects of sampling size, sampling strategies, and acceptance/rejection criteria for QC/QA projects using statistically based decision making in hot-mix asphalt (HMA) construction are presented. Also, there has developed an increased interest recently in ensuring that the HMA as placed will meet certain performance requirements by measuring the actual performance parameters on test specimens prepared from in situ samples rather than from surrogate values such as asphalt content and aggregate gradation. Examples include direct measures of mix permanent deformation characteristics and fatigue characteristics, mix stiffness, and degree of compaction as measured by air-void content. Determination of sample size is primarily based on an acceptable error level for a performance parameter specified by the agency. It is not uncommon to base quality assurance by many agencies on three samples. Through the t distributions, discussion is presented as to why it is not appropriate to take only this number of samples for qualityassurance. Based only on three samples in a large project, the agency will have insufficient power to reject the null hypothesis given that the null hypothesis is false unless the project quality delivered by the contractor is extremely poor so that the agency is confident enough to reject the project. In addition to providing a general introduction to fundamental statistics and hypothesis testing, two case studies are used to clarify the relationships among sampling size, sample strategies, and performance specifications (or acceptance/rejection criterion). These include the following: